improve-bot-evolve

name	improve-bot-evolve
description	Autonomous generation-phase improvement loop. Generates a pool of Claude-proposed improvements, fitness-tests each vs the current parent, stacks the winners onto a new snapshot (with an import-check gate), and regression-checks against the prior parent — repeating for hours until the pool or wall-clock budget is exhausted. Designed for overnight unattended runs.

/improve-bot-evolve

Autonomous generation-phase improvement loop. Every generation:

1. Fitness — each active pool imp is individually snapshotted, applied, and plays the current parent for --games-per-eval games. Strict-majority wins (≥3/5) become fitness-pass; one-short (2/5) become fitness-close (resurrection-eligible, retry cap 2); anything lower evicts immediately.
2. Stack-apply + promote — if ≥1 fitness-pass imp exists, snapshot the parent into a fresh vN+1 directory, apply every fitness-pass imp in rank order, run python -c "import bots.vN+1.bot" as a pre-regression gate, and commit the promotion as one [evo-auto] commit. Import-check failures roll back the new directory and skip regression for the generation.
3. Regression — if anything was promoted, new parent plays prior parent for --games-per-eval games. On rollback, git revert the promote commit (also under EVO_AUTO=1) and restore the pointer.
4. Pool refresh — close-loss and benched-pass imps go back to active (retry cap enforced; cap=3 total evals before eviction). Claude tops up the active pool back to --pool-size with fresh orthogonal imps targeting the new parent.

Gate-reduction note (2026-04-23): The legacy third gate — a 5-game composition batch testing the stacked candidate against the parent before promotion — was removed per evolve-gate-reduction-plan.md. Regression already catches bad-interaction stacks as "new parent loses to prior parent", and the extra Bernoulli filter dominated promotion rate without adding unique detection capability. The import-check gate that used to live inside composition migrated into the stack-apply step.

Design goal: /improve-bot-evolve in a fresh context window with no additional input should produce a measurably stronger parent version after a few hours, with every promotion recorded as an [evo-auto] commit and every regression recorded as an [evo-auto] revert.

Zero-input contract: When invoked with no flags, this skill MUST NOT ask the user any questions. It proceeds immediately with safe defaults (pool size 10, 5 games per eval, 4-hour budget, Simple64). Every phase is designed to resolve ambiguity autonomously — pick reasonable defaults, log the choice, and keep going. The only exception is if a hard pre-flight failure makes the run impossible (e.g., SC2 not installed, claude CLI missing or unauthenticated).

Relationship to /improve-bot-advised: These two skills are siblings with different inner mechanics:

• /improve-bot-advised picks one improvement, applies it, validates win-rate, commits — linear.
• /improve-bot-evolve generates a pool of 10, fitness-tests each vs parent, stacks winners onto a new snapshot with an import-check gate — parallel with a regression safety net.

The outer phase shape (pre-flight → seed → loop → decision → report) is identical. The two skills must NEVER run concurrently (they both mutate bots/current/current.txt). The pre-flight explicitly refuses to start if an advised run is in progress.

---

Flags

Flag	Type	Default	Purpose
--pool-size	int	10	Number of improvements Claude generates (and tops up to between generations)
--games-per-eval	int	5	Games in each phase evaluation (fitness / regression). Pass threshold = strict majority of this count.
--hours	float	4.0	Wall-clock budget. 0 disables the check (test-only).
--concurrency	int	1	Number of fitness-eval workers run in parallel by scripts/evolve.py. 1 is byte-identical to the historical serial path (Decision D-1 in documentation/plans/evolve-parallelization-plan.md). >1 fans the fitness phase out across N worker subprocesses; stack-apply + regression remain serial.
--lineages	int	1	Number of parallel lineages to round-robin across. 1 with no data/lineages.json is byte-identical to the historical single-lineage path. >1 (or a non-empty data/lineages.json) flips bots/current/current.txt to each lineage's head before its generation, so the loop interleaves divergent branches (Phase EL). A bare /improve-bot-evolve invocation stays single-lineage.
--map	str	Simple64	SC2 map name
--game-time-limit	int	1800	SC2 in-game time limit per game, in seconds
--hard-timeout	float	2700.0	Wall-clock timeout per game, in seconds
--no-commit	flag	off	Skip the EVO_AUTO commit on promote. Dev/test only.
--results-path	path	data/evolve_results.jsonl	JSONL log of every phase outcome
--pool-path	path	data/evolve_pool.json	Pool state file (dashboard reads this)
--state-path	path	data/evolve_run_state.json	Run state file (dashboard reads this)
--current-round-path	path	data/evolve_current_round.json	Live per-game progress file
--crash-log-path	path	data/evolve_crashes.jsonl	Full-traceback crash log
--run-log	path	auto	Human-readable markdown run log
--resume	flag	off	Reload pool + per-item statuses from --pool-path instead of generating fresh.
--post-training-cycles	int	0	On promoted runs, start the training daemon for exactly N cycles after the loop exits.

Budget math: pool=10, games-per-eval=5 → ~55 games per generation (50 fitness + 5 regression; stack-apply runs no SC2 games); with 4-hour budget and ~3-min games, roughly 1 generation per hour — ~15 min faster than the pre-2026-04-23 3-gate pipeline.

---

Phase 0: Bootstrap

0.0 Run-start banner

Print this banner at the start of every run (before any other output):

🔒 Sandbox active (EVO_AUTO scope)
  I can edit:   bots/** (any version dir, including new ones from snapshot_current)
  I cannot edit: src/orchestrator/, pyproject.toml, tests/, frontend/, scripts/
  Commit marker: [evo-auto] on its own line in the commit message body
  Env: EVO_AUTO=1 must be set in the commit subprocess env (scripts/evolve.py handles this)
  SC2 required for mirror seed, fitness batches, regression gate

The banner differs from the advised banner in three ways:

• Scope is bots/** (any version), not bots/current/** (a single version).
• Commit marker is [evo-auto], not [advised-auto].
• Env var is EVO_AUTO=1, not ADVISED_AUTO=1.

Both env vars must NOT be set simultaneously — the sandbox hook fails loudly on that conflict. scripts/evolve.py unsets ADVISED_AUTO defensively in its commit subprocess env.

0.1 Parse flags

Parse all flags. Never ask the user, always resolve automatically. Log any overrides to $LOGFILE.

0.2 Pre-flight checks

All pre-flight checks resolve autonomously. Only stop if the situation is truly unrecoverable.

# Git state
git status --porcelain
git rev-parse --abbrev-ref HEAD
git fetch origin && git status -sb

# SC2
ls "C:/Program Files (x86)/StarCraft II/Versions/"

# Claude CLI on PATH + authenticated
claude --version && claude -p "ping" --model haiku --output-format text --no-session-persistence | head -1

# Tools
uv run pytest --co -q 2>&1 | tail -1
uv run ruff check . --quiet
uv run mypy src --quiet

# Concurrent-run interlock — refuse if an advised run is active
python -c "
import json, sys
from pathlib import Path
p = Path('data/advised_run_state.json')
if not p.exists():
    sys.exit(0)
state = json.loads(p.read_text())
if state.get('status') == 'running':
    print(f'Advised run {state.get(\"run_id\")} is active; evolve will not start.')
    sys.exit(1)
"

Autonomous resolution for common issues:

• Git dirty (untracked files only): git stash --include-untracked -m "evolve-preflight-$RUN_TS". Log. Proceed.
• Git dirty (staged/modified tracked files): Commit them with "chore: auto-stash before evolve run $RUN_TS". Log SHA. Proceed.
• Not on master: git checkout master. Stash first if needed. Log.
• Behind origin/master: git pull --rebase origin master. STOP on conflicts.
• Quality gates fail: Log but proceed — pre-existing failures are the baseline.
• SC2 not found: STOP.
• claude CLI missing/unauthenticated: STOP.
• Advised run active: STOP.
• Stale evolve run (state file running but no process): if older than 12 hours, rewrite status to stopped; otherwise abort.

0.3 Record baseline

LOOP_START=$(date +%s)
RUN_TS=$(date -d @$LOOP_START +%Y%m%d-%H%M)

LOGFILE="documentation/soak-test-runs/evolve-$(date +%F).md"
i=0; while [ -e "$LOGFILE" ]; do i=$((i+1)); suf=$(printf "\\x$(printf '%x' $((96+i)))"); LOGFILE="documentation/soak-test-runs/evolve-$(date +%F)-$suf.md"; done

Capture baseline: current parent, recent win rate, Elo, git SHA. Write run header to $LOGFILE.

0.4 Start systems

Backend lifecycle: Start exactly ONE --serve process. It stays alive for the entire run so the Evolution dashboard tab can monitor. Never start a second --serve process.

export PYTHONUNBUFFERED=1

python -c "import socket; s=socket.socket(); r=s.connect_ex(('127.0.0.1',8765)); s.close(); exit(0 if r!=0 else 1)" && {
  DEBUG_ENDPOINTS=1 PYTHONUNBUFFERED=1 uv run python -m bots.v0.runner --serve 2>&1 &
  BACKEND_PID=$!
  echo "Backend started (PID $BACKEND_PID)"
} || echo "Backend already running on port 8765, skipping"

The evolve loop does NOT use --daemon; scripts/evolve.py drives games directly.

0.5 Seed game (sanity check)

Run 1 mirror game (parent-vs-parent) to verify the full subprocess self-play pipeline works before entering the expensive pool generation.

uv run python scripts/selfplay.py --p1 "$(cat bots/current/current.txt)" --p2 "$(cat bots/current/current.txt)" --games 1 --map "$MAP" 2>&1 | tee -a "$LOGFILE"

If this returns non-zero or no SelfPlayRecord, STOP.

0.6 Dashboard check

Run /a4g-dashboard-check. The Evolution tab should show "idle". Stop and fix any ✗ tabs.

0.7 Baseline tag

git tag "evolve/run/$RUN_TS/baseline"
git push origin "evolve/run/$RUN_TS/baseline"

This tag is the restore point for a full revert of the run. scripts/evolve.py handles the initial run-state write via write_run_state(); the operator does not write it manually.

---

Phase 1: Seed + Pool

1.1 Invoke the evolve runner

The entire generation loop (pool gen + fitness + stack-apply + regression + refresh) is owned by scripts/evolve.py. The skill's job is to invoke with the right flags, monitor state files, and handle exit.

uv run python scripts/evolve.py \
    --pool-size 10 \
    --games-per-eval 5 \
    --hours 4 \
    --concurrency "$CONCURRENCY" \
    --map Simple64 \
    2>&1 | tee -a "$LOGFILE"

$CONCURRENCY defaults to 1 and is set from the skill's --concurrency flag. Operators wanting a parallel run pass it explicitly: e.g. /improve-bot-evolve --concurrency 4 produces the 4-worker fan-out. At N=1 the serial path runs unchanged.

Internally:

1. Runs 3 parent-vs-parent mirror games via orchestrator.selfplay.run_batch.
2. Calls orchestrator.evolve.generate_pool(parent, pool_size=10, ...) which prompts Claude (Opus by default) with the mirror summary, source tree, and guiding principles. Claude returns 10 orthogonal dev Improvement records.
3. If the initial response has file overlaps (two imps touching the same file), re-prompts once with a conflict list. A second-round overlap is accepted — the stack-apply step surfaces merge failures empirically at the import-check gate.
4. Writes data/evolve_pool.json with all 10 items marked status: "active".

If pool generation fails (malformed JSON, rate limit, missing API key), the script writes status: "failed" to data/evolve_run_state.json and exits 1. See Troubleshooting.

1.2 Pool-state file schema

{
  "generated_at": "2026-04-21T21:33:00+00:00",
  "parent": "v5",
  "generation": 0,
  "pool": [
    {
      "rank": 1,
      "title": "Chrono boost auto-cast",
      "type": "dev",
      "description": "...",
      "principle_ids": ["4"],
      "expected_impact": "high",
      "concrete_change": "Add chrono_boost_manager.py ...",
      "files_touched": ["bots/v5/chrono_boost_manager.py", "bots/v5/bot.py"],
      "status": "active",
      "fitness_score": null,
      "retry_count": 0,
      "first_evaluated_against": null,
      "last_evaluated_against": null
    }
  ]
}

Per-item status vocabulary (managed by scripts/evolve.py):

Status	Meaning
active	awaiting fitness eval this generation
fitness-pass	beat parent ≥ majority this gen; included in the stack-apply set
fitness-close	one win short of majority; resurrection-eligible (cap=3 total evals)
evicted	permanent. Either 0/1 wins on fitness, hit the retry cap, or crashed during a phase.
promoted	part of the winning set that passed stack-apply AND regression
regression-rollback	promoted but regression check reverted the commit

Transitions outside active are visible in the dashboard Pool view. At the end of each generation, fitness-pass and fitness-close imps whose retry_count is below the cap flip back to active for the next generation.

---

Phase 2: Generation loop

Each iteration = one generation. scripts/evolve.py runs internally; the skill reads state files.

2a. Fitness phase

For every imp with status == "active":

1. snapshot_current() → scratch cand_* dir.
2. apply_improvement(cand, imp, dev_apply_fn=spawn_dev_subagent).
3. run_batch(cand, parent, games_per_eval, map) — individual-vs-parent.
4. Classify wins: >= games // 2 + 1 = pass; one short = close; else fail.
5. rmtree scratch dir. Pointer restored to parent.
6. Append a phase: "fitness" row to evolve_results.jsonl. Update pool state.

2b. Stack-apply + promote

If ≥1 fitness-pass imp exists:

1. snapshot_current() → fresh vN+1 directory (auto-incremented from the highest existing vN). snapshot_current also flips bots/current/current.txt to the new version as a side effect.
2. Apply ALL fitness-pass imps to bots/vN+1/, in rank order.
3. Import-check gate: python -c "import bots.vN+1.bot" under a 30-second timeout. On failure: rmtree bots/vN+1/, restore the pointer to the parent, and skip regression for the generation — all winners stay fitness-close for next generation.
4. On pass: rewrite manifest.parent to the real parent, then commit [evo-auto] with the stacked titles.
5. promote_sha is captured for the regression rollback's git revert call.

Option B rationale (2026-04-23 gate reduction): every fitness-pass imp is stacked unconditionally — there is no empirical pre-regression composition filter. Bad-interaction stacks are caught by regression as "new parent loses to prior parent". The import-check gate only catches the cheap failure mode where two imps' edits, each passing ruff + mypy individually, produce a module that fails to import when combined.

2c. Regression phase

If stack-apply promoted anything:

1. run_batch(new_parent, prior_parent, games_per_eval, map) — no snapshots.
2. Majority new-parent win: accept the promotion, log regression-pass.
3. Else: git revert --no-commit <promote_sha>, commit with [evo-auto], flip promoted imps to regression-rollback, restore pointer to prior_parent.

2d. Pool refresh

1. For each fitness-pass or fitness-close imp with retry_count < 3: flip to active.
2. For each at the cap: flip to evicted.
3. If count(active) < pool_size: call generate_pool(parent_current, pool_size=delta, skip_mirror=True) and append the new imps.

2.4 Commit format

Stack promotion. Subject MUST be exactly evolve: generation N promoted stack (M imps) where N is the 1-based generation index and M is the count of stacked fitness-pass imps; the body MUST list one - <imp title> bullet per stacked imp, then a blank line, then [evo-auto]. Emit this commit for EVERY promoted generation (e.g. scenario gen 1 → evolve: generation 1 promoted stack (3 imps), gen 4 → evolve: generation 4 promoted stack (4 imps)):

evolve: generation 3 promoted stack (3 imps)

- Chrono boost auto-cast
- Forward pylon warp-in
- Archon morph on 4 HTs

[evo-auto]

Regression rollback:

evolve: generation 3 regression rollback

Reverts abc123def456. regression rollback: new v7 1-4 prior v6 (needed 3); pointer reset

[evo-auto]

The [evo-auto] marker MUST appear on its own line in the commit body. The sandbox hook reads the env var (EVO_AUTO=1), not the marker, but the marker is the human-readable audit trail.

---

Phase 3: Loop decision (stop conditions)

The loop exits when ANY of:

1. Wall-clock budget exceeded — elapsed_seconds >= hours * 3600. Disabled when --hours 0.
2. Pool exhausted — fewer than 1 item with status: "active" remains AND pool refresh also produced none.
3. Dashboard stop request — control-file flag (not yet enforced mid-generation; future enhancement).

stop_reason in the final run log: "wall-clock", "pool-exhausted", or "dashboard-stop".

---

Phase 4: Morning Report

Write the final report to $LOGFILE and print to stdout. The block below is a fully-rendered example, not a template — every <...> token (RUN_TS, sha, ISO timestamps, imp titles) MUST be substituted with the run's actual values before printing. The emitted report must contain no literal <...> placeholders ANYWHERE — including inside any commit bodies quoted into the report (substitute every <imp title> with the real imp name and every <promote_sha> / <sha> with the real short SHA): only a # Evolve run — <concrete RUN_TS> heading, the header field block, and one filled-in Generations table.

# Evolve run — 20260421-2133

- Parent (start): v5
- Parent (end):   v9
- Wall-clock budget: 4.0h
- Started:  2026-04-21T21:33:00+00:00
- Finished: 2026-04-22T01:12:04+00:00
- Generations completed: 4
- Generations promoted:  2
- Total evictions: 6
- Stop reason: wall-clock

## Generations

| gen | fitness pass/close/fail | stack-apply | regression | outcome |
|---|---|---|---|---|
| 1 | 3/2/5 | stack-apply-pass | pass | promoted v5 → v6 |
| 2 | 1/3/6 | stack-apply-pass | rollback | ROLLBACK |
| 3 | 2/2/5 (+1 crash) | stack-apply-import-fail | — | no promote |
| 4 | 4/1/5 | stack-apply-pass | pass | promoted v6 → v7 |

Final tag + GitHub issue + cleanup as before.

git tag "evolve/run/$RUN_TS/final"
git push origin "evolve/run/$RUN_TS/final"

Cleanup:

curl -s -X POST http://localhost:8765/api/shutdown || true
sleep 2
powershell.exe -Command "Get-WmiObject Win32_Process | Where-Object { \$_.CommandLine -match 'bots.v0.runner|scripts/evolve.py|scripts/selfplay.py' -and \$_.CommandLine -notmatch 'SC2' } | ForEach-Object { Stop-Process -Id \$_.ProcessId -Force -ErrorAction SilentlyContinue }"
python -c "import socket; s=socket.socket(); r=s.connect_ex(('127.0.0.1',8765)); s.close(); exit(0 if r!=0 else 1)" || echo "WARNING: port 8765 still occupied"

Do NOT kill SC2_x64.exe.

---

Dashboard Control Panel Bridge

State file: data/evolve_run_state.json

{
  "status": "running",
  "parent_start": "v5",
  "parent_current": "v7",
  "started_at": "2026-04-21T21:33:00+00:00",
  "wall_budget_hours": 4.0,
  "generation_index": 3,
  "generations_completed": 2,
  "generations_promoted": 1,
  "evictions": 4,
  "resurrections_remaining": 3,
  "pool_remaining_count": 6,
  "last_result": {
    "generation_index": 3,
    "phase": "stack_apply",
    "imp_title": null,
    "stacked_titles": ["Chrono boost", "Forward pylon"],
    "new_version": "v7",
    "score": [0, 0],
    "outcome": "stack-apply-pass",
    "reason": "..."
  }
}

Status transitions:

• "running" — written on startup and after every phase.
• "completed" — written when the loop exits cleanly.
• "failed" — written on pool-generation failure.

Pool file: data/evolve_pool.json

See §1.2.

Results file: data/evolve_results.jsonl

One line per phase outcome. Each row's phase field is one of fitness, stack_apply, regression, or the crash equivalents. Full schema in frontend/src/hooks/useEvolveRun.ts.

Control file: data/evolve_run_control.json

{
  "stop_run": false,
  "pause_after_round": false,
  "updated_at": "2026-04-21T22:00:00+00:00"
}

(Dashboard mid-generation stop is a future enhancement — today the stop signal takes effect at the next generation boundary.)

---

What NOT to do

• DO NOT run concurrently with /improve-bot-advised. Pre-flight refuses if data/advised_run_state.json shows status: "running".
• DO NOT manually commit during a run. The pre-commit hook allows EVO_AUTO=1 commits to touch bots/**; manual commits may collide on bots/current/current.txt.
• DO NOT kill the SC2 process. Only restart Python processes.
• DO NOT set both EVO_AUTO=1 and ADVISED_AUTO=1. The sandbox hook fails loudly.
• DO NOT start a --daemon backend during an evolve run. The evolve loop drives games directly.
• DO NOT modify scripts/evolve.py or src/orchestrator/evolve.py mid-run.
• DO NOT use --no-commit for production runs.
• DO NOT lower --games-per-eval below 5 unless you're running a fast smoke test. 3 games is statistically too noisy to separate pass from close.

---

Troubleshooting

Pool generation fails

Check $LOGFILE for the Python exception. Common causes:

• Claude returned malformed JSON. _parse_claude_pool retries once on short/malformed responses; a second failure raises ValueError.
• claude CLI missing/unauthenticated. Run claude --version and claude -p "ping" --model haiku --output-format text --no-session-persistence to verify.
• Rate limit. Wait a few minutes.
• Mirror games crashed. Check data/evolve_results.jsonl; re-run Phase 0.5 manually.

First fitness eval crashes immediately

• SC2 not running. Start SC2 first.
• Port collision. Get-NetTCPConnection -LocalPort 8765, then cleanup block from Phase 4.
• Stale bots/<candidate>/. snapshot_current() picks fresh UUID names; collisions are almost always permission / disk-space issues.

Stack-apply import check fails on every generation

Claude's proposals are probably not orthogonal even after the retry. Check files_touched in the most recent pool. If two fitness-pass imps edit overlapping regions of the same file, their combined edits may fail to import at bots.vN+1.bot import time — the pre-regression import gate catches this and rolls the snapshot back. Manually prune the conflicting imp from the pool and --resume.

Regression rollback on every generation

New parent is a local regression. The fitness phase is finding imps that beat the current parent but not the prior parent — often a strong parent has blind spots that an imp exploits but that don't generalise. Watch for this pattern on the dashboard; if it persists for 3 generations, git reset --hard evolve/run/<TS>/baseline and re-run with a different seed.

Dashboard Evolution tab shows stale state

Atomic writes prevent half-written files; stale state is usually a cache-key mismatch in the frontend (see feedback_useapi_cache_schema_break.md). The hook file bumps its cache key whenever the schema changes — if you're seeing crashes after pulling a new version, hard-refresh the browser.

Pre-commit hook blocks the evolve commit

The sandbox hook checks EVO_AUTO=1 in the env, not the commit message. If the commit fails with "SANDBOX VIOLATION — commit blocked", the commit subprocess didn't inherit the env var. Confirm scripts/evolve.py's git_commit_evo_auto passes env=env where env["EVO_AUTO"] = "1".

"SANDBOX CONFLICT — commit blocked"

Both ADVISED_AUTO and EVO_AUTO are set. Close the shell, open a fresh one, retry.

No promotions after N generations

Expected when the pool is low-quality or the parent is already strong. Check the stack-apply column in the run log. If mostly stack-apply-import-fail, Claude's proposals are not orthogonal and their combined edits break at import — reseed the pool. If mostly rollback in the regression column, the fitness-pass threshold may be too loose for this parent — re-run with --games-per-eval 7.

Stale data/evolve_run_state.json blocks a fresh run

python -c "
import json
from pathlib import Path
p = Path('data/evolve_run_state.json')
state = json.loads(p.read_text())
state['status'] = 'stopped'
p.write_text(json.dumps(state, indent=2, sort_keys=True) + '\n')
"

---

Reverting an Evolve Run

Every run is fully reversible. The baseline tag from Phase 0.7 is the restore point.

Quick revert (everything)

git tag -l "evolve/run/*"
git reset --hard "evolve/run/<RUN_TS>/baseline"
git push origin master --force-with-lease
git clean -fd bots/

Partial revert

Promotion commits and regression-rollback commits are sequential on master. Find the boundary you want to keep:

git log "evolve/run/<RUN_TS>/baseline..evolve/run/<RUN_TS>/final" --oneline --grep "\[evo-auto\]"
git reset --hard <commit-sha-after-good-promote>
git push origin master --force-with-lease

Morning-after checklist

1. Read $LOGFILE.
2. Check the generation table — which promoted, which rolled back.
3. Inspect bots/current/current.txt matches the expected final parent.
4. git log "evolve/run/<RUN_TS>/baseline..master" --oneline.
5. Quick regression gate: uv run pytest && uv run mypy src && uv run ruff check ..
6. If unhappy, use quick revert. If happy, git clean -fd bots/ to remove orphaned cand_* dirs.

---

Safety Rails

• One evolve run at a time. Pre-flight refuses on fresh running state (<12h).
• No concurrent advised runs. Pre-flight refuses on running advised.
• Atomic state writes. All JSON writes use tmp.replace(path).
• Fitness + stack-apply import gate + regression are non-negotiable. Never bypass any phase gate; the whole point is that LLM proposals are untrusted and must earn their promotion empirically.
• EVO_AUTO scope is bots/**. Broader than advised's bots/current/** because evolve creates new version dirs.
• Never kill SC2_x64.exe.
• Wall-clock discipline. Check elapsed at every phase boundary.

---

Relationship to Other Skills

/improve-bot-evolve (outer loop, this skill)
  ├── Phase 0: Bootstrap (sandbox, pre-flight, baseline tag, start backend)
  ├── Phase 1: Seed + Pool (mirror games, generate_pool via Claude)
  ├── Phase 2: Generation loop
  │     ├── 2a Fitness       (run_fitness_eval per active imp)
  │     ├── 2b Stack-apply   (_stack_apply_and_promote → vN+1 + import check)
  │     ├── 2c Regression    (run_regression_eval vs prior parent)
  │     └── 2d Pool refresh  (retry bookkeeping + generate_pool delta)
  ├── Phase 3: Loop decision (wall-clock / pool-exhausted / dashboard-stop)
  └── Phase 4: Morning Report (final tag, GitHub issue, generation table)

• /improve-bot-advised — sibling. Linear. Mutually exclusive with evolve.
• /improve-bot — building block used inside advised's dev path. Not called by evolve.
• /improve-bot-triage — post-run helper; can read documentation/soak-test-runs/evolve-*.md.
• /a4g-dashboard-check — pre-flight (Phase 0.6) and post-run validation.
• /repo-update — end-of-cycle docs + README sync after a productive run.