home/dot_config/exact_agents/skills/worklog-manager/SKILL.md
Manage Codex worklog files under `.agents/worklog/codex`, hard-gate stale learnings through `learn_index.md`, and audit learn metadata deterministically. Use when a Codex agent or user needs to bootstrap worklog context, maintain plan/todo/learn files, or validate stale learn state before trusting prior session knowledge.
npx skillsauth add shunk031/dotfiles worklog-managerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill to manage .agents/worklog/codex/** for Codex sessions.
It keeps startup context constrained to valid learn entries, maintains plan/todo/learn metadata, and audits stale learn state deterministically.
.agents/worklog/codex/{plan,todo,learn} for a non-trivial Codex task..agents/worklog/codex/**. If the request needs repo edits, GitHub operations, or product decisions, hand that back to the parent agent..agents/worklog/codex/learn/learn_index.md.
.agents/worklog/codex/plan/, todo/, and learn/ exist.learn_index.md does not exist yet, skip the startup audit and continue with empty learn context.learn_index.md exists, run python3 ~/.agents/skills/worklog-manager/scripts/codex_worklog_audit.py check before reading any learn entry.python3 home/dot_config/exact_agents/skills/worklog-manager/scripts/codex_worklog_audit.py check.check fails, stop startup and report the exact audit failures to the parent. Do not continue with best-effort learn selection.## Active as the only startup source of truth.## Needs Review as context candidates, not facts.## Superseded and ## Archived unless the parent explicitly asks for history or migration context.Active learnings: only active entries with freshness: stable.Needs revalidation: every needs_review entry plus any active entry with freshness: drift_prone.Ignored historical entries: relevant superseded or archived entries that were intentionally skipped.type, id, owner, created_at, updated_at.plan key: status.todo keys: status, workstream, related_plan.learn keys: validated, apply_to, status, freshness, last_validated_at.todo.status within active | blocked | done | superseded.plan.status within draft | active | done | superseded.User Prompt, Goal, Scope, Assumptions, Design, Tests, Open Questions.TODO, Done.Date, Learnings, Plan Updates.status must be one of active | needs_review | superseded | archived.freshness must be one of stable | drift_prone.freshness: drift_prone requires review_after.status: superseded requires superseded_by.supersedes.learn_index.md must contain exactly these sections: ## Active, ## Needs Review, ## Superseded, ## Archived.- [Title](file.md) [stable|drift_prone] — SummaryAssumptions, Design, or Tests sections to match.Use this flow only when a later user direction conflicts with the current session facts.
For this workflow, startup facts means only the learn entries listed under the startup summary Active learnings.
Needs revalidation, ## Needs Review, and any active learn with freshness: drift_prone are context only and are not startup facts.
The conflict detection scope is limited to:
startup factsAssumptionsWhen a later user message conflicts with one of those sources:
CONFLICT_REPORT to the parent.CONFIRM_OVERRIDE, REJECT_OVERRIDE, or NEEDS_USER_CLARIFICATION.CONFIRM_OVERRIDE.Plan Updates to note that it is a corpus migration candidate only after revalidation evidence exists.The audit validates corpus integrity, not parent confirmation flow.
Use these parent-facing message contracts:
CONFLICT_REPORT
source_type: startup_fact|plan_assumption|todo
source_ref: <learn filename | plan section | todo line>
old_statement: <current assumption>
user_request: <new direction>
rationale: <why this is a direction change instead of a minor refinement>
proposed_session_action: ignore_for_session|rewrite_plan_todo
learn_update: pending_revalidation
CONFIRM_OVERRIDE
source_ref: <same value>
approved_action: rewrite_plan_todo
REJECT_OVERRIDE
source_ref: <same value>
keep_existing_assumption: true
NEEDS_USER_CLARIFICATION
source_ref: <same value>
clarification_question: <short question>
Do not write .agents/worklog/codex/** before confirmation.
After CONFIRM_OVERRIDE, rewrite .agents/worklog/codex/** with these rules:
User Prompt update: append the user message that changed direction.Assumptions note: keep the old assumption, but annotate it with Superseded in this session by user direction on YYYY-MM-DD.Design update: add the new direction.Open Questions revalidation note: add one line when persistent learn revalidation is still needed.TODO rewrite: move unfinished items that depend on the old assumption to # Done, mark the individual line as superseded after the confirmed direction change, do not replace them with the literal line [x] Superseded by confirmed direction change, and add replacement work under # TODO.todo.status as active because the session is still in progress.If the parent responds with REJECT_OVERRIDE, keep plan/todo unchanged and tell the parent existing assumption kept.
If the parent responds with NEEDS_USER_CLARIFICATION, keep plan/todo unchanged and wait for the parent's clarification flow.
freshness: drift_prone and set an explicit review_after.default branch is master must not stay active; move it to superseded.origin/master should move to needs_review until it is revalidated against the current main workflow.check is mandatory during startup whenever learn_index.md exists.
Use summary for manual inspection or for diagnosing a failed startup audit after the failure has already been reported to the parent.
python3 ~/.agents/skills/worklog-manager/scripts/codex_worklog_audit.py check
python3 ~/.agents/skills/worklog-manager/scripts/codex_worklog_audit.py summary
Use --learn-root <path> when you need to audit fixtures or a non-default corpus.
Use --now <ISO-8601> when you need deterministic review expiry checks in tests.
📝 まとめ:.scripts/codex_worklog_audit.py: deterministic audit helper for learn metadata, review expiry, supersession links, and index/file consistency.references/learn_rules.md: detailed learn metadata rules, targeted migration examples, and audit expectations.development
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