Triage Woo Feature Requests

Full Feature Request Triage

You are running a full triage of open feature requests for a WooCommerce Marketplace product. This orchestrator is built for products with hundreds of FRs: the working set lives on disk (not in your context), each phase runs in a subagent that returns a compact flagged list, and progress is resumable per FR so a disconnect or compaction never loses ground.

Read first:

• .claude/skills/shared/RULES.md — display rules, confidence, plain text comments, URL carry-through, HTML entity decoding, translation.
• .claude/skills/shared/DISPLAY.md — pagination conventions (flat and grouped).
• .claude/skills/shared/RESOLVE_PRODUCT.md — product ID resolution.
• .claude/skills/shared/KNOWLEDGE_BASE.md — used by the completed phase.

State directory: .triage-state/<product_id>/ (gitignored). Helper CLI: scripts/triage_state.py. Use it for every read/write of state.

Step 1 — Resume or fresh start

After resolving the product (Step 2), run:

python3 scripts/triage_state.py status --product-id <id>

If exists is true and any phase_status is in_progress or there are entries in flagged/ or actioned.jsonl, ask:

Found prior triage state for [product_name] (id [id]):
  Fetched: [fetched_at humanized, or "never"]
  Working set: [N] FRs cached
  Actioned so far: [M]
  Phase status: completed=[…] duplicates=[…] spam=[…] support=[…] stale=[…]

Resume from where you left off? (Y / start fresh / cancel)

• Y / Enter: continue. Skip phases already completed. Re-enter in_progress phases mid-flight.
• start fresh: run triage_state.py reset --product-id <id>, then proceed.
• cancel: stop.

If no state exists, proceed straight to Step 2.

Display only the phases the user selected (Step 4). Don't list status for phases that were never initialised.

Step 2 — Resolve the product

Follow .claude/skills/shared/RESOLVE_PRODUCT.md.

Step 3 — Verify ownership (read-only)

Fetch the first open feature request for this product:

wccom-feature-requests-list with product_id: <id>, status: "publish", per_page: 1

• If the list is empty, skip this check — nothing to action anyway.
• If at least one FR returned: read the response shape. If the API surfaces an editable / can_edit / _links.edit field (or equivalent), use it to confirm write access without performing any write.

Do not perform a no-op write probe (the previous design wrote a current status back to the FR — even no-ops may trigger audit logs, webhooks, or last_modified bumps). If you cannot determine write access from the read response, proceed and let the first real write either succeed or fail; if the first write returns a permission error, stop and report:

⛔ Product [id] does not appear to be owned by the current API credentials.
Write actions are being rejected. Please re-run with credentials that own
this product.

Do not continue actioning further phases.

Step 4 — Select phases to run

Which checks should I run? (default: all)

  [1] Completed   — flag requests fulfilled by a shipped release
  [2] Duplicates  — find and close duplicate requests
  [3] Spam        — silently mark spam requests
  [4] Support     — close misplaced support questions
  [5] Stale       — close old low-vote requests

Reply with numbers (e.g. "2 4"), or press Enter / type A to run all.

Map to phase keys: completed,duplicates,spam,support,stale. Initialise:

python3 scripts/triage_state.py init \
  --product-id <id> \
  --product-name "<product_name>" \
  --phases <comma-separated-keys>

init is resume-safe — preserves existing phase_status and fetched_at.

Step 5 — Build the knowledge base (only if Completed is selected)

If Phase 1 (Completed) is selected AND knowledge_base.json does NOT exist under .triage-state/<id>/, follow .claude/skills/shared/KNOWLEDGE_BASE.md in full to build the changelog + documentation knowledge base.

Write to .triage-state/<id>/knowledge_base.json per the schema in that file. Subsequent runs reuse it.

If Phase 1 isn't selected, or the file exists, skip.

Step 6 — Fetch ALL open feature requests (to disk)

Check freshness first:

python3 scripts/triage_state.py fetched-age --product-id <id>

• fetched: false: proceed to fetch.
• fetched: true: ask:

  Cached working set is [age humanized] old ([N] FRs).
  Refresh from the API? (y / N — keep cache)
  

  • y: re-fetch.
  • Enter / N: skip fetch, reuse cache.

To fetch — MUST be done in a subagent. Do NOT call wccom-feature-requests-list from the main (orchestrator) context. MCP tool results land in the caller's context window; for products with hundreds of FRs this blows the budget before any phase runs. The fetch subagent's context holds the raw JSON; the orchestrator only sees a compact summary.

Spawn a general-purpose subagent with the following prompt (substitute <id>, <product_name>):

You are a fetch-only subagent for the wccom triage orchestrator.

Goal: page through wccom-feature-requests-list and save every open FR to
disk for product <id> (<product_name>).

DO NOT:
- Call any wccom-feature-requests-* write tools.
- Re-fetch beyond what's needed (stop on the first short page).
- Echo FR payloads back to the orchestrator. Return only a compact summary.

DO:
- Call `mcp__wccom-feature-requests-prod__wccom-feature-requests-list` with
  product_id: <id>, status: "publish", per_page: 100, starting at page 1.
- For each page, write the raw JSON response to
  $TMPDIR/triage-page-<page>.txt via the Write tool. If a tool result is
  truncated and saved to a tool-results file by the harness, copy that
  file to $TMPDIR/triage-page-<page>.txt instead — do NOT Read it and
  re-Write it.
- Stop when a page returns fewer than 100 items.
- Merge:
  python3 scripts/save_frs.py $TMPDIR/triage-page-*.txt -o /Users/jasonkytros/wccom-triage-agents/.triage-state/<id>/working_set.jsonl
- Mark fetched:
  python3 scripts/triage_state.py set-fetched --product-id <id>
- Return one-line JSON summary on stdout:
  {"pages": <int>, "total": <int>, "working_set": "<path>"}
- Do NOT include FR titles, ids, or descriptions in the summary.

Working dir: /Users/jasonkytros/wccom-triage-agents

After the subagent returns, the orchestrator prints:

Fetched [total] open FRs for [product_name] → .triage-state/[id]/working_set.jsonl

If total == 0: report "No open feature requests found for [product_name]." and stop.

Never load the full working set into your own context. This includes:

• Do NOT call the MCP list tool directly from the orchestrator.
• Do NOT Read working_set.jsonl, page files, or actioned.jsonl in full.
• Do NOT Write FR payloads from the orchestrator (the payload appears in tool-call args and is just as costly as a Read).
• Subsequent phases must always go through subagents.

Step 7 — Run each selected phase (subagent dispatch)

For each selected phase not already completed:

1. Skip if done: phase_status[<phase>] == "completed" → skip.
2. Mark in progress:

   python3 scripts/triage_state.py set-phase --product-id <id> \
     --phase <phase> --phase-status in_progress
   

3. Build unactioned input — drop FRs actioned in prior phases or earlier this run:

   python3 scripts/triage_state.py filter-unactioned --product-id <id> \
     --out .triage-state/<id>/flagged/<phase>.input.jsonl
   

4. For duplicates only — prompt comparison mode before spawning (subagent cannot prompt):

   Comparison depth: (F)ast keyword/TF-IDF, or (I)n-depth semantic rerank?
   In-depth needs .venv with sentence-transformers installed.
   

5. Spawn a subagent — detection only, no writes. Use the subagent prompt template below. Pass:
   • subagent_type: general-purpose
   • Skill file: .claude/skills/detect-<phase>/SKILL.md
   • Input JSONL: .triage-state/<id>/flagged/<phase>.input.jsonl
   • Output JSONL: .triage-state/<id>/flagged/<phase>.jsonl
   • Knowledge base path (completed only): .triage-state/<id>/knowledge_base.json
   • Comparison mode (duplicates only): fast | in-depth
   • mode: orchestrated (suppresses re-scan in PHASE_LOOP.md)
6. Empty output handling — if the subagent's output JSONL is empty:
   • Print: _No <phase> findings._
   • Mark phase completed:

     python3 scripts/triage_state.py set-phase --product-id <id> \
       --phase <phase> --phase-status completed
     

   • Continue to the next phase.
7. Read flagged output — main agent reads only what it needs to present. Page user prompts in batches of 20 per DISPLAY.md (grouped or flat per phase). Decode HTML entities. Translate non-English excerpts per RULES.md.
8. Execute approved actions in the main agent (auth + confirmations stay here). Per FR the user approves, see the per-phase action table below.
9. After every successful API write, append to actioned.jsonl immediately — that's the resume anchor:

   python3 scripts/triage_state.py append-actioned --product-id <id> \
     --phase <phase> --fr-id <id> --action <verb> --status <new_status>
   

10. API write failure handling — if any write call fails:
    • Do not append to actioned.jsonl (so resume retries it).
    • Print: ⚠️ ID [id] — "[title]": failed — [error]
    • Continue to the next FR.
    • If a comment posted but the status update failed, log action=comment-only status=publish to actioned.jsonl so we know not to re-post the comment. Surface the half-state in the summary.
11. Skipped FRs: when the user explicitly passes on a flagged FR (does not approve closure), append to actioned.jsonl with action=skipped status=publish so future re-scans don't re-prompt:

    python3 scripts/triage_state.py append-actioned --product-id <id> \
      --phase <phase> --fr-id <id> --action skipped --status publish
    

12. End-of-phase loop:
    • Ask: Would you like to action more requests from this phase? (Y / N)
      • Y: loop back to step 7 with remaining items.
      • N / empty: continue.
    • Always ask the re-scan prompt next. Substitute <phase> with the current phase name (e.g. "completed", "duplicates"):

      Run the <phase> detection again in case anything was missed, or move
      on to the next phase? (Another look / Move on)
      

      • Another look: re-run from step 3 (rebuild unactioned input, re-spawn subagent). If the subagent returns zero new flagged FRs, print _No new findings._, mark phase completed, and continue. Do not loop the re-scan prompt again.
      • Move on: mark phase completed.
13. Print a one-line phase summary, continue.

Per-phase action table

Spam fallback — when calling wccom-feature-requests-update-status with status: "spam" returns a permission error (403 / "not allowed"), retry with status: "closed" and log action=marked-spam-fallback status=closed. Surface fallbacks in the phase summary.

Duplicates extras — after all closures for a primary, optionally run the "Extract insights for each primary" step from the duplicates skill (Step 6). Main agent only — it needs to read closed FR descriptions from the working set on disk.

Subagent prompt template

Use this when spawning the per-phase subagent. Substitute <…>.

Base (every phase)

You are a detection-only subagent for the wccom triage orchestrator.

mode: orchestrated

DO NOT:
- Call any wccom-feature-requests-* write tools (no comment, no update-status).
- Re-fetch the FR list.
- Resolve the product (already done).
- Crawl the changelog or docs (already done; knowledge base path provided
  when relevant).
- Run the standalone PHASE_LOOP.md re-scan offer — the orchestrator handles
  it. Return after the phase summary.

DO:
- Read the skill file at <skill_path>. Each detect-* skill marks where the
  subagent should begin with a header line:
  `## Step <N> — DETECTION STARTS HERE — …`
  Skip everything above that header.
- Read the input working set from <input_path> (JSONL, one FR per line,
  fields: id, title, description, votes, date, url, status).
- Process FRs in chunks of 50. After each chunk, append flagged records to
  the output file <output_path>.
- Write flagged records as JSONL using the skill's "Flagged record schema"
  block. Every record must include at minimum:
  { "id": <int>, "title": "<str>", "url": "<str>",
    "reason": "<one sentence>", "confidence": "High" | "Low",
    "excerpt": "<first 1–3 sentences of description, trimmed>" }
  Include phase-specific extras per the skill's schema.
- Decode HTML entities in excerpts. Carry the API `url` field verbatim.
- Return a compact JSON summary to stdout when done:
  { "phase": "<phase>", "scanned": <int>, "flagged": <int>,
    "output": "<output_path>", "notes": "<caveats or empty>" }

Inputs:
  phase:           <phase>
  product_id:      <id>
  product_name:    <product_name>
  skill_path:      <skill_path>
  input_path:      <input_path>
  output_path:     <output_path>
  kb_path:         <kb_path or "n/a">
  comparison_mode: <fast | in-depth | "n/a">

Phase-specific tail — append to the base

completed:

- Use kb_path to load the knowledge base built by the orchestrator.
- Apply the docs source rule from KNOWLEDGE_BASE.md / detect-completed
  Step 4: docs-sourced matches must cite a URL present in the knowledge
  base; never infer.

duplicates:

- Skip Steps 1, 2, 2b, 2c of the skill — input is already on disk and
  comparison_mode is set.
- Run the detection script directly on <input_path>:
  - fast:     python3 scripts/detect_duplicates.py <input_path> --json
  - in-depth: .venv/bin/python3 scripts/detect_duplicates.py <input_path> --semantic --rerank --json
- Emit one record per duplicate-to-close with shared "group_id" and
  embedded "primary" object per the duplicates schema.
- Add a top-level "groups": <int> field to the stdout summary.

spam / support / stale: base alone — no extra tail.

Step 8 — Triage summary

After all selected phases are completed, read state:

python3 scripts/triage_state.py status --product-id <id>

Group actioned.jsonl by action. Print:

## Triage Complete — [product_name]

Total open requests fetched: [N]

✅ Marked completed:        [N]
❌ Closed as duplicates:    [N]
🚫 Marked as spam:          [N]
   ↳ closed (spam fallback): [N]
❌ Closed as support:       [N]
❌ Closed as stale:         [N]
⚠️  Failed (need retry):    [N]
📋 Remaining open:          [N − total actioned]

Step 9 — Free-form analysis (optional)

Ask:

Would you like me to run any further analysis on the remaining [N] open requests?

Examples:
  - Flag requests that appear to be for a different plugin or product
  - Identify requests in a specific language or region
  - Surface requests around a particular feature area or theme
  - Any other custom filter or pattern

Describe what you'd like me to look for, or type N to finish.

If declined: print "Triage complete. Thanks!" and stop.

9a — Run analysis

Build the unactioned set:

python3 scripts/triage_state.py filter-unactioned --product-id <id> \
  --out .triage-state/<id>/flagged/freeform.input.jsonl

Spawn a general-purpose subagent. Pass the user's stated goal, the input path, and the output path .triage-state/<id>/flagged/freeform.jsonl. The subagent processes unactioned FRs in chunks of 50 and writes flagged records: {id, title, url, votes, date, reason, excerpt}.

Present findings paged in batches of 20 per DISPLAY.md:

## Free-Form Analysis: [user's stated goal]
[N] requests analysed · [Y] flagged (showing 1–20)

[N]. ID [id] — "[title]"
     [votes] vote(s) · opened [date]
     [url]
     Reason: [one sentence]

     Excerpt: "[1–2 verbatim sentences]"

9b — Action menu

Found [Y] requests matching your criteria.

What would you like to do with these?

  1. What comment should I post? (describe or paste the comment text)
  2. What status should I set? (closed / spam / completed / or leave open)

You can also select a subset — reply with numbers to act on specific items
(e.g. "1 3 5"), A for all, or N to skip.

9c — Execute

Plain text only (see RULES.md).

For each approved FR:

1. If a comment was provided: wccom-feature-requests-comment.
2. If a status was provided: wccom-feature-requests-update-status.
3. On success, append to actioned.jsonl with phase=freeform action=<verb> status=<new_status>. On failure: report, do not append, continue.

Per-FR confirmation:

✔ ID [id] — "[title]": [action taken]
⚠️  ID [id] — "[title]": failed — [error]

9d — Loop

Anything else you'd like to analyse in the remaining [N] open requests?
(Describe what to look for, or N to finish.)

Repeat 9a–9d until done.

Step 10 — General rules

• Bash hygiene: when running inline Python via Bash, always use a heredoc with a single-quoted delimiter — never python3 -c "...". The -c form passes the script through the shell, where ! triggers history expansion and $var references get expanded or stripped. A single-quoted heredoc suppresses all shell expansion:

  python3 << 'PYEOF'
  # safe: !=, $var, and ! all reach Python unmodified
  PYEOF
  

• Never re-fetch the FR list after Step 6. All analysis uses the cached working set on disk.
• Never load the full working set into your own context. Always operate on flagged outputs from subagents or paged reads.
• Always skip actioned FRs. Use filter-unactioned before every detection.
• Append to actioned.jsonl immediately after every successful write.
• Wait for user confirmation before any write action.
• Process writes sequentially per FR (comment first, then status).
• Always record skips with action=skipped status=publish so skipped FRs don't reappear on resume or re-scan.
• Plain text comments only, ID display rules, URL carry-through, HTML entity decoding, non-English translation — see .claude/skills/shared/RULES.md.