Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.
日本語の概要は準備中です。原文の説明を表示しています。
Run Semgrep static analysis across a codebase, optionally using Semgrep Pro for cross-file taint analysis. Use when Semgrep or a static-analysis scan is requested; use security-review for a manual audit.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Run a Semgrep scan with automatic language detection, parallel execution via subagents when the host supports delegation (otherwise scan sequentially), and merged SARIF output.
--metrics=off — Semgrep sends telemetry by default; --config auto also phones home. Every semgrep command must include --metrics=off to prevent data leakage during security audits.semgrep-rule-creator skillsemgrep-rule-variant-creator skillAll scan results, SARIF files, and temporary data are stored in a single output directory.
OUTPUT_DIR../static_analysis_semgrep_1. If that already exists, increment to _2, _3, etc.In both cases, always create the directory with mkdir -p before writing any files.
# Resolve output directory
if [ -n "$USER_SPECIFIED_DIR" ]; then
OUTPUT_DIR="$USER_SPECIFIED_DIR"
else
BASE="static_analysis_semgrep"
N=1
while [ -e "${BASE}_${N}" ]; do
N=$((N + 1))
done
OUTPUT_DIR="${BASE}_${N}"
fi
mkdir -p "$OUTPUT_DIR/raw" "$OUTPUT_DIR/results"
The output directory is resolved once at the start of Step 1 and used throughout all subsequent steps.
$OUTPUT_DIR/
├── rulesets.txt # Approved rulesets (logged after Step 3)
├── raw/ # Per-scan raw output (unfiltered)
│ ├── python-python.json
│ ├── python-python.sarif
│ ├── python-django.json
│ ├── python-django.sarif
│ └── ...
└── results/ # Final merged output
└── results.sarif
Required: Semgrep CLI (semgrep --version). If not installed, see Semgrep installation docs.
Optional: Semgrep Pro — enables cross-file taint tracking, inter-procedural analysis, and additional languages (Apex, C#, Elixir). Check with:
semgrep --pro --validate --config p/default 2>/dev/null && echo "Pro available" || echo "OSS only"
Limitations: OSS mode cannot track data flow across files. Pro mode uses -j 1 for cross-file analysis (slower per ruleset, but parallel rulesets compensate).
Select mode in Step 2 of the workflow. Mode affects both scanner flags and post-processing.
| Mode | Coverage | Findings Reported |
|---|---|---|
| Run all | All rulesets, all severity levels | Everything |
| Important only | All rulesets, pre- and post-filtered | Security vulns only, medium-high confidence/impact |
Important only applies two filter layers:
--severity MEDIUM --severity HIGH --severity CRITICAL (CLI flag)category=security, confidence∈{MEDIUM,HIGH}, impact∈{MEDIUM,HIGH}See scan-modes.md for metadata criteria and jq filter commands.
┌──────────────────────────────────────────────────────────────────┐
│ MAIN AGENT (this skill) │
│ Step 1: Detect languages + check Pro availability │
│ Step 2: Select scan mode + rulesets (ref: rulesets.md) │
│ Step 3: Present plan + rulesets, get approval [⛔ HARD GATE] │
│ Step 4: Run one scan per language/category (parallel if the │
│ host supports subagent delegation, else sequential) │
│ Step 5: Merge results and report │
└──────────────────────────────────────────────────────────────────┘
│ Step 4
▼
┌─────────────────┐
│ Per-language │
│ scan │
├─────────────────┤
│ Python scanner │
│ JS/TS scanner │
│ Go scanner │
│ Docker scanner │
└─────────────────┘
Follow the detailed workflow in scan-workflow.md. Summary:
| Step | Action | Gate | Key Reference |
|---|---|---|---|
| 1 | Resolve output dir, detect languages + Pro availability | — | Use Glob, not Bash |
| 2 | Select scan mode + rulesets | — | rulesets.md |
| 3 | Present plan, get explicit approval | ⛔ HARD | Ask the user directly, or via the host's structured question tool if it has one |
| 4 | Run one scan per language/category | — | scanner-task-prompt.md — a prompt template for hosts that delegate to subagents; run the same steps directly otherwise |
| 5 | Merge results and report | — | Merge script (below) |
Enforcement: Track the 5 steps as a dependency chain (each blocks the next), using the host's task-tracking tool if one is available. Step 3 is a HARD GATE — do not proceed to Step 4 until the user has explicitly approved the plan.
Merge command (Step 5):
uv run scripts/merge_sarif.py $OUTPUT_DIR/raw $OUTPUT_DIR/results/results.sarif
| Shortcut | Why It's Wrong |
|---|---|
| "User asked for scan, that's approval" | Original request ≠ plan approval. Present plan, use AskUserQuestion, await explicit "yes" |
| "Step 3 task is blocking, just mark complete" | Lying about task status defeats enforcement. Only mark complete after real approval |
| "I already know what they want" | Assumptions cause scanning wrong directories/rulesets. Present plan for verification |
| "Just use default rulesets" | User must see and approve exact rulesets before scan |
| "Add extra rulesets without asking" | Modifying approved list without consent breaks trust |
| "Third-party rulesets are optional" | Trail of Bits, 0xdea, Decurity catch vulnerabilities not in official registry — REQUIRED |
| "Use --config auto" | Sends metrics; less control over rulesets |
| "One scan at a time when parallel is possible" | Defeats the performance advantage; run all per-language scans concurrently when the host supports it |
| "Pro is too slow, skip --pro" | Cross-file analysis catches 250% more true positives; worth the time |
| "Semgrep handles GitHub URLs natively" | URL handling fails on repos with non-standard YAML; always clone first |
| "Cleanup is optional" | Cloned repos pollute the user's workspace and accumulate across runs |
"Use . or relative path as target" | Parallel/delegated scans need absolute paths to avoid ambiguity |
| "Let the user pick an output dir later" | Output directory must be resolved at Step 1, before any files are created |
| File | Content |
|---|---|
| rulesets.md | Complete ruleset catalog and selection algorithm |
| scan-modes.md | Pre/post-filter criteria and jq commands |
| scanner-task-prompt.md | Prompt template for delegating a per-language scan to a subagent |
| Workflow | Purpose |
|---|---|
| scan-workflow.md | Complete 5-step scan execution process |
$OUTPUT_DIRsemgrep command used --metrics=off$OUTPUT_DIR/rulesets.txt$OUTPUT_DIR/raw/results.sarif exists in $OUTPUT_DIR/results/ and is valid JSONraw/$OUTPUT_DIR/repos/まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Audit GitHub Actions that run AI agents for prompt injection, unsafe interpolation, sandbox gaps, and permissive actor rules. Use for agentic CI workflows, not general application code review.
日本語の概要は準備中です。原文の説明を表示しています。
Audit and improve project-rules files (AGENTS.md, CLAUDE.md, .agents/instructions, local overrides) so the agent keeps accurate project context. Use when the user asks to check, audit, review, update, improve, or fix their AGENTS.md or CLAUDE.md, mentions "project rules maintenance" or "agent context optimization", or when the codebase has changed enough that the rules file may be stale. Scans the repository for every rules file, grades each against a quality rubric, outputs a quality report, and applies targeted edits only after user approval.
日本語の概要は準備中です。原文の説明を表示しています。
Capture learnings from the current session into the project-rules file (AGENTS.md, CLAUDE.md, or local override) so future sessions benefit. Use when the user says "revise the rules", "update AGENTS.md / CLAUDE.md with what we just learned", "save this to project memory", "remember this for next time", or at the end of a productive session when valuable context has emerged that is not yet documented. This complements agents-md-improver — improver audits, while this one captures.
日本語の概要は準備中です。原文の説明を表示しています。
Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. Use as the reference rubric when building or reviewing marketing sites, product interfaces, dashboards, portfolios, or e-commerce pages, especially alongside frontend-design.
日本語の概要は準備中です。原文の説明を表示しています。
Design a feature architecture by analyzing existing codebase patterns and conventions, then provide a comprehensive implementation blueprint with specific files to create or modify, component designs, data flows, and a build sequence. Use this skill when the user asks for an architecture design, an implementation plan for a non-trivial feature, or when dispatched as a sub-task during feature-dev architecture phase.
日本語の概要は準備中です。原文の説明を表示しています。
Deeply analyze an existing codebase feature by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use this skill when you need to understand how a feature works before modifying or extending it, when dispatched as a sub-task during feature-dev exploration, or when the user asks "how does X work in this codebase".
日本語の概要は準備中です。原文の説明を表示しています。