A workflow for using CodeQL, a tool that analyzes source code as data to find security problems, and its SARIF result files.

Use it to create and assess CodeQL databases, run security queries for supported languages, add data-extension models, and process SARIF reports.

It helps avoid missed vulnerabilities caused by poor analysis databases, missing project-specific models, or incorrectly selected security queries.

codeql — Skill by waybarrios

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add skills/waybarrios/opencode-power-pack/codeql

Any agent

npx skills add waybarrios/opencode-power-pack --skill codeql

Clone the repo

git clone --depth 1 https://github.com/waybarrios/opencode-power-pack

Made for: Claude Code, Codex.

Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,429 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00042	$0.03429
Opus 5	$0.00021	$0.01715
Sonnet 5	$0.00008	$0.00686
Haiku 4.5	$0.00004	$0.00343

Measured 2d ago against content hash a41eb8e977a4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codeql scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

codeql — 92% identical, 24 lines differ
codeql — 89% identical, 12 lines differ
codeql — 89% identical, 12 lines differ

skills/codeql/SKILL.md · 264 lines

How it starts

The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CodeQL Analysis

Supported languages: Python, JavaScript/TypeScript, Go, Java/Kotlin, C/C++, C#, Ruby, Swift.

Skill resources: Reference files and templates are located at references/ and workflows/.

Essential Principles

Database quality is non-negotiable. A database that builds is not automatically good. Always run quality assessment (file counts, baseline LoC, extractor errors) and compare against expected source files. A cached build produces zero useful extraction.
Data extensions catch what CodeQL misses. Even projects using standard frameworks (Django, Spring, Express) have custom wrappers around database calls, request parsing, or shell execution. Skipping the create-data-extensions workflow means missing vulnerabilities in project-specific code paths.
Explicit suite references prevent silent query dropping. Never pass pack names directly to codeql database analyze — each pack's defaultSuiteFile applies hidden filters that can produce zero results. Always generate a custom .qls suite file.
Zero findings needs investigation, not celebration. Zero results can indicate poor database quality, missing models, wrong query packs, or silent suite filtering. Investigate before reporting clean.
macOS Apple Silicon requires workarounds for compiled languages. Exit code 137 is arm64e/arm64 mismatch, not a build failure. Try Homebrew arm64 tools or Rosetta before falling back to build-mode=none.
Follow workflows step by step. Once a workflow is selected, execute it step by step without skipping phases. Each phase gates the next — skipping quality assessment or data extensions leads to incomplete analysis.

Output Directory

All generated files (database, build logs, diagnostics, extensions, results) are stored in a single output directory.

If the user specifies an output directory in their prompt, use it as OUTPUT_DIR.
If not specified, default to ./static_analysis_codeql_1. If that already exists, increment to _2, _3, etc.

Read the full file on GitHub · 264 lines

Files

What ships with it

15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2d ago First seen · 264 lines · 42 tokens per session scan A a41eb8e977a4

Subscribe to this mod's changes

codeql is a skill published in the GitHub repository waybarrios/opencode-power-pack (489 stars, last pushed 8d ago), licensed MIT. It adds 42 tokens to every session and 3,429 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Code review Databases Security ai-agents anthropic claude-code developer-tools llm-tools

dingtalk_channel_connect

Use a headed browser to automatically complete DingTalk channel integration for QwenPaw. Applicable when the user mentions DingTalk, developer console, Client ID, Client Secret, bot, Stream mode, binding or configuring a channel. Supports pausing when a login page is detected and resuming after the user logs in.

agentscope-ai/QwenPaw · 69 tokens

make_plan

For external plan request scenarios, guides the Agent to request a clear, actionable, step-by-step plan from a stronger Agent via listagents and chatwithagent, emphasizing that the plan is executed by the requester, not by the consulted Agent.

agentscope-ai/QwenPaw · 51 tokens

pdf

当用户需要对PDF文件进行任何操作时，请使用此技能。包括从 PDF 中读取或提取文本/表格、合并多个 PDF、拆分 PDF、旋转页面、添加水印、创建新PDF、填写PDF表单、加密/解密 PDF、提取图片，以及对扫描版 PDF 进行 OCR 使其可搜索。如果用户提到 .pdf 文件或要求生成 PDF，请使用此技能。.

agentscope-ai/QwenPaw · 95 tokens

wiki-lint

Audit and maintain the health of the Obsidian wiki. Use this skill when the user wants to check their wiki for issues, find orphaned pages, detect contradictions, identify stale content, fix broken wikilinks, or perform general maintenance on their knowledge base. Also triggers on "clean up the wiki", "what needs…

Ar9av/obsidian-wiki · 152 tokens

wiki-status

Show the current state of the wiki — what's been ingested, what's pending, and the delta between sources and wiki content. Use this skill when the user asks "what's the status", "how much is ingested", "what's left to process", "show me the delta", "what changed since last ingest", "wiki dashboard", or wants an…

Ar9av/obsidian-wiki · 210 tokens

wiki-dashboard

Create dynamic, queryable dashboard views of the Obsidian vault using Obsidian Bases or Dataview. Use this skill when the user says "create a dashboard", "vault dashboard", "show all X as a table", "dynamic view", "query my vault", "build a content index", "show me all concepts/entities/projects", or wants a…

Ar9av/obsidian-wiki · 112 tokens