archive
Phase 3: merge spec/design deltas, code review, atomic commits, push, and trigger self-evolution
Skill by zxdxjtu
Chalk Labs
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About
Use cases: design
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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codeload.github.com· found in install command
Files it touches
~/.claude/skills/archive
What's inside
- Skill name
archive- Description
- Phase 3: merge spec/design deltas, code review, atomic commits, push, and trigger self-evolution
- License
- MIT
- Instructions
- 149 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Archive — Merge, Review, Commit & Evolve
You are finalizing a completed feature: merging incremental specs back into the full documents, running a final code review, making clean commits, and triggering self-evolution.
**Parameter**: $ARGUMENTS — feature ID (e.g. F001)
## Step 1: Verify Prerequisites
```bash
cat .harness/evidence/${FEATURE_ID}/verdict.md 2>/dev/null
```
The feature must be verified (verdict = PASS) before archiving. If not verified → suggest running `/verify` first.
## Step 2: Merge Spec & Design Deltas
### 2.1 Merge Spec Delta into Full Spec
Read `.harness/specs/{FXXX}-*.md` (the incremental spec).
Read `.harness/full-spec.md` (the full project spec, if exists).
Merge the feature spec into the full spec:
- Add the feature to the "Existing Features" section
- Update "Module Inventory" if new modules were created
- Update "Architecture Summary" if architecture changed
- Preserve all existing content, only ADD the new feature
If conflicts detected (e.g., feature contradicts existing spec), present to user for resolution.
### 2.2 Merge Design Delta into Full Design
Read `.harness/designs/{FXXX}-*.md` (if exists).
Read `.harness/full-design.md` (if exists).
Merge similarly: add new components, update dependency graph, add new data models.
## Step 3: Final Code Review
Launch a comprehensive code review sub-agent:
```
Agent(subagent_type: "code-reviewer", run_in_background: true,
prompt: "Final code review for feature {FXXX}.
Review ALL files changed for this feature:
git diff {base_commit}..HEAD -- {files from tasks.md}
Check:
1. Code quality: naming, readability, complexity
2. Error handling: no swallowed errors, proper messages
3. Security: no hardcoded secrets, input validation
4. Immutability: no mutation of shared state
5. Style consistency: matches project conventions
Report: CRITICAL / HIGH / MEDIUM issues only.
Ignore cosmetic issues.")
```
Read the review. If CRITICAL issues → fix before proceeding. HIGH issues → fix or acknowledge.
## Step 4: Style Unification
If a lint/format command is configured:
```bash
{lint_command} --fix 2>&1
{format_command} 2>&1
```
Commit style fixes separately: `chore(style): unify code style for {FXXX}`
## Step 5: Atomic Commit Splitting
Review the git history for this feature. If commits are messy or mixed:
1. Identify logical units of change
2. Suggest splitting into clean, atomic commits:
- One commit per logical unit (e.g., "add auth middleware", "add login endpoint", "add login tests")
- Each commit should build and pass tests independently
Present the commit plan to user:
> "当前有 {N} 个 commits。建议整理为 {M} 个原子 commits: {list}。是否同意?"
If user agrees, execute interactive rebase (only if user explicitly approves).
## Step 6: Push & MR
```bash
git push origin {current_branch}
```
Ask user:
> "代码已推送。是否需要创建 MR/PR?"
If yes:
```bash
gh pr create --title "feat({FXXX}): {feature name}" --body "$(cat <<'EOF'
## Summary
{feature description}
## Changes
{list of key changes}
## Test Evidence
- V1 (Unit): ✅ {pass count}/{total}
- V2 (Integration): ✅ {pass count}/{total}
- V3 (E2E): ✅ {pass count}/{total}
- Evaluation Score: {score}/10
## Evidence
See `.harness/evidence/{FXXX}/` for full reports.
EOF
)"
```
## Step 7: Update Evolution Data
Record this iteration for self-evolution analysis:
Append to `.harness/evolution/memory.jsonl`:From zxdxjtu/harness, MIT.
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Signals
- Stars
- 8
- Forks
- 3
- Open issues
- 1
- Last commit (this folder)
- Mar 28, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/zxdxjtu/harness
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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- 0.466score
evaluate
zxdxjtu
Adversarial evaluation: compare dev product against reference baseline using Playwright MCP
SkillDFreshness: D★ 8Claude Code +9 - 0.466score
harness-init
zxdxjtu
Initialize Harness for your project — learn repo, team norms, generate customized framework
SkillDFreshness: D★ 8Claude Code +9 - 0.466score
eval-fix
zxdxjtu
Adversarial fix loop: read eval report → fix gaps → re-evaluate → repeat until convergence
SkillDFreshness: D★ 8Claude Code +9 - 0.466score
entropy-clean
zxdxjtu
Post-wave entropy cleanup — remove debug artifacts, enforce style, ensure git hygiene
SkillDFreshness: D★ 8Claude Code +9 - 0.466score
baseline
zxdxjtu
Capture baseline of a reference product using Playwright MCP for clone/replicate scenarios
SkillDFreshness: D★ 8Claude Code +9 - 0.466score
harness-status
zxdxjtu
Restore state, health check, determine current phase, suggest next step
SkillDFreshness: D★ 8Claude Code +9
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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archive skill. Agent Mart. https://agentmart.dev/skills/zxdxjtu-archive (last updated 2026-10-24)