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.
npx skills add waybarrios/opencode-power-pack --skill agentic-actions-auditorgit clone --depth 1 https://github.com/waybarrios/opencode-power-packWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/waybarrios/opencode-power-pack/agentic-actions-auditor)<a href="https://agentmods.dev/skills/waybarrios/opencode-power-pack/agentic-actions-auditor"><img src="https://agentmods.dev/badge/skills/waybarrios/opencode-power-pack/agentic-actions-auditor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/waybarrios/opencode-power-pack/agentic-actions-auditor"><img src="https://agentmods.dev/badge/skills/waybarrios/opencode-power-pack/agentic-actions-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 5.1 | $0.00044 | $0.04671 |
| Opus 5.5 | $0.00018 | $0.01868 |
| Sonnet 5.5 | $0.00009 | $0.00934 |
| Haiku 4.5 | $0.00004 | $0.00467 |
Grade A, and why
agentic-actions-auditor 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 1mo 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.
This is a copy
92% identical to agentic-actions-auditor — 80 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Actions Auditor
Static security analysis guidance for GitHub Actions workflows that invoke AI coding agents. This skill teaches you how to discover workflow files locally or from remote GitHub repositories, identify AI action steps, follow cross-file references to composite actions and reusable workflows that may contain hidden AI agents, capture security-relevant configuration, and detect attack vectors where attacker-controlled input reaches an AI agent running in a CI/CD pipeline.
When to Use
- Auditing a repository's GitHub Actions workflows for AI agent security
- Reviewing CI/CD configurations that invoke Claude Code Action, Gemini CLI, or OpenAI Codex
- Checking whether attacker-controlled input can reach AI agent prompts
- Evaluating agentic action configurations (sandbox settings, tool permissions, user allowlists)
- Assessing trigger events that expose workflows to external input (
pull_request_target,issue_comment, etc.) - Investigating data flow from GitHub event context through
env:blocks to AI prompt fields
When NOT to Use
- Analyzing workflows that do NOT use any AI agent actions (use general Actions security tools instead)
- Reviewing standalone composite actions or reusable workflows outside of a caller workflow context (use this skill when analyzing a workflow that references them via
uses:) - Performing runtime prompt injection testing (this is static analysis guidance, not exploitation)
- Auditing non-GitHub CI/CD systems (Jenkins, GitLab CI, CircleCI)
- Auto-fixing or modifying workflow files (this skill reports findings, does not modify files)
Rationalizations to Reject
When auditing agentic actions, reject these common rationalizations. Each represents a reasoning shortcut that leads to missed findings.
1. "It only runs on PRs from maintainers"
Wrong because it ignores pull_request_target, issue_comment, and other trigger events that expose actions to external input. Attackers do not need write access to trigger these workflows. A pull_request_target event runs in the context of the base branch, not the PR branch, meaning any external contributor can trigger it by opening a PR.
What ships with it
12 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.
- references/action-profiles.md 8.6 KB
- references/cross-file-resolution.md 10 KB
- references/foundations.md 5.0 KB
- references/vector-a-env-var-intermediary.md 4.4 KB
- references/vector-b-direct-expression-injection.md 4.4 KB
- references/vector-c-cli-data-fetch.md 4.9 KB
- references/vector-d-pr-target-checkout.md 5.1 KB
- references/vector-e-error-log-injection.md 5.3 KB
- references/vector-f-subshell-expansion.md 5.7 KB
- references/vector-g-eval-of-ai-output.md 5.5 KB
- references/vector-h-dangerous-sandbox-configs.md 5.4 KB
- references/vector-i-wildcard-allowlists.md 4.3 KB
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.
- 1mo ago First seen · 324 lines · 44 tokens per session scan A aef91fc6243e
agentic-actions-auditor is a skill published in the GitHub repository waybarrios/opencode-power-pack (544 stars, last pushed 5d ago), licensed MIT. It adds 44 tokens to every session and 4,671 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to agentic-actions-auditor, differing in 80 lines, and is treated as a copy.
Other skills, from other repositories
green-prs
Inspect and prepare the selected PR queue against its exact current base, repair authorized defects with contributor credit, and report full versus partial validation. Use for maintainer pre-greening; merging requires separate owner authorization and the shared merge gates.
ln-63-deployment-engineer
Prepares delivery pipelines and remote infrastructure, then executes authorized rollouts; not standalone quality-gate setup or local container packaging.
pr-babysitter
Monitors or repairs an open GitHub PR: CI failures, conflicts, review threads, and merge readiness, reporting state changes. Use when asked to "watch this PR", "fix CI", "resolve conflicts", or "address review comments".
verification-quality
Truth scoring, code-quality verification, and automatic rollback with a high accuracy threshold. Use when validating agent output before it ships, gating changes on quality, or adding a verify-and-rollback safety loop.
loki-mode
Runs an autonomous software factory that knows what it is supposed to deliver and proves it did, with a signed receipt. Use when the user says Loki Mode or asks to build, fix or verify software autonomously.
checkpoint-mode
Pauses for human review every N tasks (selective autonomy). Use when work needs short autonomous bursts with feedback instead of one long run.