Chalk Labs
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Install
Works with Claude Code. Read the repository before you give any tool access to your data.
npx agentmarket install skill/sd0xdev-pre-pr-audit
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: testing, devops, security, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/pre-pr-audit
Tools it pre-approves 8
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
Read,Grep,Glob,Bash(git:*),Bash(bash:*),Skill,AskUserQuestion,Agent
What's inside
- Skill name
pre-pr-audit- Description
- Pre-PR confidence audit with 5-dimension scoring. Use when: final check before commit/push/PR, evaluating PR readiness, assessing test quality + risk + coverage holistically. Triggers: pre-pr, readiness check, confidence audit, final verification, ready to PR, how confident. Not for: code review (use codex-review-fast), post-deploy verification (use feature-verify), periodic health (use project-audit).
- License
- MIT
- Allowed tools
- Read,, Grep,, Glob,, Bash(git:*),, Bash(bash:*),, Skill,, AskUserQuestion,, Agent
- Instructions
- 192 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves some shell commands
Files (3)
- SKILL.md
- output-template.md · references/
- scoring-model.md · references/
SKILL.md (first lines)
# Pre-PR Audit
Pre-deploy ultimate verification. Aggregates test quality, coverage, risk, and AC traceability into a single confidence index (0-100).
## When NOT to Use
| Need | Use Instead |
|------|-------------|
| Code review | `/codex-review-fast` |
| Post-deploy runtime verification | `/feature-verify` |
| Periodic project health | `/project-audit` |
| Just run tests | `/verify` |
| Just check risk | `/risk-assess` |
## Positioning
```
auto-loop done → [user invokes] /pre-pr-audit → /smart-commit → /push-ci → /create-pr
↑
Pre-deploy ultimate verification
```
## Prohibited
```
❌ git add | git commit | git push — per @rules/git-workflow.md
```
This skill audits and reports. It does not modify code or commit.
## Arguments
| Arg | Description | Default |
|-----|-------------|---------|
| `--mode fast\|deep` | Execution depth | `fast` |
| `--strict` | Non-zero exit on ⛔ PR-Blocked | off |
| `--json` | Machine-readable JSON output | off |
| `--base <ref>` | Compare against ref | HEAD |
## Workflow
```mermaid
sequenceDiagram
participant U as User
participant PA as /pre-pr-audit
participant RA as /risk-assess
participant TR as /codex-test-review
participant CC as /check-coverage
participant ST as State / Artifacts
U->>PA: /pre-pr-audit [--mode fast|deep]
par Phase A: Collect
PA->>ST: [Background Agent] Read precommit/verify state (freshness)
PA->>RA: [Foreground — blocking] /risk-assess --mode fast
PA->>PA: [Background Agent] Detect changed files + map to tests
end
Note over PA,RA: A2 (/risk-assess) must complete before Phase B — Module Selection depends on top_affected
par Phase B: Targeted
PA->>TR: [Foreground] /codex-test-review (top-N risky modules)
PA->>CC: [Background Agent: coverage-analyst] /check-coverage (deep mode only)
PA->>PA: [Background Agent] AC trace (if request doc exists)
end
PA->>PA: Phase C: Aggregate + hard-fail + gate
PA->>U: Phase D: Report + confidence index
```
### Phase A: Collect (parallel with dispatch annotations)
| Step | Dispatch | Action | Source |
|------|----------|--------|--------|
| A1 | Background Agent | Read precommit gate state | `node scripts/review-state.js check --format=json`(installed copy first: `.claude/scripts/review-state.js`)— `precommit.passed` is content-addressed, so no separate freshness check; checker absent → report "no verdict source", never a pass |
| A2 | **Foreground** (blocking) | Invoke `/risk-assess --mode fast` | Skill tool — get risk_level, top_affected, overall_score |
| A3 | Background Agent | Detect changed files + map to test files | `git diff --name-only HEAD` → match against `test/` patterns |
**A2 MUST stay foreground**: Phase B Module Selection depends on `top_affected` from `/risk-assess` output. A1 and A3 dispatch as background Agents and run in parallel with A2.
### Phase B: Targeted (parallel, mode-dependent, with dispatch annotations)
| Step | Dispatch | fast | deep | Action |
|------|----------|------|------|--------|
| B1 | Foreground | top-3 | top-10 + supplement | `/codex-test-review` on selected modules (see Module Selection) |
| B2 | Background Agent (`coverage-analyst`) | skip | ✅ | `/check-coverage` for pyramid balance |
| B3 | Background Agent | skip | ✅ (if request doc) | AC trace: parse `## Acceptance Criteria` → map to test evidence |
**B2 uses `coverage-analyst` agent** (`agents/coverage-analyst.md`) for background execution. B3 dispatches as a background Agent for AC parsing. B1 stays foreground as the primary assessment.
### Module Selection (deterministic)
1. Source: `/risk-assess` JSON `top_affected` array (each: `file` + `dependent_count`)
2. Sort: `dependent_count` descending, tie-break `file` ascending (stable sort)
3. Select: N=3 (`fast`) or N=10 (`deep`)
4. Deep supplement: `git diff --name-only` for files beyond top_affected cap
5. Fallback: if `/risk-assess` unavailable, `git diff --stat` sorted by lines-changed descending
### Phase C: Aggregate
1. Score each dimension per `references/scoring-model.md`
2. Apply evidence confidence cap
3. Check hard-fail overrides
4. Compute final index
### Phase D: Output
Output report per `references/output-template.md`. Include:
- Confidence index (0-100) + gate sentinel
- Per-dimension score table
- Hard-fail check results
- Findings (prioritized)
- Next actions
## 5 Dimensions
| # | Dimension | Weight | Checks |
|---|-----------|--------|--------|
| 1 | Execution Integrity | 25% | All tests pass, precommit passed, HEAD freshness, no flaky indicators |From sd0xdev/sd0x-harness, MIT.
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Signals
- Stars
- 194
- Forks
- 26
- Open issues
- 5
- Last commit (this folder)
- Sep 25, 2026 (1 month ago)
- Last release
- Oct 6, 2026 (25 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/sd0xdev/sd0x-harness
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
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.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
pre-pr-audit skill. Agent Mart. https://agentmart.dev/skills/sd0xdev-pre-pr-audit (last updated 2026-10-24)