release-doc

name	release-doc
description	[Documentation] Use when you need to generate a detailed, AI-analyzed release document from git history over a time range or custom prompt.

Codex compatibility note:

• Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.
• Prefer the plan-hard skill for planning guidance in this Codex mirror.
• Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.
• User-question prompts mean to ask the user directly in Codex.
• Ignore Claude-specific mode-switch instructions when they appear.
• Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.
• Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.
• Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.
• For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.
• If a required step/tool cannot run in this environment, stop and ask the user before adapting.

Codex Project-Reference Loading (No Hooks)

Codex does not receive Claude hook-based doc injection. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec/test-case planning or TC mapping: feature-docs-reference.md
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

Quick Summary

Goal: Generate a detailed, AI-analyzed release document from git history — by time range (e.g., last 30 days) or custom comparison (e.g., v1.0.0..HEAD) or a user-described focus area.

Workflow:

1. Resolve Range — Determine the git range from user input
2. Dump Artifacts — Save log, file-status, and full diff to docs/release/ BEFORE analyzing
3. Categorize Changes — Group changed files by framework area (hooks, skills, agents, workflows, principles, config, docs)
4. Read Key Diffs — For each category, read the most significant changes via git show or git diff
5. Generate Doc — Write structured markdown release doc to docs/release/
6. Validate — Verify completeness and accuracy against the artifact files

Key Rules:

• Dump first, read second — NEVER analyze a diff you haven't saved to a file first
• Group by theme — Do not list commits chronologically; group by what area they impact
• Cite evidence — Every section claim must reference a specific commit hash or file path
• Custom focus honored — If user provides a focus prompt, weight that area more deeply
• Draft status — All generated docs are Draft; add "Status: Draft" to the header

---

Release Doc Skill

Generate a detailed, narrative release document by analyzing git history over a time range or between two refs.

Invocation

$release-doc [--days N] [--since DATE] [--range base..head] [--focus "custom prompt"] [--output path]

Examples:

# Last 30 days
$release-doc --days 30

# Since a specific date
$release-doc --since 2026-03-15

# Between two tags or commits
$release-doc --range v1.0.0..HEAD

# With custom focus area
$release-doc --days 30 --focus "what changed in hooks and workflow enforcement"

# Specify output file
$release-doc --days 30 --output docs/release/release-2026-Q1.md

Differences from $release-notes and $changelog

Feature	$release-doc	$release-notes	$changelog
Time-based ranges	✅ --days N / --since	❌ ref-to-ref only	❌ PR/commit only
AI thematic analysis	✅ Groups by framework area	❌ Commit-type categories	❌ File-by-file
Dumps artifacts to files	✅ Mandatory before analysis	❌ Pipes in memory	❌ In memory
Custom focus prompt	✅ --focus "..."	❌	❌
Narrative sections	✅ Context + rationale	❌ Bullet list only	❌ Bullet list only
Framework-level docs	✅ hooks/skills/agents	❌ App features	❌ App features

Step 1: Resolve Range

Determine the git range from the user's input:

# Time-based (--days N or --since DATE)
SINCE_DATE=$(date -d "-30 days" +%Y-%m-%d)    # Linux
SINCE_DATE=$(date -v-30d +%Y-%m-%d)            # macOS
git log --since="$SINCE_DATE" --oneline --format="%H %ad %s" --date=short

# Ref-based (--range base..head)
git log v1.0.0..HEAD --oneline --format="%H %ad %s" --date=short

# Count commits in range
git log --since="$SINCE_DATE" --oneline | wc -l

Identify the boundary commits:

# Oldest commit in range (for diff base)
OLDEST=$(git log --since="$SINCE_DATE" --format="%H" | tail -1)
# Newest
NEWEST=HEAD

Step 2: Dump Git Artifacts (MANDATORY BEFORE ANALYSIS)

CRITICAL: Run ALL dumps before reading ANY content. Use background runs for large diffs.

# Create output directory
mkdir -p docs/release

# 1. Full git log with bodies
git log --since="$SINCE_DATE" --format="%H %ad %s%n%b" --date=short \
  > docs/release/git-log-{PERIOD}.txt

# 2. File-level change status (A/M/D)
git diff ${OLDEST}^..HEAD --name-status \
  > docs/release/diff-file-status-{PERIOD}.txt

# 3. Diff stat summary (line counts)
git diff ${OLDEST}^..HEAD --stat \
  > docs/release/diff-stat-{PERIOD}.txt

# 4. Full consolidated diff (background — may be large)
git diff ${OLDEST}^..HEAD \
  > docs/release/git-diff-{PERIOD}-full.txt &

echo "Artifacts saved. Commit count: $(cat docs/release/git-log-{PERIOD}.txt | grep -c '^[a-f0-9]\{40\}')"

Replace {PERIOD} with a human-readable period string, e.g., 30d, 2026-03-15-to-2026-04-14.

Verify all artifact files exist and are non-empty before proceeding.

Step 3: Categorize Changes by Framework Area

Read docs/release/diff-file-status-{PERIOD}.txt and group files into categories:

# Count by area
grep -c "^[AMD]\s*.claude/hooks/" docs/release/diff-file-status-{PERIOD}.txt
grep -c "^[AMD]\s*.claude/skills/" docs/release/diff-file-status-{PERIOD}.txt
grep -c "^[AMD]\s*.claude/agents/" docs/release/diff-file-status-{PERIOD}.txt
grep -c "^[AMD]\s*.claude/workflows" docs/release/diff-file-status-{PERIOD}.txt
grep -c "^[AMD]\s*.claude/docs/" docs/release/diff-file-status-{PERIOD}.txt
grep -c "^[AMD]\s*docs/" docs/release/diff-file-status-{PERIOD}.txt
grep -c "^[AMD]\s*CLAUDE.md" docs/release/diff-file-status-{PERIOD}.txt

Standard category map for easy-claude projects:

File Path Pattern	Category
.claude/hooks/**	Hook Enhancements
.claude/hooks/lib/**	Hook Library
.claude/skills/**	Skills
.claude/agents/**	Agent Definitions
.claude/workflows/**	Workflow Orchestration
.claude/workflows.json	Workflow Registry
.claude/docs/**	Framework Documentation
.claude/scripts/**	Tooling & Scripts
docs/project-reference/**	Project Reference Docs
CLAUDE.md	Principles & Core Rules
.claude/.ck.json / settings.json	Configuration

For non-easy-claude projects, derive categories from the file path patterns actually present.

Step 4: Analyze Key Changes Per Category

For each category with significant changes (>5 files or >200 lines), read representative diffs:

# Most impactful commits (by files changed)
git log --since="$SINCE_DATE" --format="%H %s" --name-only | \
  grep -A100 "^[a-f0-9]\{40\}" | head -200

# Show specific commit detail
git show {COMMIT_HASH} --stat --format="%s%n%b"

# Diff for a specific file across the range
git diff ${OLDEST}^..HEAD -- .claude/hooks/init-prompt-gate.cjs

Analysis questions for each category:

• Hooks: What new gates or enforcement were added? What context injection changed? What was the trigger behavior before vs after?
• Skills: What new skills were created? What protocols were updated in existing skills? What was removed or merged?
• Agents: What agent definitions changed? Did tool lists or dispatch rules change?
• Workflows: What workflow steps were added/removed? Did sequence order change? Were any workflows merged or deleted?
• Principles: What rules in CLAUDE.md changed? Were confidence thresholds tightened? New hard gates added?
• Config: What new schema fields? What validation was added?
• Scripts/Tooling: What new utilities? What improved or automated?

Evidence requirement: For every claim in the doc, record {commit_hash}:{file_path} as your source.

Step 5: Handle Custom Focus Prompt

If user provided --focus "...", apply additional depth to that area:

1. Grep all changed files matching the focus keywords
2. Read the full diff for matching files (not just stat)
3. Include a dedicated top-level section for the focus area in the output doc
4. Cross-reference related changes in other areas (e.g., a new skill + its hook + its workflow entry)

Step 6: Generate the Release Doc

Write to docs/release/release-notes-{PERIOD}.md (or --output path).

Required structure:

# Release Notes — {Project Name}

**Period:** {START} → {END}
**Commits:** {N} commits | **Files changed:** {N} | **Insertions:** +{N} | **Deletions:** −{N}
**Status:** Draft

---

## Executive Summary

3-4 sentences. The most transformative changes, their business/developer impact, and the overall trajectory.

---

## {Category 1}: {Theme Name}

### What Changed

{Narrative description — not bullet-list of commits}

### Why It Matters

{Impact on how developers/AI uses the system}

### Key Additions / Modifications

| Item | Type | Effect |
| ---- | ---- | ------ |

---

## {Category 2}: ...

[repeat for each significant category]

---

## New Skills Added

| Skill | Command | Purpose |
| ----- | ------- | ------- |

## Skills Removed or Merged

| Skill | Reason |
| ----- | ------ |

## Principles & Rules Updated

| Rule | Before | After | Reason |
| ---- | ------ | ----- | ------ |

---

## Summary Statistics

| Category       | Count |
| -------------- | ----- |
| Commits        | {N}   |
| Files changed  | {N}   |
| New skills     | {N}   |
| Skills removed | {N}   |
| New hooks      | {N}   |
| Hooks modified | {N}   |
| Agents updated | {N}   |
| Net lines      | +{N}  |

---

_Generated: {DATE} | Branch: {BRANCH} | Range: {OLDEST_HASH}..{HEAD_HASH}_
_Artifacts: `docs/release/git-log-{PERIOD}.txt`, `docs/release/diff-file-status-{PERIOD}.txt`_

Step 7: Validate

After writing, verify:

• Every category section references at least one commit hash
• "New Skills" table is complete (cross-check against grep "^A.*skills" diff-file-status-*.txt)
• "Skills Removed" is complete (cross-check against grep "^D.*skills" diff-file-status-*.txt)
• Summary Statistics match the actual diff stat
• No section says "TODO" or contains unfilled template placeholders
• Artifact files are listed in the doc footer

Configuration: Category Map Override

For projects with custom directory structures, override the category map via project-config.json:

{
    "releaseDoc": {
        "categoryMap": {
            "src/api/**": "API Layer",
            "src/ui/**": "Frontend",
            "migrations/**": "Database Schema"
        },
        "outputDir": "docs/release",
        "focusAreas": ["hooks", "skills", "agents"]
    }
}

Integration with Other Skills

• $release-notes — Use after $release-doc to generate a consumer-facing version (tag-to-tag, conventional commits)
• $changelog — Use for individual feature changelog entries; $release-doc is for multi-week summaries
• $graph-blast-radius — Run before release to assess impact of the most changed files
• $docs-update — Update project reference docs after analyzing what changed
• $commit — Commit the generated release doc

Troubleshooting

Diff too large for context

Solution: The skill requires artifact files be written first — never read the full diff into context. Use git show {hash} for individual commits and grep -l to narrow file scope.

Time range yields 0 commits

# Verify date format (ISO 8601)
git log --since="2026-03-15" --oneline | head -5
# If empty, check git's date interpretation:
git log --format="%ad" --date=short | head -5

Non-easy-claude project structure

The skill auto-derives categories from file paths. For projects without .claude/, group by src/, tests/, docs/, scripts/, config/ instead.

---

Workflow Recommendation

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS: If you are NOT already in a workflow, use a direct user question to ask the user:

1. Execute $release-doc directly (Recommended) — Standalone analysis and doc generation
2. Activate workflow-release-prep — Full pre-release quality gate + release doc

---

Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, use a direct user question to present:

• "$release-notes (Recommended)" — Generate consumer-facing release notes from the same range
• "$commit" — Commit the generated release doc to version control
• "$docs-update" — Sync project reference docs with any changes discovered during analysis
• "Skip, done" — User decides

---

[IMPORTANT] Use task tracking to break ALL work into small tasks BEFORE starting. This prevents context loss during large diff analysis. Always dump git artifacts to external files before reading.

External Memory: Write ALL intermediate findings and git artifacts to docs/release/ — this is MANDATORY. Large diffs will overflow context. Never try to hold a 30-day diff in memory.

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

IMPORTANT MUST ATTENTION dump ALL git artifacts to docs/release/ BEFORE reading any diff content IMPORTANT MUST ATTENTION break work into small todo tasks using task tracking BEFORE starting IMPORTANT MUST ATTENTION cite commit hash + file path for every claim in the generated doc IMPORTANT MUST ATTENTION add a final review task to validate completeness against artifact files

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using task tracking.

Hookless Prompt Protocol Mirror (Auto-Synced)

Source: .claude/hooks/lib/prompt-injections.cjs + .claude/.ck.json

[WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason.

1. DETECT: Match prompt against workflow catalog
2. ANALYZE: Find best-match workflow AND evaluate if a custom step combination would fit better
3. ASK (REQUIRED FORMAT): Use a direct user question with this structure:
   • Question: "Which workflow do you want to activate?"
   • Option 1: "Activate [BestMatch Workflow] (Recommended)"
   • Option 2: "Activate custom workflow: [step1 → step2 → ...]" (include one-line rationale)
4. ACTIVATE (if confirmed): Call $workflow-start <workflowId> for standard; sequence custom steps manually
5. CREATE TASKS: task tracking for ALL workflow steps
6. EXECUTE: Follow each step in sequence [CRITICAL-THINKING-MINDSET] Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination principle: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. AI Attention principle (Primacy-Recency): Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows.

Learned Lessons

Lessons Learned

[CRITICAL] Hard-won project debugging/architecture rules. MUST ATTENTION apply BEFORE forming hypothesis or writing code.

Quick Summary

Goal: Prevent recurrence of known failure patterns — debugging, architecture, naming, AI orchestration, environment.

Top Rules (apply always):

• MUST ATTENTION verify ALL preconditions (config, env, DB names, DI regs) BEFORE code-layer hypothesis
• MUST ATTENTION fix responsible layer — NEVER patch symptom sites with caller-specific defensive code
• MUST ATTENTION use ExecuteInjectScopedAsync for parallel async + repo/UoW — NEVER ExecuteUowTask
• MUST ATTENTION name by PURPOSE not CONTENT — adding member forces rename = abstraction broken
• MUST ATTENTION persist sub-agent findings incrementally after each file — NEVER batch at end
• MUST ATTENTION Windows bash: verify Python alias (where python/where py) — NEVER assume python/python3 resolves

---

Debugging & Root Cause Reasoning

• [2026-04-11] Holistic-first: verify environment before code. Failure → list ALL preconditions (config, env vars, DB names, endpoints, DI regs, credentials, permissions, data prerequisites) → verify each via evidence (grep/cat/query) BEFORE code-layer hypothesis. Worst rabbit holes: diving nearest layer while bug sits elsewhere — e.g., hours debugging "sync timeout", real cause: test appsettings pointing wrong DB. Cheapest check first.
• [2026-04-01] Ask "whose responsibility?" before fixing. Trace: bug in caller (wrong data) or callee (wrong handling)? Fix responsible layer — NEVER patch symptom site masking real issue.
• [2026-04-01] Trace data lifecycle, not error site. Follow data: creation → transformation → consumption. Bug usually where data created wrong, not consumed.
• [2026-04-01] Code is caller-agnostic. Functions/handlers/consumers don't know who invokes them. Comments/guards/messages describe business intent — NEVER reference specific callers (tests, seeders, scripts).

Architecture Invariants

• [2026-03-31] ParallelAsync + repo/UoW MUST use ExecuteInjectScopedAsync, NEVER ExecuteUowTask. ExecuteUowTask creates new UoW but reuses outer DI scope (same DbContext) — parallel iterations sharing non-thread-safe DbContext silently corrupt data. ExecuteInjectScopedAsync creates new UoW + new DI scope (fresh repo per iteration).
• [2026-03-31] Bus message naming MUST include service name prefix — core services NEVER consume feature events. Prefix declares schema ownership (AccountUserEntityEventBusMessage = Accounts owns). Core services (Accounts, Communication) are leaders. Feature services (Growth, Talents) sending to core MUST use {CoreServiceName}...RequestBusMessage — never define own event for core to consume.

Naming & Abstraction

• [2026-04-12] Name PURPOSE not CONTENT — "OrXxx" anti-pattern. HrManagerOrHrOrPayrollHrOperationsPolicy names set members, not what it guards. Add role → rename = broken abstraction. Rule: names express DOES/GUARDS, not CONTAINS. Test: adding/removing member forces rename? YES = content-driven = bad → rename to purpose (e.g., HrOperationsAccessPolicy). Nuance: "Or" fine in behavioral idioms (FirstOrDefault, SuccessOrThrow) — expresses HAPPENS, not membership.

Environment & Tooling

• [2026-04-20] Windows bash: NEVER assume python/python3 resolves — verify alias first. Python may not be in bash PATH under those names. Check: where python / where py. Prefer py (Windows Python Launcher) for one-liners, node if JS alternative exists.

Test-specific lessons → docs/project-reference/integration-test-reference.md Lessons Learned section. Production-code anti-patterns → docs/project-reference/backend-patterns-reference.md Anti-Patterns section. Generic debugging/refactoring reminders → System Lessons in .claude/hooks/lib/prompt-injections.cjs.

---

Closing Reminders

• IMPORTANT MUST ATTENTION holistic-first: verify ALL preconditions (config, env, DB names, endpoints, DI regs) BEFORE code-layer hypothesis — cheapest check first
• IMPORTANT MUST ATTENTION fix responsible layer — NEVER patch symptom site; trace caller (wrong data) vs callee (wrong handling), fix root owner
• IMPORTANT MUST ATTENTION parallel async + repo/UoW → ALWAYS ExecuteInjectScopedAsync, NEVER ExecuteUowTask (shared DbContext = silent data corruption)
• IMPORTANT MUST ATTENTION bus message prefix = schema ownership; feature services NEVER define events for core services — use {CoreServiceName}...RequestBusMessage
• IMPORTANT MUST ATTENTION name by PURPOSE — adding/removing member forces rename = broken abstraction
• IMPORTANT MUST ATTENTION sub-agents MUST write findings after each file/section — NEVER batch all findings into one final write
• IMPORTANT MUST ATTENTION Windows bash: NEVER assume python/python3 resolves — run where python/where py first, use py launcher or node

[LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip.

Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".

Extract lessons — ROOT CAUSE ONLY, not symptom fixes:

1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value".
2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up.
3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase.
4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson.
5. Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip $learn.
6. Auto-fix gate: "Could $code-review/$code-simplifier/$security/$lint catch this?" — Yes → improve review skill instead.
7. BOTH gates pass → ask user to run $learn. [TASK-PLANNING] [MANDATORY] BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes.