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 OpenHands/extensions --skill github-agents-md-maintainergit clone --depth 1 https://github.com/OpenHands/extensionsWrote 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/openhands/extensions/github-agents-md-maintainer)<a href="https://agentmods.dev/skills/openhands/extensions/github-agents-md-maintainer"><img src="https://agentmods.dev/badge/skills/openhands/extensions/github-agents-md-maintainer/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/openhands/extensions/github-agents-md-maintainer"><img src="https://agentmods.dev/badge/skills/openhands/extensions/github-agents-md-maintainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 8 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 Supply Chain · line 172 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 185 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 49 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.
- medium Data Exfiltration · line 78 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.
- medium Data Exfiltration · line 172 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.
- medium Data Exfiltration · line 185 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.
- low Supply Chain · line 49 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- low Supply Chain · line 78 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
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 | $0.00064 | $0.03017 |
| Opus 5.5 | $0.00026 | $0.01207 |
| Sonnet 5.5 | $0.00013 | $0.00603 |
| Haiku 4.5 | $0.00006 | $0.00302 |
Grade A, and why
github-agents-md-maintainer scanned grade A with 1 finding 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 14d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://api.github.com/user \ How it starts
The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md Maintainer Automation
Create a cron automation that keeps each configured repository's AGENTS.md -
the file an agent reads first when it starts work there - matching what the
repository actually is. It is created when missing, updated when the repository
has moved on, and left alone when it is still accurate.
The automation script is deterministic: scheduling, the once-per-week claim, the clone, the branch, the commit, the push, the pull request, and the clone's removal are all handled in Python. The LLM is invoked only to read the repository and write the file.
A week is one unit of work per repository, so a cron that fires more often than intended, a retried run, or a restarted service cannot open the same pull request twice. A repository whose previous pull request from this automation is still open is skipped, because a second one would edit the same file and reviewing it would tell you nothing the first did not.
The script imports shared GitHub transport from
scripts/github_client.py, installed with this skill. Include it beside
main.py when packaging manually, as shown below.
Prerequisites
Required secret
Verify that the following secret is set in OpenHands Settings -> Secrets:
| Secret name | Token type | Minimum permissions |
|---|---|---|
GITHUB_PERSONAL_ACCESS_TOKEN |
Classic PAT | repo |
GITHUB_PERSONAL_ACCESS_TOKEN |
Fine-grained PAT | Contents: Read and write, Metadata: Read, Pull requests: Read and write |
Contents write is required because the branch is pushed, and pull request write because the pull request is opened. No issue permission is needed: this automation never comments on an issue.
Check with:
curl -s https://api.github.com/user \
-H "Authorization: Bearer $GITHUB_PERSONAL_ACCESS_TOKEN" \
| python3 -c "import json,sys; d=json.load(sys.stdin); print(d.get('login') or d.get('message'))"
If the token is missing or invalid, inform the user and stop.
Setup Workflow
What ships with it
8 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.
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.
- 14d ago Changed · +7 lines 2da13b34624f
- 1mo ago Changed · +6 lines a117d2f599af
- 1mo ago First seen · 272 lines · 64 tokens per session scan A ff07d89b3293
github-agents-md-maintainer is a skill published in the GitHub repository OpenHands/extensions (167 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 3,017 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (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
prowler-commit
Creates professional git commits following conventional-commits format. Trigger: When creating commits, after completing code changes, when user asks to commit.
gh-auth-isolation
Safely manage multiple GitHub identities (EMU + personal) in agent workflows.
comet-github
A routing guide for Comet-related GitHub work. It directs requests about pull requests, issues, CI failures, ideas, and fixes to the appropriate review or implementation process.
release-helper
Ensures configuration and code changes are released correctly. Use PROACTIVELY whenever you edit config.json, change any setting, or fix a configuration bug in this project, so the change reaches production.
github-skill
Work with GitHub via the gh CLI — clone repositories, create/list/merge pull requests, create/list issues, and run any other gh command (API calls, workflow runs, releases, repo administration). List operations return parsed JSON.
merge-pr
Merge a pull request with status checks, squash merge, and branch cleanup. Handles worktree contexts.