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evor

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更新时间2026年7月13日 15:04

Main 9-step Evor tick loop with meta-evolution, doom-loop detection, and parallel candidate scheduling

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在 Manus 中运行

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it-dainb

it-dainb/oh-my-evor

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Step 0 — Run Startup (once, before the first tick)

Before Step 1 of the first tick, guarantee the hardware profile exists — Mutagen and Selector read the capability profile for hardware gotcha-avoidance, and setup's preflight may have been skipped. Call evor_capability to probe hardware and write the capability profile. This is idempotent and cheap (no micro-train).

Confirm capability detection succeeded — if it failed, log a warning and continue with cpu_only defaults.

Use TaskCreate to open a tracking task for this run (title: "Mission <mission_id> — tick loop"). Use TaskUpdate to mark each tick's step progress as the loop advances.

Step 1 — Select

Read the current tree state via evor_tree_read. Apply UCB1 selection policy (or the current selection policy from run state) to choose the parent node(s) for this tick.

selected = evor_select(run_id, strategy=current_strategy, count=ResourcePlan.concurrency)

If the frontier has ≥2 nodes from distinct lineages with scores within 10% of each other, flag to Mutagen that a crossover proposal is eligible this tick.

Step 2 — Ideate

Spawn Mutagen and Sage as REAL sub-agents. Do NOT write proposals or citations yourself.

Task(subagent_type="oh-my-evor:evor-mutagen", description="Tick <n> proposals", prompt="Run dir: <run_dir>. Tick: <n>. Parent node(s): <ids>. Wildness: <w>. Generate N=<concurrency> proposals and write ticks/<n>/mutagen/proposals.json per your write-as-you-go contract.").
- POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "mutagen" }). If it returns {error:"not found"}, re-spawn Mutagen with a corrective note. Never fabricate the artifact.
Write Mutagen's investigation_queries[] to the tick handoff via evor_write_handoff({ run_id, tick: n, data: { to: "sage", investigation_queries: [...] } }).

P1-8 — Conditional Sage gate (wiki+gotcha first; Sage only when needed): Before spawning Sage, call evor_wiki_query and evor_gotcha_query for each angle in investigation_queries[]. Classify each query as wiki-resolved, gotcha-resolved, or unresolved.

Skip Sage entirely (and mark all queries resolved from wiki/gotcha) when ALL of the following hold:
- All investigation_queries are wiki-resolved (wiki returned a confirmed lesson for each angle)
- The proposal's approach_family is a known recipe already run this mission (not new to the run)
- wildness < 0.7 (parametric / familiar territory; low surprise risk)
- approach_family != "data-acquisition" (no sourcing due diligence needed)
Spawn Sage when ANY of the following is true:
- One or more investigation_queries are NOT wiki-resolved after the wiki+gotcha check
- approach_family is new to this run (first tick using this family in this mission)
- wildness >= 0.7 (structural or high-exploration proposal; external grounding adds value)
- approach_family == "data-acquisition" (license sourcing requires Sage's Tier-1 search)
When spawning Sage (narrowed scope): pass the UNRESOLVED angles only; wiki-resolved angles are already handled. Include the wiki hit IDs in the spawn prompt so Sage skips them.

Task(subagent_type="oh-my-evor:evor-sage", description="Tick <n> grounding", prompt="Run dir: <run_dir>. Tick: <n>. Read the tick handoff via evor_read_handoff and answer the UNRESOLVED investigation_queries (wiki-resolved angle IDs already handled: [<ids>]). Write ticks/<n>/sage/findings.json.").
- POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "sage" }). If it returns {error:"not found"}, re-spawn Sage.
Attach Sage's findings to the matching proposal's citations.

Run Mutagen then Sage sequentially, or both in parallel when CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1. proposals.json and findings.json are the SUB-AGENTS' outputs — you never author them.

Step 3 — Hypothesis Registration

For each proposal returned by Mutagen:

Confirm the Hypothesis is populated (statement + quantified prediction).
Register the Hypothesis in the run state via evor_state_write (append to hypotheses[] list).
Assign a hypothesis_id and set it on the proposal.

Step 4 — Critique

P1-7/P1-13 — Deterministic pre-screen before spawning Selector: Call evor_validate_proposals({ run_id, tick }) to run deterministic checks (field presence, numeric types, schema, H001/H002/H003/H004 fast-path) on all proposals BEFORE spawning Selector. The result classifies each proposal as "fast_pass", "fast_reject", or "needs_llm". Pass the classification result in Selector's spawn prompt. Selector skips full LLM gate evaluation for fast_pass proposals (write approved verdict immediately) and only runs the complete 7-gate loop for needs_llm ones. fast_reject proposals are dropped before Selector is invoked. This eliminates full LLM evaluation cost for structurally clean, low-risk proposals.

Spawn Selector as a REAL sub-agent in a SEPARATE context. Do NOT approve/reject proposals yourself — the whole point is an independent critic that did not generate the proposals it gates.

Task(subagent_type="oh-my-evor:evor-selector", description="Tick <n> gate", prompt="Run dir: <run_dir>. Tick: <n>. Read proposals via evor_read_artifact(run_id, tick=<n>, agent='mutagen'). evor_validate_proposals result: <classification_json>. fast_pass proposals: write approved verdict immediately. needs_llm proposals: run full 7-gate evaluation. Write your verdict via evor_write_artifact.").

POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "selector" }). If it returns {error:"not found"}, re-spawn Selector.
Read the verdict; collect approved proposals. If zero pass, trigger Doom-Loop_Detection.
The rejection reasons are already in the verdict artifact; append a DecisionLogEntry summarizing them via evor_state_write.

Step 5 — Implement + Run

For each approved proposal, spawn Forge as a REAL sub-agent. Do NOT write or run training code yourself.

Task(subagent_type="oh-my-evor:evor-forge", description="Implement <proposal_name>", prompt="Run dir: <run_dir>. Tick: <n>. Proposal name: <proposal_name>. Materialize the genome for this proposal, instrument telemetry via EVOR_TELEMETRY_PATH env-path append, store the delta, run the harness/training, and write your artifacts via evor_write_artifact.").

Pass the proposal by NAME. Do NOT pass raw node_id UUIDs or internal path literals. Forge derives its own artifact paths and writes via evor_write_artifact.
POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "forge" }). If it returns {error:"not found"}, re-spawn Forge.
If parallel teams available: launch Forge Tasks concurrently; use Monitor for job_complete. Otherwise run one at a time.
P0-4 — Forge atomic completion contract: evor_read_artifact({ run_id, tick: n, agent: "forge" }) returning successfully is the ONLY signal that Forge's full turn is done. Individual forge-* sub-agent completions (forge-critic, forge-architect, forge-analyst, forge-junior completing their Tasks) are Forge's INTERNAL delegation — they are NOT signals that Forge itself has finished. Do NOT advance to Step 6 until the forge-report artifact is confirmed present. Treating a forge-critic or forge-analyst Task completion as "Forge done" is a protocol violation that corrupts the tick.
Then YOU (orchestrator) call evor_record_node to register each new node, and append a DecisionLogEntry (decision_type="implement", node_ids=[node_id]) via evor_state_write.
Verify the returned node_name is non-null before advancing. Training a candidate without a confirmed node record is a FAILED tick (the Stop hook enforces this).

Step 6 — Evaluate + Integrity

For each completed Forge job:

Call evor_record_eval(run_id, node_id, result) — this auto-triggers the integrity check.
If the integrity check fails, the node is rejected and its integrity_status is set to "failed" — skip promotion. Log failure_reason via evor_state_write.
If the integrity check passes, integrity_status is "passed" and promotion is eligible.

Ingestion Contamination Gate (data-acquisition nodes only):

The integrity check verifies acquisition_contamination_clear: no acquired sample collides with any frozen eval split.
If false: node is rejected at integrity, never promoted to frontier.

Step 7 — Analyze + Learn

For each node where integrity_status="passed", spawn Probe as a REAL sub-agent. Do NOT write lessons or hypothesis verdicts yourself.

Task(subagent_type="oh-my-evor:evor-probe", description="Analyze <node_name>", prompt="Run dir: <run_dir>. Tick: <n>. Node name: <node_name>. Read telemetry via evor_read_artifact, analyze against the registered Hypothesis, and write your findings via evor_write_artifact (lesson entry + hypothesis_verdict).").

Pass the node by NAME (as returned by evor_record_node). Probe reads via evor_read_artifact and writes via evor_write_artifact; it derives its own paths.
POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "probe" }). If it returns {error:"not found"}, re-spawn Probe.
Read the lesson entry from the artifact; call evor_wiki_add(run_id, lesson_entry) to persist it.
Update node.lesson_ids with the returned lesson_id.

P1-4 — Prediction bias tracking (close the producer gap; Mutagen reads this every tick): After the probe artifact is confirmed, extract actual_delta_pp (the numeric metric change Probe measured) and the predicted_gain midpoint from the original proposal's hypothesis. Record the sample:

evor_state_write({ prediction_bias_sample: { predicted_gain: <midpoint_pp>, actual_gain: <actual_delta_pp> } })

Skip this write ONLY when hypothesis_verdict="inconclusive" (no valid prediction error). The server accumulates the bias history; Mutagen reads it each tick via evor_state_read to self-calibrate its quantified predictions — this write is mandatory.

If Probe returns a benchmark upgrade proposal:
- Log it as a DecisionLogEntry (decision_type="meta-evolve") via evor_state_write.
- Apply the benchmark upgrade.
- If consent_granted=true (user confirmed): bump eval_version via evor_state_write, rescore frontier nodes.

Step 8 — Record

For all nodes this tick:

Append DecisionLogEntry to the run state (decision_type="record", node_ids=all_this_tick) via evor_state_write.
Update run state: increment tick count, update best_score if improved, update frontier_ids.
Call evor_state_write with the run-state patch.

Step 9 — Prune / Promote

Promote nodes with integrity_status="passed" to the frontier if fitness_value > current worst frontier node.
Prune nodes: remove nodes with status="done" AND integrity_status="failed" AND depth > pruning_depth_threshold (default 3) from active consideration. Never delete a node record — set status="pruned" only.
Stop check: call evor_check_stop({ run_id }). If it returns { should_stop: true }, proceed to step 4; otherwise continue the loop.
If stop condition met: print final summary, invoke evor-report skill, call evor_plot_report({ run_id }) to render the final tree PNG and HTML, then deliver via SendUserFile. Exit loop.
If continuing: call Meta-Evolution check (see below), use TaskUpdate to mark tick complete, then return to Step 1.

Step 9.5 — BenchmarkUpgrade Re-scoring (conditional)

If a BenchmarkUpgrade was applied in Step 7 and the rescore mode is "sync":

For all frontier nodes not yet scored under the new eval_version: run partial evaluation on the new domains only.
Merge cached per-domain scores (old domains) with new per-domain scores to maintain comparability.
Update fitness_value using the contract's fitness mode.
Nodes not re-scored within rescore_deadline_ticks are demoted to version-specific status.

If rescore mode is "async": schedule re-scoring jobs via evor_schedule without blocking the tick loop.

<Tick_Lifecycle> Every tick follows this mandatory lifecycle wrapping all 9 steps.

Tick Start — Read Prior Tick Handoff If tick_count > 0, call evor_read_handoff({ run_id, to_agent: "orchestrator" }) before beginning Step 1. Incorporate the result's lessons, dominant_family, and next_tick_seed hint into orchestrator context before Step 1. This prevents re-proposing dead-end families and provides Mutagen with the next_tick_seed hint.

Tick Start — Inbox Drain (before Step 1) After reading the tick handoff and before executing Step 1, drain both inboxes:

evor_drain_inbox({ run_id, kind: "remember" })
evor_drain_inbox({ run_id, kind: "signals" })

The remember drain routes <evor-remember> entries to the wiki and gotcha store. The signals drain routes <evor-signal> entries into the deduped signal bus. Both calls return the count drained and atomically truncate the inbox.

Before Each Step N (1–9): Write tick-state Call evor_state_write with a tick_state payload before executing each step:

{
  "tick_state": {
    "tick": "<current_tick_number>",
    "current_step": "<N>",
    "step_status": "running",
    "step_outputs": {},
    "updated_at": "<ISO 8601>"
  }
}

This enables step-level resumability: if the loop is interrupted mid-tick, evor-resume reads current_step and restarts from that step.

After Each Step N: Update step_status Call evor_state_write with an updated tick_state payload to mark the step done:

{
  "tick_state": {
    "tick": "<current_tick_number>",
    "current_step": "<N>",
    "step_status": "done",
    "step_outputs": { "<key>": "<brief summary of step output>" },
    "updated_at": "<ISO 8601>"
  }
}

Tick End — Write Tick Handoff After Step 9 (before the stop-check / next-tick loop decision), call evor_write_handoff with the tick summary:

{
  "tick": "<current_tick_number>",
  "best_score": "<run_state.best_score>",
  "best_node_name": "<name returned by evor_record_node for the best node>",
  "frontier_size": "<len(frontier_ids)>",
  "nodes_this_tick": ["<node_name>"],
  "lessons": ["<lesson_id>"],
  "dominant_family": "<dominant_approach_family_this_tick>",
  "next_tick_seed": "<brief hint for Mutagen: what to explore next based on Probe's lessons>",
  "strategy_state": {
    "wildness": "<strategy.wildness>",
    "selection_policy": "<strategy.selection_policy>",
    "meta_iteration": "<strategy.meta_iteration>"
  }
}

best_node_name and nodes_this_tick use node NAMES as returned by evor_record_node. evor_write_handoff accepts names. Do not carry raw UUIDs across tick boundaries.

At milestones (every 5 ticks, or when best_score improves by ≥5%): call evor_plot_report({ run_id }) then deliver the tree PNG via SendUserFile.

Step-Level Resume Detection When the tick loop starts a new tick (or when /evor-resume invokes this skill), call evor_state_read to retrieve the current tick_state before executing Step 1:

If tick_state.tick == current_tick AND tick_state.step_status == "running" AND tick_state.current_step < 9: an interrupted tick is detected — skip steps 1 through tick_state.current_step - 1 and re-run the interrupted step from the top.
Otherwise: start at Step 1 (fresh tick).

Re-run the interrupted step from its beginning (write tick-state with step_status: "running" again via evor_state_write).

Why This Matters tick-state makes every tick resumable at the step level — an interrupted tick at step 5 restarts from step 5, not step 1. Tick handoffs compound learning across ticks: Mutagen reads the prior handoff and avoids families proven ineffective; Probe's lessons accumulate across ticks rather than being siloed to the current tick's context. </Tick_Lifecycle>

<Meta_Evolution> Adaptive meta-evolve trigger (P1-3): At the end of Step 9 (after promote/prune), ALWAYS call evor_check_plateau({ run_id }) first:

If plateau=true OR consecutive_regression=true in the result → call evor_meta_evolve({ run_id }) IMMEDIATELY, regardless of the tick interval. Log as DecisionLogEntry(decision_type="meta-evolve", rationale="plateau/regression-triggered", strategy_delta=delta) via evor_state_write.
Otherwise → check the fixed interval: if the configured meta-loop interval has elapsed → call evor_meta_evolve({ run_id }) and log normally.

At the configured interval (default 5 ticks) — fixed-interval fallback if no plateau/regression detected. evor_meta_evolve updates the selection strategy. Log as DecisionLogEntry(decision_type="meta-evolve", strategy_delta=delta) via evor_state_write.

If a BenchmarkUpgrade was recently applied (post_upgrade_exploration_ticks > 0):

Override wildness to strategy.post_upgrade_exploration_boost for post_upgrade_exploration_ticks remaining ticks.
Decrement post_upgrade_exploration_ticks each tick.
This exploration boost counteracts convergence risk after the benchmark expands (Risk D-2). </Meta_Evolution>

<Doom_Loop_Detection> Monitor for doom-loop conditions after Step 4 (Critique) in each tick:

Trigger condition: any of:

3 consecutive ticks where zero proposals passed Selector (all rejected).
3 consecutive ticks where Forge produced zero tool calls (harness never invoked).
3 consecutive ticks where all nodes were integrity_status="failed".

Response: immediately inject the following message into the orchestrator context before proceeding:

[DOOM-LOOP DETECTED: 3 consecutive ticks with no approved/runnable candidates. Forcing exploration mode.]

Then apply the following overrides for the next tick:

Set wildness override = 0.9 (maximum exploration) regardless of current strategy settings.
Force approach_family diversity: require Mutagen to generate proposals from 3 distinct families.
If winning_families shows a monopoly (one family in last 5 entries), explicitly exclude that family for one tick.
Log the intervention as DecisionLogEntry(decision_type="meta-evolve", rationale="doom-loop intervention") via evor_state_write. </Doom_Loop_Detection>

<Signal_Routing> The run has a SIGNAL BUS — the shared observation/pain-point stream. You are the ROUTER: you read it and PUSH the relevant slice to each sub-agent (agents also pull depth themselves). A signal is neutral; each lens treats it differently — a brief to Mutagen, a gate to Selector, a default to Forge-architect, an escalate to you.

Tick start — drain the signal inbox (handled by evor_drain_inbox({ run_id, kind: "signals" }) in the Inbox Drain step above). The PostToolUse hook appends <evor-signal> tags to the signal inbox; the drain call routes them into the deduped bus.

Before each sub-agent spawn — PUSH the digest (the mandatory awareness floor). Call evor_signal_digest({ run_id }) to retrieve the compact top-slice (severity≥medium), then inject the result into each sub-agent's Task prompt:

Task(subagent_type="oh-my-evor:evor-mutagen", prompt=... + "\nRecent signals (dream around these): " + digest)

Escalate signals — resolved by the Autonomy Charter, NEVER by asking. When a signal implies the locked contract needs reconciling (eval-saturated → benchmark too easy; label-noise → metric untrustworthy; guard-unsatisfiable → guard mis-specified; placeholder anchors), apply the Monotonic-Honesty Invariant (see <Autonomy_Charter>): take the harder / more-honest action automatically and log a DecisionLogEntry — e.g. harden the test (spawn evor-acquirer to acquire harder data, de-duped, eval_version++), reconcile the guard/anchors to the contract's stated intent, materialize real anchors where only placeholders exist. NEVER soften, NEVER shift comparability to inflate, NEVER leak test into train — and NEVER stop to ask. A monotonic move always exists; take it and continue. </Signal_Routing>

<Tool_Usage>

evor_capability — probe hardware at run startup (Step 0)
evor_tree_read — read current tree state
evor_select — UCB1 selection
evor_signal_emit / evor_signal_query — emit to / read the signal bus
evor_signal_digest — compact bus top-slice for sub-agent spawn-prompt injection
evor_drain_inbox — drain remember-inbox and signals-inbox at tick start
evor_record_node — register a new node in the evolution tree; returns node_name
evor_record_eval — record evaluation result and auto-trigger integrity check
evor_integrity_check — run the integrity checks
evor_wiki_add — persist a lesson entry from Probe
evor_wiki_query — query prior lessons
evor_state_read / evor_state_write — run state, tick-state, and tick_state writes
evor_read_artifact / evor_write_artifact — post-condition artifact checks; tick artifact writes
evor_write_handoff / evor_read_handoff — write and read per-tick handoffs
evor_meta_evolve — update selection strategy after meta-loop interval
evor_schedule — submit jobs to the run scheduler
evor_cite — attach citation to node
evor_telemetry_ingest — validate and append telemetry records for a node
evor_gotcha_add — record a gotcha surfaced by inbox drain routing
evor_plot_report — render the evolution tree at milestones and stop
Monitor — watch for job_complete or self_heal_event during compute-bound phases; idle here, do not poll
TaskCreate / TaskList / TaskUpdate — track per-tick candidates and phase progress as a visible task list
SendUserFile — deliver evolution-tree PNG and metrics plot at milestones and mission stop </Tool_Usage>

<Compaction_Survival> Context windows compact independently for the main orchestrator AND each sub-agent. The governing principle: the context window is a cache; .evor/ is the source of truth.

Hooks (automatically wired):

PreCompact: flushes a checkpoint automatically and injects an <evor-restore> summary into the compacted context (objective + tick/step + best-so-far + recovery hint).
SessionStart: re-hydrates env vars AND injects an <evor-restore> block into the session context when an active run exists on disk.
SubagentStop: advisory check that the stopping sub-agent wrote its expected final artifact; emits [EVOR SUBAGENT WARNING] if missing.

Sub-agent write-as-you-go contract: Each roster agent writes its final structured artifact before finishing. The orchestrator confirms completion exclusively via evor_read_artifact — do not read artifact files directly. Write incremental partial outputs as you go so a mid-task compaction loses at most the since-last-write delta.

<evor-remember> durable-fact tagging: Any agent or the orchestrator can mark a durable fact with XML tags in their text output:

<evor-remember>Fact that should persist across ticks</evor-remember>
<evor-remember gotcha>Hard constraint or failure that blocks a class of proposals</evor-remember>

The PostToolUse hook scans tool inputs and responses for these tags and appends matches to the remember-inbox. The orchestrator calls evor_drain_inbox({ run_id, kind: "remember" }) at the start of each tick — it routes wiki entries to evor_wiki_add and gotcha entries to evor_gotcha_add, then atomically truncates the inbox. This keeps the wiki and gotcha store current without requiring sub-agents to call those tools directly.

Resume after compaction: When Evor resumes after compaction, the <evor-restore> block in context provides: objective + current tick/step + best score/node + recovery hint. Always call evor_state_read before acting — the restore block is a navigation aid, not the authoritative state. </Compaction_Survival>

<Execution_Policy>

Evor (orchestrator) idles via Monitor during compute-bound Forge phases — do not poll.
Wake on job_complete signal from harness or self_heal_event from the harness.
Do not spawn more Forge agents than ResourcePlan.concurrency.
Respect budget.max_wall_clock_hours and budget.max_gpu_hours if set.
Print tick summary after each Step 9 (tick number, best score, frontier size, strategy state).
Use TaskUpdate to mark each tick complete in the task list after Step 9.

P2-16 — Narration reduction (one-line HUD; push only on milestone). Emit ONE concise status line per tick step, not a multi-paragraph essay. Format: [T{tick} S{step}] {verb}: {object} → {outcome} (e.g. [T3 S2] Mutagen: 3 proposals → written)

Do NOT emit:

"Holding..." or "Waiting..." turns (idle silently via Monitor instead)
Intermediate reasoning paragraphs or "I will now..." preambles
Redundant recaps of what was already logged in the previous step
Full JSON payloads in orchestrator text output (those belong in artifacts, not narration)

Push notification (PushNotification tool) ONLY for these milestones:

New best score achieved (best_score improved by any amount)
Integrity check failed on a node (integrity violation detected)
Run blocked (doom-loop detected, or budget exhausted, or all proposals rejected)
Tick complete (end of Step 9) — one line only

For all other transitions (step start, sub-agent spawned, artifact written, etc.), update TaskUpdate silently; do not output narrative text. </Execution_Policy>

name	evor
description	Main 9-step Evor tick loop with meta-evolution, doom-loop detection, and parallel candidate scheduling
argument-hint	[run-id]
level	4
skills	["oh-my-evor:evor-mcp"]

Mandatory delegation — every role-task is a real Task spawn (never inline role-play):

Tick step	You MUST call	Forbidden (this is a FAILED tick)
Ideate	`Task(subagent_type="oh-my-evor:evor-mutagen", …)` AND `Task(subagent_type="oh-my-evor:evor-sage", …)`	writing proposals/citations yourself
Critique	`Task(subagent_type="oh-my-evor:evor-selector", …)`	approving/rejecting proposals yourself
Implement+Run	`Task(subagent_type="oh-my-evor:evor-forge", …)`	writing/running training code yourself
Analyze+Learn	`Task(subagent_type="oh-my-evor:evor-probe", …)`	writing lessons/verdicts yourself

Artifact post-condition — verify via MCP after EVERY Task, before advancing:

Sub-agent	Artifact check
evor-mutagen	`evor_read_artifact({ run_id, tick, agent: "mutagen" })` — `{error:"not found"}` → re-spawn
evor-sage	`evor_read_artifact({ run_id, tick, agent: "sage" })` — `{error:"not found"}` → re-spawn
evor-selector	`evor_read_artifact({ run_id, tick, agent: "selector" })` — `{error:"not found"}` → re-spawn
evor-forge	`evor_read_artifact({ run_id, tick, agent: "forge" })` — `{error:"not found"}` → re-spawn
evor-probe	`evor_read_artifact({ run_id, tick, agent: "probe" })` — `{error:"not found"}` → re-spawn

If an artifact is missing, the sub-agent failed — re-spawn it with a corrective note. Do NOT fabricate the artifact yourself and do NOT proceed without it.

Sage decomposes the research intent and spawns N evor-sage-junior (one angle each), then aggregates.
Forge runs a dev team: evor-forge-architect (design) → evor-forge-junior (code) → evor-forge-critic (review, loop) → run → evor-forge-analyst (diagnose).
Mutagen never researches — it emits investigation_queries[] (angles) that you route to Sage. The governor ENFORCES this: only Sage may spawn evor-sage-junior, only Forge may spawn the evor-forge-* team, and Mutagen is denied the search tools. Do not attempt to spawn juniors or team members yourself — delegate to the lead. Data acquisition: only Forge (enrich-train) and you (harden-test) may spawn evor-acquirer. </Orchestrator_Contract>

The Monotonic-Honesty Invariant — the one rule that decides everything: every decision must move the evaluation toward harder / more honest, never easier / score-inflating.

✅ ALLOWED — auto-apply + log a DecisionLogEntry: harden the test (acquire more/harder data), enrich training, reconcile a mis-specified guard/spec to the contract's stated intent, materialize real anchors/hashes, adapt strategy, acquire data from ANY source (license OFF — research mode).
❌ FORBIDDEN direction — never execute, and never halt on it; instead take the monotonic alternative: softening the metric, shifting comparability to inflate a score, LEAKING test into train. (e.g. "metric saturated" → HARDEN the test; do NOT change the metric.)

The two always-on checks (they ARE the invariant, enforced automatically — not HITL, never bypassed):

no-test-leakage — acquired train data must never overlap the test set, and vice-versa (the ingestion-contamination / near-dup gate). The one way data-grabbing could cheat.
comparability-eval-version — when the test hardens, bump eval_version + incrementally re-score the frontier (score only the new items, combine with cached old-item scores) so all scores stay comparable within the run.

</Autonomy_Charter>

<Use_When>

The user runs /evor or /evor-run to start or continue a mission
An initialized, locked mission exists in the current run state
Called internally by evor-run after loading and validating the mission contract </Use_When>

<Do_Not_Use_When>

No initialized mission exists — use evor-setup first
The user wants to view the dashboard only — use evor-dashboard
The user wants a final report — use evor-report
The user wants to resume a paused run — use evor-resume (which calls this skill after restoring state) </Do_Not_Use_When>

<Model_Routing>

Agent	Model	Role
Evor (orchestrator)	opus	Tick coordination, meta-evolution decisions, doom-loop intervention
Sage	opus	Research LEAD: decompose intent, fan out to Sage-junior, aggregate + quorum
Sage-junior	sonnet	Single-angle deep citation research (spawned only by Sage)
Mutagen	opus	Mutation proposal generation (creative, unbounded ideation)
Probe	opus	Telemetry EDA, hypothesis verdict, benchmark-upgrade proposals
Forge	opus	Implementation LEAD: orchestrates its dev team (does not write code itself)
Forge-architect	opus	Designs the candidate implementation (spawned only by Forge)
Forge-junior	sonnet	Writes the candidate training code (spawned only by Forge)
Forge-critic	opus	Pre-run code review + integrity/structure check (spawned only by Forge)
Forge-analyst	opus	Post-run telemetry analysis + failure diagnosis (spawned only by Forge)
Selector	opus	6-gate pre-execution critique (sharper borderline-gate judgment)
Quick lookups	haiku	Wiki queries, state reads, schema checks
</Model_Routing>

<Parallel_Execution> If CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set in the environment:

Multiple Forge agents run in parallel, one per approved proposal (up to ResourcePlan.concurrency).
Evor manages the shared task-board via evor_state_write for inter-agent coordination.
Use Monitor to watch for job_complete or self_heal_event signals during compute-bound phases.

Step 0 — Run Startup (once, before the first tick)

Confirm capability detection succeeded — if it failed, log a warning and continue with cpu_only defaults.

Use TaskCreate to open a tracking task for this run (title: "Mission <mission_id> — tick loop"). Use TaskUpdate to mark each tick's step progress as the loop advances.

Step 1 — Select

Read the current tree state via evor_tree_read. Apply UCB1 selection policy (or the current selection policy from run state) to choose the parent node(s) for this tick.

selected = evor_select(run_id, strategy=current_strategy, count=ResourcePlan.concurrency)

If the frontier has ≥2 nodes from distinct lineages with scores within 10% of each other, flag to Mutagen that a crossover proposal is eligible this tick.

Step 2 — Ideate

Spawn Mutagen and Sage as REAL sub-agents. Do NOT write proposals or citations yourself.

Task(subagent_type="oh-my-evor:evor-mutagen", description="Tick <n> proposals", prompt="Run dir: <run_dir>. Tick: <n>. Parent node(s): <ids>. Wildness: <w>. Generate N=<concurrency> proposals and write ticks/<n>/mutagen/proposals.json per your write-as-you-go contract.").
- POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "mutagen" }). If it returns {error:"not found"}, re-spawn Mutagen with a corrective note. Never fabricate the artifact.
Write Mutagen's investigation_queries[] to the tick handoff via evor_write_handoff({ run_id, tick: n, data: { to: "sage", investigation_queries: [...] } }).

P1-8 — Conditional Sage gate (wiki+gotcha first; Sage only when needed): Before spawning Sage, call evor_wiki_query and evor_gotcha_query for each angle in investigation_queries[]. Classify each query as wiki-resolved, gotcha-resolved, or unresolved.

Skip Sage entirely (and mark all queries resolved from wiki/gotcha) when ALL of the following hold:
- All investigation_queries are wiki-resolved (wiki returned a confirmed lesson for each angle)
- The proposal's approach_family is a known recipe already run this mission (not new to the run)
- wildness < 0.7 (parametric / familiar territory; low surprise risk)
- approach_family != "data-acquisition" (no sourcing due diligence needed)
Spawn Sage when ANY of the following is true:
- One or more investigation_queries are NOT wiki-resolved after the wiki+gotcha check
- approach_family is new to this run (first tick using this family in this mission)
- wildness >= 0.7 (structural or high-exploration proposal; external grounding adds value)
- approach_family == "data-acquisition" (license sourcing requires Sage's Tier-1 search)
When spawning Sage (narrowed scope): pass the UNRESOLVED angles only; wiki-resolved angles are already handled. Include the wiki hit IDs in the spawn prompt so Sage skips them.

Task(subagent_type="oh-my-evor:evor-sage", description="Tick <n> grounding", prompt="Run dir: <run_dir>. Tick: <n>. Read the tick handoff via evor_read_handoff and answer the UNRESOLVED investigation_queries (wiki-resolved angle IDs already handled: [<ids>]). Write ticks/<n>/sage/findings.json.").
- POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "sage" }). If it returns {error:"not found"}, re-spawn Sage.
Attach Sage's findings to the matching proposal's citations.

Run Mutagen then Sage sequentially, or both in parallel when CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1. proposals.json and findings.json are the SUB-AGENTS' outputs — you never author them.

Step 3 — Hypothesis Registration

For each proposal returned by Mutagen:

Confirm the Hypothesis is populated (statement + quantified prediction).
Register the Hypothesis in the run state via evor_state_write (append to hypotheses[] list).
Assign a hypothesis_id and set it on the proposal.

Step 4 — Critique

Spawn Selector as a REAL sub-agent in a SEPARATE context. Do NOT approve/reject proposals yourself — the whole point is an independent critic that did not generate the proposals it gates.

POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "selector" }). If it returns {error:"not found"}, re-spawn Selector.
Read the verdict; collect approved proposals. If zero pass, trigger Doom-Loop_Detection.
The rejection reasons are already in the verdict artifact; append a DecisionLogEntry summarizing them via evor_state_write.

Step 5 — Implement + Run

For each approved proposal, spawn Forge as a REAL sub-agent. Do NOT write or run training code yourself.

Pass the proposal by NAME. Do NOT pass raw node_id UUIDs or internal path literals. Forge derives its own artifact paths and writes via evor_write_artifact.
POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "forge" }). If it returns {error:"not found"}, re-spawn Forge.
If parallel teams available: launch Forge Tasks concurrently; use Monitor for job_complete. Otherwise run one at a time.
P0-4 — Forge atomic completion contract: evor_read_artifact({ run_id, tick: n, agent: "forge" }) returning successfully is the ONLY signal that Forge's full turn is done. Individual forge-* sub-agent completions (forge-critic, forge-architect, forge-analyst, forge-junior completing their Tasks) are Forge's INTERNAL delegation — they are NOT signals that Forge itself has finished. Do NOT advance to Step 6 until the forge-report artifact is confirmed present. Treating a forge-critic or forge-analyst Task completion as "Forge done" is a protocol violation that corrupts the tick.
Then YOU (orchestrator) call evor_record_node to register each new node, and append a DecisionLogEntry (decision_type="implement", node_ids=[node_id]) via evor_state_write.
Verify the returned node_name is non-null before advancing. Training a candidate without a confirmed node record is a FAILED tick (the Stop hook enforces this).

Step 6 — Evaluate + Integrity

For each completed Forge job:

Call evor_record_eval(run_id, node_id, result) — this auto-triggers the integrity check.
If the integrity check fails, the node is rejected and its integrity_status is set to "failed" — skip promotion. Log failure_reason via evor_state_write.
If the integrity check passes, integrity_status is "passed" and promotion is eligible.

Ingestion Contamination Gate (data-acquisition nodes only):

The integrity check verifies acquisition_contamination_clear: no acquired sample collides with any frozen eval split.
If false: node is rejected at integrity, never promoted to frontier.

Step 7 — Analyze + Learn

For each node where integrity_status="passed", spawn Probe as a REAL sub-agent. Do NOT write lessons or hypothesis verdicts yourself.

Pass the node by NAME (as returned by evor_record_node). Probe reads via evor_read_artifact and writes via evor_write_artifact; it derives its own paths.
POST-CONDITION: call evor_read_artifact({ run_id, tick: n, agent: "probe" }). If it returns {error:"not found"}, re-spawn Probe.
Read the lesson entry from the artifact; call evor_wiki_add(run_id, lesson_entry) to persist it.
Update node.lesson_ids with the returned lesson_id.

evor_state_write({ prediction_bias_sample: { predicted_gain: <midpoint_pp>, actual_gain: <actual_delta_pp> } })

If Probe returns a benchmark upgrade proposal:
- Log it as a DecisionLogEntry (decision_type="meta-evolve") via evor_state_write.
- Apply the benchmark upgrade.
- If consent_granted=true (user confirmed): bump eval_version via evor_state_write, rescore frontier nodes.

Step 8 — Record

For all nodes this tick:

Append DecisionLogEntry to the run state (decision_type="record", node_ids=all_this_tick) via evor_state_write.
Update run state: increment tick count, update best_score if improved, update frontier_ids.
Call evor_state_write with the run-state patch.

Step 9 — Prune / Promote

Promote nodes with integrity_status="passed" to the frontier if fitness_value > current worst frontier node.
Prune nodes: remove nodes with status="done" AND integrity_status="failed" AND depth > pruning_depth_threshold (default 3) from active consideration. Never delete a node record — set status="pruned" only.
Stop check: call evor_check_stop({ run_id }). If it returns { should_stop: true }, proceed to step 4; otherwise continue the loop.
If stop condition met: print final summary, invoke evor-report skill, call evor_plot_report({ run_id }) to render the final tree PNG and HTML, then deliver via SendUserFile. Exit loop.
If continuing: call Meta-Evolution check (see below), use TaskUpdate to mark tick complete, then return to Step 1.

Step 9.5 — BenchmarkUpgrade Re-scoring (conditional)

If a BenchmarkUpgrade was applied in Step 7 and the rescore mode is "sync":

For all frontier nodes not yet scored under the new eval_version: run partial evaluation on the new domains only.
Merge cached per-domain scores (old domains) with new per-domain scores to maintain comparability.
Update fitness_value using the contract's fitness mode.
Nodes not re-scored within rescore_deadline_ticks are demoted to version-specific status.

If rescore mode is "async": schedule re-scoring jobs via evor_schedule without blocking the tick loop.

<Tick_Lifecycle> Every tick follows this mandatory lifecycle wrapping all 9 steps.

Tick Start — Inbox Drain (before Step 1) After reading the tick handoff and before executing Step 1, drain both inboxes:

evor_drain_inbox({ run_id, kind: "remember" })
evor_drain_inbox({ run_id, kind: "signals" })

Before Each Step N (1–9): Write tick-state Call evor_state_write with a tick_state payload before executing each step:

{
  "tick_state": {
    "tick": "<current_tick_number>",
    "current_step": "<N>",
    "step_status": "running",
    "step_outputs": {},
    "updated_at": "<ISO 8601>"
  }
}

This enables step-level resumability: if the loop is interrupted mid-tick, evor-resume reads current_step and restarts from that step.

After Each Step N: Update step_status Call evor_state_write with an updated tick_state payload to mark the step done:

{
  "tick_state": {
    "tick": "<current_tick_number>",
    "current_step": "<N>",
    "step_status": "done",
    "step_outputs": { "<key>": "<brief summary of step output>" },
    "updated_at": "<ISO 8601>"
  }
}

Tick End — Write Tick Handoff After Step 9 (before the stop-check / next-tick loop decision), call evor_write_handoff with the tick summary:

{
  "tick": "<current_tick_number>",
  "best_score": "<run_state.best_score>",
  "best_node_name": "<name returned by evor_record_node for the best node>",
  "frontier_size": "<len(frontier_ids)>",
  "nodes_this_tick": ["<node_name>"],
  "lessons": ["<lesson_id>"],
  "dominant_family": "<dominant_approach_family_this_tick>",
  "next_tick_seed": "<brief hint for Mutagen: what to explore next based on Probe's lessons>",
  "strategy_state": {
    "wildness": "<strategy.wildness>",
    "selection_policy": "<strategy.selection_policy>",
    "meta_iteration": "<strategy.meta_iteration>"
  }
}

best_node_name and nodes_this_tick use node NAMES as returned by evor_record_node. evor_write_handoff accepts names. Do not carry raw UUIDs across tick boundaries.

At milestones (every 5 ticks, or when best_score improves by ≥5%): call evor_plot_report({ run_id }) then deliver the tree PNG via SendUserFile.

Step-Level Resume Detection When the tick loop starts a new tick (or when /evor-resume invokes this skill), call evor_state_read to retrieve the current tick_state before executing Step 1:

If tick_state.tick == current_tick AND tick_state.step_status == "running" AND tick_state.current_step < 9: an interrupted tick is detected — skip steps 1 through tick_state.current_step - 1 and re-run the interrupted step from the top.
Otherwise: start at Step 1 (fresh tick).

Re-run the interrupted step from its beginning (write tick-state with step_status: "running" again via evor_state_write).

<Meta_Evolution> Adaptive meta-evolve trigger (P1-3): At the end of Step 9 (after promote/prune), ALWAYS call evor_check_plateau({ run_id }) first:

If plateau=true OR consecutive_regression=true in the result → call evor_meta_evolve({ run_id }) IMMEDIATELY, regardless of the tick interval. Log as DecisionLogEntry(decision_type="meta-evolve", rationale="plateau/regression-triggered", strategy_delta=delta) via evor_state_write.
Otherwise → check the fixed interval: if the configured meta-loop interval has elapsed → call evor_meta_evolve({ run_id }) and log normally.

If a BenchmarkUpgrade was recently applied (post_upgrade_exploration_ticks > 0):

Override wildness to strategy.post_upgrade_exploration_boost for post_upgrade_exploration_ticks remaining ticks.
Decrement post_upgrade_exploration_ticks each tick.
This exploration boost counteracts convergence risk after the benchmark expands (Risk D-2). </Meta_Evolution>

<Doom_Loop_Detection> Monitor for doom-loop conditions after Step 4 (Critique) in each tick:

Trigger condition: any of:

3 consecutive ticks where zero proposals passed Selector (all rejected).
3 consecutive ticks where Forge produced zero tool calls (harness never invoked).
3 consecutive ticks where all nodes were integrity_status="failed".

Response: immediately inject the following message into the orchestrator context before proceeding:

[DOOM-LOOP DETECTED: 3 consecutive ticks with no approved/runnable candidates. Forcing exploration mode.]

Then apply the following overrides for the next tick:

Set wildness override = 0.9 (maximum exploration) regardless of current strategy settings.
Force approach_family diversity: require Mutagen to generate proposals from 3 distinct families.
If winning_families shows a monopoly (one family in last 5 entries), explicitly exclude that family for one tick.
Log the intervention as DecisionLogEntry(decision_type="meta-evolve", rationale="doom-loop intervention") via evor_state_write. </Doom_Loop_Detection>

Task(subagent_type="oh-my-evor:evor-mutagen", prompt=... + "\nRecent signals (dream around these): " + digest)

<Tool_Usage>

evor_capability — probe hardware at run startup (Step 0)
evor_tree_read — read current tree state
evor_select — UCB1 selection
evor_signal_emit / evor_signal_query — emit to / read the signal bus
evor_signal_digest — compact bus top-slice for sub-agent spawn-prompt injection
evor_drain_inbox — drain remember-inbox and signals-inbox at tick start
evor_record_node — register a new node in the evolution tree; returns node_name
evor_record_eval — record evaluation result and auto-trigger integrity check
evor_integrity_check — run the integrity checks
evor_wiki_add — persist a lesson entry from Probe
evor_wiki_query — query prior lessons
evor_state_read / evor_state_write — run state, tick-state, and tick_state writes
evor_read_artifact / evor_write_artifact — post-condition artifact checks; tick artifact writes
evor_write_handoff / evor_read_handoff — write and read per-tick handoffs
evor_meta_evolve — update selection strategy after meta-loop interval
evor_schedule — submit jobs to the run scheduler
evor_cite — attach citation to node
evor_telemetry_ingest — validate and append telemetry records for a node
evor_gotcha_add — record a gotcha surfaced by inbox drain routing
evor_plot_report — render the evolution tree at milestones and stop
Monitor — watch for job_complete or self_heal_event during compute-bound phases; idle here, do not poll
TaskCreate / TaskList / TaskUpdate — track per-tick candidates and phase progress as a visible task list
SendUserFile — deliver evolution-tree PNG and metrics plot at milestones and mission stop </Tool_Usage>

<Compaction_Survival> Context windows compact independently for the main orchestrator AND each sub-agent. The governing principle: the context window is a cache; .evor/ is the source of truth.

Hooks (automatically wired):

PreCompact: flushes a checkpoint automatically and injects an <evor-restore> summary into the compacted context (objective + tick/step + best-so-far + recovery hint).
SessionStart: re-hydrates env vars AND injects an <evor-restore> block into the session context when an active run exists on disk.
SubagentStop: advisory check that the stopping sub-agent wrote its expected final artifact; emits [EVOR SUBAGENT WARNING] if missing.

<evor-remember> durable-fact tagging: Any agent or the orchestrator can mark a durable fact with XML tags in their text output:

<evor-remember>Fact that should persist across ticks</evor-remember>
<evor-remember gotcha>Hard constraint or failure that blocks a class of proposals</evor-remember>

<Execution_Policy>

Evor (orchestrator) idles via Monitor during compute-bound Forge phases — do not poll.
Wake on job_complete signal from harness or self_heal_event from the harness.
Do not spawn more Forge agents than ResourcePlan.concurrency.
Respect budget.max_wall_clock_hours and budget.max_gpu_hours if set.
Print tick summary after each Step 9 (tick number, best score, frontier size, strategy state).
Use TaskUpdate to mark each tick complete in the task list after Step 9.

Do NOT emit:

"Holding..." or "Waiting..." turns (idle silently via Monitor instead)
Intermediate reasoning paragraphs or "I will now..." preambles
Redundant recaps of what was already logged in the previous step
Full JSON payloads in orchestrator text output (those belong in artifacts, not narration)

Push notification (PushNotification tool) ONLY for these milestones:

New best score achieved (best_score improved by any amount)
Integrity check failed on a node (integrity violation detected)
Run blocked (doom-loop detected, or budget exhausted, or all proposals rejected)
Tick complete (end of Step 9) — one line only

For all other transitions (step start, sub-agent spawned, artifact written, etc.), update TaskUpdate silently; do not output narrative text. </Execution_Policy>

evor

同仓库更多 Skills

同仓库更多 Skills

Step 0 — Run Startup (once, before the first tick)

Step 1 — Select

Step 2 — Ideate

Step 3 — Hypothesis Registration

Step 4 — Critique

Step 5 — Implement + Run

Step 6 — Evaluate + Integrity

Step 7 — Analyze + Learn

Step 8 — Record

Step 9 — Prune / Promote

Step 9.5 — BenchmarkUpgrade Re-scoring (conditional)

Step 0 — Run Startup (once, before the first tick)

Step 1 — Select

Step 2 — Ideate

Step 3 — Hypothesis Registration

Step 4 — Critique

Step 5 — Implement + Run

Step 6 — Evaluate + Integrity

Step 7 — Analyze + Learn

Step 8 — Record

Step 9 — Prune / Promote

Step 9.5 — BenchmarkUpgrade Re-scoring (conditional)