triage

name	triage
description	Propose and apply optimal ordering for pending specs on the graph backlog. LLM proposes, human approves. Use when: 'triage the backlog', 'what should I work on next', 'reorder my specs', 'find duplicates in graph'.
argument-hint	[deep] [all] [each] [dry-run] [--project NAME] [--roadmap-id ID]

Triage

Propose an optimal ordering for pending specs on ~/.fno/graph.json based on dependencies, sequencing, priority versus project goals, and duplicate detection.

Philosophy

• LLM proposes, human approves. Triage never auto-applies priority changes — priority is a business decision.
• Shallow by default. Metadata-only reasoning keeps token cost low for large backlogs. Use deep when you want richer inference from the plan contents.
• Cycles are dropped automatically. If a proposed dependency would create a cycle (A blocks B, B blocks A), validation drops the offending edge and logs the conflict.
• Project-scoped by default. Triage filters to the current repo's project (matched by canonical repo root, stable across worktrees). Pass all to triage across every project or --project <name> to target a specific one. Matches the scoping of roadmap-tasks.py next/ready.

Setup

Project scoping requires at least one node registered to the current repo. The first /blueprint with auto-intake (or a manual roadmap-tasks.py intake) stores the canonical repo root as the node's cwd and derives a project name from the repo directory basename. Subsequent triage runs from the same repo — including from any git worktree of it — auto-detect that project.

If no project is detected (no adopted node yet for this repo), triage falls through to all projects and prints a hint in the scope line so the behavior is visible, not silent.

Invocation

Positional modifiers (boolean switches): deep, all, dry-run. Value-carriers (flags with arguments): --project NAME, --roadmap-id ID.

Form	Effect
/triage	Shallow triage, scoped to the current project
/triage deep	Read the first 150 lines of each plan_path for richer inference
/triage all	Include pending nodes from every project
/triage each	Iterate through every project with pending nodes, running the full pipeline and per-project approval once per project
/triage deep all	Combine: cross-project, read plan contents
/triage --project <name>	Scope to a specific project by name
/triage --roadmap-id rm-X	Triage only nodes tagged to a specific roadmap
/triage dry-run	Print candidates only, no LLM call, no mutations

Invocation surface (CLI-source-agnostic)

The skill issues triage verbs through whichever implementation is available. Preference order:

1. fno backlog triage <verb> <flags> - the v2 CLI (canonical)
2. python3 scripts/triage.py <verb> <flags> - the shim, which itself forwards to v2 when fno is on PATH or falls back to the in-repo module via cli/src

Both satisfy the same JSON protocol - callers see identical input/output. Every scripts/triage.py … command in the steps below is equivalent to fno backlog triage …; prefer the latter when fno is on PATH so the call path is one process shorter.

Translating positional modifiers to the underlying command

Both implementations use standard argparse/Typer conventions (--deep, --all, --dry-run). When executing a user invocation, translate positional words into the equivalent flag:

User typed	Pass through
deep	--deep
all	--all
dry-run	--dry-run
each	(no direct flag; orchestrates multi-run invocation in the skill, not the command)
--project foo	--project foo (unchanged)
--roadmap-id rm-X	--roadmap-id rm-X (unchanged)

Mutually-exclusive and composition rules

• each combined with --project <name> is an error. The skill must refuse this combination with the exact message "each and --project are mutually exclusive: --project scopes to one, each iterates many" and exit without calling the script. Confirms before any graph mutation.
• each combined with all is redundant (each is stricter). Silently prefer each and note in the scope line printed to the user.
• each composes normally with deep, dry-run, and --roadmap-id. Those modifiers forward into every per-project invocation.

Process

1. Gather context. Run the context generator to get pending nodes plus project goals from config.toml. Forward the user's positional modifiers as the matching flags (e.g. deep -> --deep):

   # v2 preferred; shim used when `fno` is not on PATH
   (fno backlog triage context [--deep] [--all] [--project NAME] [--roadmap-id ID] 2>/dev/null \
      || python3 scripts/triage.py context [--deep] [--all] [--project NAME] [--roadmap-id ID]) \
     > /tmp/triage-ctx.json
   

   The context JSON has two top-level arrays:

   • candidates: claim-ready rows (_status: ready or blocked). These are what the LLM should reason about for ordering, blocker edges, and priority changes.
   • ideas: plan-less rows (_status: idea). These are NOT claimable work - they are captured thoughts waiting for a spec. The LLM should mention them in its summary with the recommendation "write a spec for this idea before claiming it" rather than proposing dependency edges or claim ordering. Run /blueprint against the idea's title + details, then fno backlog intake <plan_path> to flip the node to _status: ready.

   If candidates is empty AND ideas is empty, print "no pending nodes to triage" and exit. Done. If candidates is empty but ideas is non-empty, surface the idea list to the user with the spec-it-first recommendation and exit (no LLM reasoning needed - there is no claim-ordering decision to make until a spec lands).

2. LLM reasoning. Spawn a subagent (Task tool) with the context JSON and this instruction. Run the subagent at temperature 0 - triage is a classification task and determinism drives the 95%+ consistency target (fno backlog triage consistency measures it).

   You are a backlog triage classifier. First reason, then label - this ordering (analysis before the JSON) is what makes the classification consistent, so never emit the JSON first.

   First, in a short ## Reasoning section, work through the candidates: which specs block which, which priorities are misaligned with the project goals, which are stale or duplicated. Name the primary concern of each spec you touch. When a spec raises several concerns at once, classify on its primary intent, not the loudest surface signal.

   Then, output an optimal ordering as JSON with four keys:

   • dependencies: edges where one spec must complete before another (e.g. {"from": "ab-X", "to": "ab-Y", "reason": "..."} means Y is blocked_by X).
   • priority_changes: spec priority adjustments that align better with the project's stated goals.
   • defer: nodes to pause with {"id": "ab-X", "reason": "..."}. Use when a node is stale, waiting on an external decision, or otherwise not suitable for the current cycle. Defer is reversible via fno backlog undefer <id>. Reason is required and is surfaced in the kanban view alongside the card.
   • duplicates: specs that look like near-duplicates, with a recommended action of "merge" and a reason. To pause one of a pair without merging, use the defer action above instead.

   Every entry MUST include a reason field (one line) referencing the plan contents (deep mode) or the title/priority signal (shallow mode). An entry without a reason is dropped by validation, so a missing reason is a wasted proposal. Do not propose self-edges or edges that create cycles.

   Field reference: each candidate carries enrichment fields beyond the basic id/title/priority. size is S/M/L (omit size-based reasoning when null). domain is the execution domain (code/research/etc). details is the user's implementation guidance captured at intake; cite it for shallow-mode reasoning instead of paying for a deep read. claim_history.session_count > 1 means the node has been claimed and released before; claim_history.total_cost_usd is cumulative spend without shipping. ship_state.pr_number set means a PR exists - the node may already be done and just needs a done flip rather than re-triaging. ship_state.merge_status carries the PR's merge state (merged/closed/null).

   IMPORTANT: only reason over the candidates array. The ideas array contains plan-less rows that are not claimable yet - do NOT propose dependencies or priority changes for ideas. Pass them through unchanged in your summary so the user sees them and can spec them next.

   Examples (reasoning before label; classify on primary intent):

   • Implicit dependency. Candidate ab-9f "add rate-limit headers to the API" and ab-3c "build the API gateway". The gateway is never named as a blocker, but headers cannot ship before the gateway exists. Reasoning: ab-9f's work sits on top of ab-3c's surface. Label: dependencies: [{"from":"ab-3c","to":"ab-9f","reason":"rate-limit headers need the gateway surface first"}].
   • Emotion over intent. Candidate details read "this flaky test has wasted HOURS, it is infuriating, the whole suite is garbage." The heat is noise; the actionable intent is one flaky test. Reasoning: strip the frustration, the core ask is de-flaking one test - a normal p2, not a p0 because it is loud. Label: no priority bump; a defer only if it is blocked on an external fix.
   • Multiple issues, pick the primary. Candidate details raise a perf regression, a typo in a log line, and a docs gap. The perf regression is the reason the node exists; the rest are incidental. Reasoning: classify on the perf regression (the primary), mention the others in the summary, do not split the node. Label: priority reflects the perf regression only.

   The subagent returns proposal JSON.

   Tournament ordering (large backlogs). When count (from triage context) is large enough that a one-shot ordering gets unreliable - roughly count >= 6 - prefer comparative judgment over absolute scoring for the claim-order decision: ask the LLM to pick a winner per candidate PAIR ("ship X or Y first?") rather than rank all at once. Enumerate the candidate pairs, collect each verdict as {"winner": "ab-X", "loser": "ab-Y"}, write them to /tmp/triage-verdicts.json, then fold them into a single consistent order:

   fno backlog triage rank --verdicts /tmp/triage-verdicts.json
   

   It aggregates by Copeland score (wins minus losses), tolerating the occasional contradictory or cyclic verdict, and emits a best-first order. Apply that order to the board so board position matches work order: seed the top item with fno backlog rank <first-id> --top, then chain each remaining id after its predecessor with fno backlog rank <id> --after <previous-id>. Do NOT call --top for every id in a forward pass: --top inserts before the current front of the lane, so iterating best-first would reverse the order (the last id processed would land first). Feed the ranking into the priority_changes rationale too. For a small backlog the one-shot proposal above is cheaper and fine; reserve the pairwise pass for when the node count makes it worthwhile.

3. Validate. Run:

   (fno backlog triage validate /tmp/triage-proposal.json 2>/dev/null \
      || python3 scripts/triage.py validate /tmp/triage-proposal.json) \
     > /tmp/triage-cleaned.json
   

   Stderr surfaces cycles, unknown IDs, or invalid priorities that were dropped. Stdout is the cleaned proposal.

4. Present to user via AskUserQuestion. Show a summary of the proposed changes with per-item rationale. Offer:

   • Approve all — apply every edge, priority change, and flag every duplicate
   • Pick — select a subset to apply (pass --pick id1,id2,... to apply)
   • Reject — discard the proposal; exit 0

5. Apply. On approve or pick:

   fno backlog triage apply /tmp/triage-cleaned.json [--pick id1,id2] \
     || python3 scripts/triage.py apply /tmp/triage-cleaned.json [--pick id1,id2]
   

   Apply runs inside a single locked_mutate_graph() so graph.md re-renders once with all mutations. Report the applied count plus any flagged duplicates for the user to resolve manually.

6. Suggest next step. If any dependencies or priorities changed, invite the user to run /target to pick the now-correctly-ordered top node.

Iteration Mode (each)

When each is present, the skill orchestrates the Process pipeline once per project with pending nodes, preserving project boundaries so the LLM never reasons across unrelated repos. This makes it structurally impossible to propose cross-project dependency edges or flag cross-project duplicates - the reasoner simply never sees the other project's candidates.

1. Enumerate. Call fno backlog triage projects (or python3 scripts/triage.py projects if fno is not on PATH) to get the list of projects with at least one pending node.

2. Guard. If the list is empty, print "no pending nodes in any project" and exit 0. Done.

3. Iterate. For each project (in the order returned by the script):

   a. Print a scope banner: "=== Triaging project '{name}' ({count} pending) ===" b. Run the existing Process steps 1-5 scoped to that project by passing --project {name} on every script invocation. c. Forward any composable modifiers from the outer invocation: deep -> --deep, dry-run -> --dry-run, --roadmap-id X -> --roadmap-id X. d. Present the proposal via AskUserQuestion as in the single-project flow. On Approve or Pick, call apply scoped to the project. On Reject, skip that project's apply and advance to the next. e. Accumulate per-project applied counts for the final summary.

4. Summarize. After the loop completes, print a single summary line: "Triaged N projects: X edges applied, Y priority changes, Z duplicates flagged." Include a breakdown per project if any project errored.

Failure handling

If a per-project invocation fails (context generation returns an error, proposal JSON is malformed, apply hits a locked-mutate conflict), log the error to stderr with the project name, mark that project as errored in the summary, and continue to the next project. Never abort the whole iteration because one project failed. The user can re-run /triage --project {name} later to address the single failure.

Cost profile

One LLM reasoning call per project. For N projects with M average pending nodes each:

• Shallow: ~0.5 KB/node -> per-project LLM call ~M * 0.5 KB input
• Deep: ~5 KB/node -> per-project LLM call ~M * 5 KB input

Total tokens scale linearly with project count. For users with >10 active projects, prefer each over all deep - the sum of N small calls is usually cheaper than one call over the union, and the LLM reasons better on smaller focused sets.

Token Cost

Mode	Bytes per node	20-node backlog
Shallow (default)	~0.5 KB metadata	~10 KB total
Deep (deep)	~5 KB with 150-line excerpt	~100 KB total

Chunk into two passes if pending count exceeds 50 in deep mode.

Integration with /target

When /target is invoked with no arguments, the wizard offers "Pick from backlog" as an input type. That path runs this skill inline, presents the top-ranked ready node with rationale, and on confirmation execs /target {plan_path} for that node.

Out of Scope

• Fully automated triage (no human in the loop). Intentionally rejected.
• Cross-roadmap priority comparison. Single-roadmap or all-pending only.
• Auto-merging detected duplicates. Flagged for human resolution.
• Auto-undeferring on a calendar trigger (time-bounded defer). Defer is reversed manually via fno backlog undefer <id> for now.
• Learning from past decisions. Prompt-only reasoning for now.

Health monitoring (background, deterministic)

/triage itself is interactive and LLM-driven. For continuous backlog hygiene without human attention, use the deterministic check:

# Hourly local check; produces no output unless something is wrong
/loop 1h fno backlog triage health --check --quiet

Exit code 4 indicates a threshold breach (idea pile, stale-ready, failure-prone, or collisions). Configurable via config.health_monitor in config.toml; full schema in CLAUDE.md > Backlog Health Monitoring. The monitor is pull-based (poll every interval) and never auto-mutates the graph; breaches notify and the human (or a follow-up /triage) decides what to do.

References

• fno backlog triage (canonical) — the v2 CLI sub-app; source in cli/src/fno/graph/triage.py
• scripts/triage.py — compatibility shim that forwards to the v2 CLI (or falls back to the in-repo module when fno is not on PATH)
• cli/src/fno/graph/store.py — locked_mutate_graph() entry point
• ~/.fno/graph.md — the kanban view that reflects applied changes
• cli/src/fno/health_monitor.py — threshold evaluation, notification dispatch, history append/read, trend summary