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Task close postmortem

Skill bks-lab/open-bridge/skills/task-close-postmortem

Your AI coding agent starts every session knowing your repos, your clients, and how you work — a plain git repo of markdown + YAML it reads at session start, independent of model or frontend. Context compounds instead of restarting. MIT.

Install
npx -y skills add bks-lab/open-bridge --skill task-close-postmortem

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Postmortem capture + bridge-improvement scan at task close. Surfaces six optional questions (time invested, estimate vs actual, what went well, what burned time, where the bridge fell short, concrete improvement proposal), writes structured frontmatter back to STATUS.md, and generates proposal files under work/_learning/proposals/ for later review via /bridge-learn. Invoked automatically by protocols/standing-orders/task-sync.md Phase 3b at task close, and directly user-invokable for ad-hoc reflection. Trigger: "task done", "document everything", "wrap up", "wrap-up", "task complete", "post-mortem", "/postmortem the last hour", "reflect on the piece just finished", "review the last block", "what did we learn from X".

SKILL.md

9.3 KB, as published. Nobody here has run it

Task-Close Postmortem

Captures a short reflection at task close, maps any surfaced gaps to concrete Bridge-File-Improvement-Proposals, and writes both back as structured artifacts.

The skill is always optional and always interruptible — every question is skippable, and skipping all six leaves the task unchanged from today's behavior. Default-on (per bridge-config.yaml.learning.postmortem.enabled) but cost-light: fast-path through all six skips is <20 seconds.

When this skill runs

  1. Auto, via task-sync.md Phase 3b — every time a task closes, after the dual_doku self-check passes and before the 3-step move.
  2. Manual — when the user says any of: "/postmortem the last hour", "reflect on the piece just finished", "post-mortem this", "what did we learn from X". In manual mode the scope is not bound to a task folder — the skill reflects on the recent activity (last log.md entries, recent commits, recent file edits). No frontmatter writes happen in manual mode; output is only the proposals.

Inputs

Auto mode:

  • work/tasks/<slug>/STATUS.md — the task being closed
  • workflow/contexts/<context>.yaml if STATUS references a context
  • recent entries from work/log.md (last 24h or all entries since task created)

Manual mode:

  • last N log.md entries (N defaults to last 10, or "the last hour")
  • recent uncommitted git diff in this Bridge repo and any other repos touched

The six questions

(Full script in references/postmortem-questions.md.)

Surface them one at a time. Accept skip-phrases from bridge-config.yaml.learning.postmortem.skip_phrases — default ["skip", "next", "—", "no", "next", "."]. If cutdown_after_skips (default 3) consecutive skips occur, switch to Cutdown mode for the remaining questions: ask only the single catch-all "anything else worth noting?". Empty answer → done.

#Question (EN)Writes to
1Time invested?frontmatter time_invested
2Estimate vs actual?frontmatter estimate_vs_actual
3What went well?body ## Postmortem → "What went well"
4What burned time?body ## Postmortem → "What did not go well"
5Did the bridge fail you?frontmatter bridge_gaps[] + body
6Concrete improvement?proposal file + body

Use the conversation language from bridge-config.yaml.language.conversation (default en). EN fallback if missing.

Frontmatter write rules

Use the Edit tool against work/tasks/<slug>/STATUS.md. All four fields (time_invested, estimate_vs_actual, lessons, bridge_gaps) are optional in the schema (work/templates/_schema.status.yaml) — omit the line entirely when the user skipped that question. Never write empty strings or null.

Q1 → time_invested: — accept any of the schema-allowed forms (~12h, P3D, PT4H, , unknown). Loose parsing OK; if user types "about 12 hours over 3 days", record as "~12h" and add the prose to body.

Q2 → estimate_vs_actual: — match to nearest enum value: ok / 1.5x / 2x / 3x / >3x / re-scoped / —. If user says "estimate was 4h, so 3x" record "3x" and add the math to body for human readability.

Q3+Q4 → body ## Postmortem subsections. Free-form prose. Bullet each line.

Q5 → bridge_gaps[] array. Each entry is one of: {skill: NAME, why: TEXT} / {standing_order: NAME, why: TEXT} / {rule: NAME, why: TEXT} / {doc: NAME, why: TEXT} / {protocol: NAME, why: TEXT} / {memory: NAME, why: TEXT}. A single user answer can yield multiple bridge_gaps entries.

Q6 → free-text improvement. Add to body "Concrete Bridge improvements proposed" sub-section. Each bullet there will be examined in the proposal-writing phase.

Improvement-Scan phase

After all six questions are answered (or skipped), scan for proposal-worthy candidates from THREE sources, in order:

  1. bridge_gaps[] (Q5 structured answers) — one proposal per entry.
  2. Free-text Q6 answer — try to map to a structured proposal; if it doesn't fit cleanly, write a proposal_type: needs-triage proposal.
  3. Touched files during this taskgit log --diff-filter=AM --name-only in the relevant repos since task created date. If any file changed in this Bridge repo (skills/, protocols/, rules/, docs/) that wasn't a planned edit, flag as potential trigger-or-routing miss for the postmortem.

For each candidate, write one file to:

work/_learning/proposals/<YYYY-MM-DD>-<task-slug>-<topic-slug>.md

Following the schema in references/_schema.proposal.yaml.

Naming rule: <topic-slug> is the gap-id from bridge_gaps[] if structured, or a 3-4-word kebab-case summary if from free-text. Disambiguate collisions with a -2, -3 suffix.

Proposal-writing rules

Use the template in references/proposal-writing.md.

Default severity: P2 for postmortem-sourced proposals. P0/P1 only when the gap is in an actively-used path (existing skill, common standing-order) AND the user explicitly described impact.

Default scope: user for postmortem-sourced proposals unless the target is clearly a CORE file (a generic skill, a CORE standing-order, the schema). The /bridge-learn skill (Phase 2) and /bridge-sync handle promotion to your org overlay / open-bridge later — getting the scope right at proposal-write time saves an audit later.

Default status: pending. Never write accepted or implemented from this skill — those are /bridge-learn states.

Output to user

After all phases complete, return a single block:

✅ Task <slug> postmortem complete.
   <X> answers captured (frontmatter + body)
   <N> proposals written to work/_learning/proposals/
     • <file-1>  [<severity>] <one-line summary>
     • <file-2>  [<severity>] <one-line summary>
   → review per /bridge-learn (Phase 2) — or open the files directly.

If all six questions skipped:

✅ Postmortem skipped — STATUS.md unchanged.

Hand control back to task-sync.md Phase 3c (3-step move).

Edge cases

  • Task has no context: field → skip context.yaml read, proceed.
  • Task has no mandant: field → no impact on postmortem.
  • STATUS.md is malformed → log warning, ask user to fix, exit gracefully (do not mv files yet).
  • Skip-phrase ambiguity ("no" could mean "no, nothing" or "no I'll answer in a moment"): treat as skip; user can backfill manually.
  • User says "wait" / "hold on" / "stop" mid-flow → suspend, do NOT write partial frontmatter, hand control back. User can resume by saying "continue postmortem" / "postmortem continue".
  • Proposals folder doesn't exist → create on first write (mkdir -p work/_learning/proposals/).
  • Bridge-config.yaml not present → assume defaults (postmortem enabled, skip_phrases as above, cutdown_after_skips=3).

Testing the skill

Two ways to dry-run without closing a real task:

  1. Manual mode — say "reflect on the last hour", skill runs without binding to a STATUS.md, just emits a sample proposal-set.
  2. Test fixturework/_learning/_test/sample-task/STATUS.md (create on demand) — skill runs against the fixture, writes proposals to work/_learning/_test/proposals/, asserts schema validity.

What this skill deliberately does NOT do

  • ❌ Mutate any file outside work/tasks/<slug>/STATUS.md and work/_learning/proposals/. The 3-step move is done by task-sync.md Phase 3c, not here.
  • ❌ Auto-apply any proposal. Every proposal-file is status: pending — accept/reject is the /bridge-learn skill's job.
  • ❌ Probe other repositories (customer-x, partner-project, ...). Only this Bridge repo
    • git-stats for the task duration period.
  • ❌ Write to MEMORY.md. The auto-memory system is separate; a postmortem may suggest a memory entry via bridge_gaps[].memory: but the actual write happens later, human-approved.
  • ❌ Decide when proposals get implemented. That's /bridge-learn.
  • ❌ Run if bridge-config.yaml.learning.postmortem.enabled: false.

Related

  • protocols/standing-orders/task-sync.md § Phase 3b (invokes this skill)
  • work/templates/_schema.status.yaml (schema for the frontmatter fields)
  • work/templates/STATUS.md (template ## Postmortem section)
  • work/_learning/README.md (the aggregation layer this writes into)
  • skills/bridge-learn/SKILL.md (Phase 2 — reviews proposals)
  • bridge-config.yaml.learning.postmortem (config block)
  • CLAUDE.md § Auto Memory (the parallel system this does NOT touch)

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