security-precheck: Security & Code Review for AI Agents | OpenAgentSkill

Overview

Self-run security pre-check ahead of an external security-team code audit. Runs the security-audit agent (plus SonarQube security hotspots when configured), grades findings P0/P1/P2, splits them into issues, and fixes them with parallel subagents. Use on "security check", "security audit prep", "code audit" requests.

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Security Pre-check (before an external audit)

Sweep the codebase with the same criteria an external security team would use, and fix findings ahead of time.

1. Scan (parallel)

Run concurrently:

Agent(subagent_type: "security-audit") — grep-based scan of the 12 P0 code items
  (hardcoded secrets, missing auth, PII logging, ...) + 8 agent-config items
  (.claude/ hooks, MCP, permissions, prompt injection)

# SonarQube security hotspots (TO_REVIEW only) — skip this step with a note if the
# project has no sonar-project.properties. Never hardcode the host or token:
# use $SONAR_HOST_URL / $SONAR_TOKEN from the environment.
if [ -f sonar-project.properties ]; then
  key=$(grep 'sonar.projectKey' sonar-project.properties | cut -d= -f2-)
  curl -s -u "${SONAR_TOKEN}:" \
    "${SONAR_HOST_URL}/api/hotspots/search?projectKey=$key&status=TO_REVIEW&ps=500" \
    | python3 -c "import sys,json; d=json.load(sys.stdin); print('TO_REVIEW:', len(d['hotspots'])); [print(h['ruleKey'], h['component'], h.get('line','')) for h in d['hotspots']]"
fi

The security-audit agent produces better results when its prompt names this project's concrete context (auth mechanism, session handling, CORS config, data-access layer, PII fields). Don't describe these from memory — at run time, grep the repo for its auth/session/CORS/data-access entry points and include what you actually find.

2. Grading + report

P0 (critical): escalate immediately. Hardcoded secrets, auth bypass, SQL injection, .env leaked into git, etc.
P1 (recommended fix): this skill's main target. Missing rate limits, missing cookie attributes, missing constant-time comparison, overly broad permission allows, PII logging, etc.
Pass: also list items that were checked and found clean (what was checked is the evidence of coverage).

Report as a table: P0 N / P1 N / pass N.

3. Issue registration (P1 and up, skip trivia)

Group findings by file/topic into one issue each — no issue-per-finding spam. Example: three findings in the same auth controller (rate limit, cookie attributes, constant-time comparison) become one issue.

# forge CLI per rules/forge.md
gh issue create -t "<title>" -b "<pre-check background + concrete findings + files>"   # GitHub
glab issue create -t "<title>" -d "<pre-check background + concrete findings + files>" -y  # GitLab

Local-settings fixes (.claude/settings.local.json allow-list trimming, MCP permission review, ...) are handled directly without an issue — local-scope config, not P1 workflow material.

4. Parallel fixing (model tiers)

Split issues by nature and invoke Agent concurrently. Issues touching the same file go to a single agent — splitting them causes concurrent-edit conflicts on that file.

Work type	subagent_type	model
Backend changes involving security judgment (auth/crypto/session)	sdlc-developer	opus
General implementation (logging/validation/config)	sdlc-developer	sonnet
Investigate-only review (keep if justified, fix if not)	general-purpose	haiku

Every Agent call needs isolation: "worktree" (prevents parallel edit conflicts). Tell each agent to create a branch and commit only — no push, no merge; the parent session gates merges sequentially (multiple worktrees hitting main concurrently is a race).

5. Sequential merge + close

As each agent completes:

For security/auth changes, read the diff yourself (constant-time comparison approach, session key choice, rate-limit scope, ... — if these are wrong, the pre-check was pointless)
git pull && git merge <branch> --no-edit
Re-run the project's build/test gates on the merged state (the stack gates in .claude/hooks/pre-commit.sh are the reference)
git push
git worktree remove <path> --force && git branch -d <branch>
Note + close the issue per the forge convention (rules/forge.md)

6. Memory record

Write .claude/memory/project_security-precheck.md with the date, finding counts, issue numbers handled, and accepted risks (e.g. rate-limit keying may be inaccurate behind a proxy; a specific MCP allow kept with rationale) — so the next pre-check does not re-litigate items already reviewed and consciously kept.

Learned warnings

Keying a rate limit/lockout on the raw client address alone (request.getRemoteAddr() or equivalent) collapses to the proxy IP behind a reverse proxy, turning it into a global lock — verify whether the deployment topology requires X-Forwarded-For parsing during review.
Worktrees start without installed dependencies (node_modules, venv, ...), so frontend/build gates can fail environmentally — for backend-only changes a symlink workaround is fine (never commit it); if the issue touches frontend code, tell the agent to run the package install (lockfile-frozen) in its worktree first.
MCP permissions (mcp__*) are granted per tool — "read-only only" granularity is not possible. If a tool is genuinely needed, don't force-remove it; record the rationale in memory and keep it.

View source ↗

File metadata

name: security-precheck
description: Self-run security pre-check ahead of an external security-team code audit. Runs the security-audit agent (plus SonarQube security hotspots when configured), grades findings P0/P1/P2, splits them into issues, and fixes them with parallel subagents. Use on "security check", "security audit prep", "code audit" requests.
user-invocable: true
allowed-tools: Bash, Agent, Read, Edit, Write

View original text

---
name: security-precheck
description: Self-run security pre-check ahead of an external security-team code audit. Runs the security-audit agent (plus SonarQube security hotspots when configured), grades findings P0/P1/P2, splits them into issues, and fixes them with parallel subagents. Use on "security check", "security audit prep", "code audit" requests.
user-invocable: true
allowed-tools: Bash, Agent, Read, Edit, Write
---

# Security Pre-check (before an external audit)

Sweep the codebase with the same criteria an external security team would use, and fix
findings ahead of time.

## 1. Scan (parallel)

Run concurrently:

```
Agent(subagent_type: "security-audit") — grep-based scan of the 12 P0 code items
  (hardcoded secrets, missing auth, PII logging, ...) + 8 agent-config items
  (.claude/ hooks, MCP, permissions, prompt injection)
```

```bash
# SonarQube security hotspots (TO_REVIEW only) — skip this step with a note if the
# project has no sonar-project.properties. Never hardcode the host or token:
# use $SONAR_HOST_URL / $SONAR_TOKEN from the environment.
if [ -f sonar-project.properties ]; then
  key=$(grep 'sonar.projectKey' sonar-project.properties | cut -d= -f2-)
  curl -s -u "${SONAR_TOKEN}:" \
    "${SONAR_HOST_URL}/api/hotspots/search?projectKey=$key&status=TO_REVIEW&ps=500" \
    | python3 -c "import sys,json; d=json.load(sys.stdin); print('TO_REVIEW:', len(d['hotspots'])); [print(h['ruleKey'], h['component'], h.get('line','')) for h in d['hotspots']]"
fi
```

The security-audit agent produces better results when its prompt names this project's
concrete context (auth mechanism, session handling, CORS config, data-access layer,
PII fields). Don't describe these from memory — at run time, grep the repo for its
auth/session/CORS/data-access entry points and include what you actually find.

## 2. Grading + report

- **P0 (critical)**: escalate immediately. Hardcoded secrets, auth bypass, SQL injection, `.env` leaked into git, etc.
- **P1 (recommended fix)**: this skill's main target. Missing rate limits, missing cookie attributes, missing constant-time comparison, overly broad permission allows, PII logging, etc.
- **Pass**: also list items that were checked and found clean (what was checked is the evidence of coverage).

Report as a table: `P0 N / P1 N / pass N`.

## 3. Issue registration (P1 and up, skip trivia)

Group findings by file/topic into one issue each — no issue-per-finding spam.
Example: three findings in the same auth controller (rate limit, cookie attributes,
constant-time comparison) become one issue.

```bash
# forge CLI per rules/forge.md
gh issue create -t "<title>" -b "<pre-check background + concrete findings + files>"   # GitHub
glab issue create -t "<title>" -d "<pre-check background + concrete findings + files>" -y  # GitLab
```

Local-settings fixes (`.claude/settings.local.json` allow-list trimming, MCP permission
review, ...) are handled directly without an issue — local-scope config, not P1 workflow
material.

## 4. Parallel fixing (model tiers)

Split issues by nature and invoke `Agent` concurrently. **Issues touching the same file
go to a single agent** — splitting them causes concurrent-edit conflicts on that file.

| Work type | subagent_type | model |
|---|---|---|
| Backend changes involving security judgment (auth/crypto/session) | sdlc-developer | opus |
| General implementation (logging/validation/config) | sdlc-developer | sonnet |
| Investigate-only review (keep if justified, fix if not) | general-purpose | haiku |

Every Agent call needs `isolation: "worktree"` (prevents parallel edit conflicts). Tell
each agent to create a branch and **commit only — no push, no merge**; the parent session
gates merges sequentially (multiple worktrees hitting main concurrently is a race).

## 5. Sequential merge + close

As each agent completes:

1. For security/auth changes, read the diff yourself (constant-time comparison approach, session key choice, rate-limit scope, ... — if these are wrong, the pre-check was pointless)
2. `git pull && git merge <branch> --no-edit`
3. Re-run the project's build/test gates on the merged state (the stack gates in `.claude/hooks/pre-commit.sh` are the reference)
4. `git push`
5. `git worktree remove <path> --force && git branch -d <branch>`
6. Note + close the issue per the forge convention (`rules/forge.md`)

## 6. Memory record

Write `.claude/memory/project_security-precheck.md` with the date, finding counts,
issue numbers handled, and **accepted risks** (e.g. rate-limit keying may be inaccurate
behind a proxy; a specific MCP allow kept with rationale) — so the next pre-check does
not re-litigate items already reviewed and consciously kept.

## Learned warnings

- Keying a rate limit/lockout on the raw client address alone (`request.getRemoteAddr()`
  or equivalent) collapses to the proxy IP behind a reverse proxy, turning it into a
  global lock — verify whether the deployment topology requires `X-Forwarded-For`
  parsing during review.
- Worktrees start without installed dependencies (`node_modules`, venv, ...), so
  frontend/build gates can fail environmentally — for backend-only changes a symlink
  workaround is fine (never commit it); if the issue touches frontend code, tell the
  agent to run the package install (lockfile-frozen) in its worktree first.
- MCP permissions (`mcp__*`) are granted per tool — "read-only only" granularity is not
  possible. If a tool is genuinely needed, don't force-remove it; record the rationale
  in memory and keep it.

Review the source

Source needs review

The tracked source changed or could not be synchronized. Review the current source before installing.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
The skill references external files (rules/forge.md, .claude/hooks/pre-commit.sh) that are not included in the skill directory, but they are part of the repository and expected to exist.
The skill assumes a specific environment (Claude Code with subagents, worktrees, gh/glab CLIs, curl, python3) without explicitly listing prerequisites.
Low GitHub adoption signal
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 25 GitHub stars
Stars/forks activity: 25 stars, 4 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access

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Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: LeeYudok/agents-scaffold
License: MIT
Version: Unknown
Last GitHub push: Aug 29, 2026
Registry updated: Sep 15, 2026
Instruction path: presets/lang-en/base/.claude/skills/security-precheck/SKILL.md @ 1b2f0348a508

Version reported in registry metadata; check source releases before relying on it.

Quality

60/100

Promising

Trust

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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Creator: LeeYudok
Source: LeeYudok/agents-scaffold
Indexed by: OpenAgentSkill community index

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