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 rampstackco/claude-skills --skill oss-contribution-researchgit clone --depth 1 https://github.com/rampstackco/claude-skillsWrote 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/rampstackco/claude-skills/oss-contribution-research)<a href="https://agentmods.dev/skills/rampstackco/claude-skills/oss-contribution-research"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/oss-contribution-research/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/rampstackco/claude-skills/oss-contribution-research"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/oss-contribution-research.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 | $0.00200 | $0.04438 |
| Opus 5.5 | $0.00080 | $0.01775 |
| Sonnet 5.5 | $0.00040 | $0.00888 |
| Haiku 4.5 | $0.00020 | $0.00444 |
Grade A, and why
oss-contribution-research 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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OSS Contribution Research
Prepare one outside contribution to an open-source repo, gate by gate, and stop at a queue item a human approves. The agent running this skill never posts.
When to use
- Picking up an existing issue or confirmed bug in a repo the user does not maintain
- Checking whether a repo accepts AI-assisted pull requests before any work starts
- Asking a maintainer for a go-ahead before writing a patch (an intake comment)
- Turning a fix into a small, disclosed pull request draft that a human approves
- Following up on the user's own outside pull request: a review reply, the 14-day ping, or the 28-day close
- Running a contribution pipeline with an approval queue and a per-repo registry
When NOT to use
- Reviewing a pull request in a repo the user maintains (use
code-review-web) - Updating packages or lockfiles in the user's own project (use
dependency-management) - Writing a new feature spec for the user's own product (use
pm-spec-writing) - Writing a new skill for this catalog (use
skill-creation-walkthrough) - Unsolicited refactors, rewrites, or features in someone else's repo. This skill refuses them.
Required inputs
- Target. The repo (
owner/repo) and one of: an existing issue or pull request URL, a bug the agent can reproduce, or a request to search the repo's open issues for a candidate. - Queue snapshot. Each run starts on the user's normal login. It makes read-only (GET) calls to the user's private approval queue repo and exports a snapshot to a local file. The snapshot holds three things:
- the registry (
registry.yaml), with each repo's policy class, disclosure template per action type, review mode, cadence cap, cached last submission date and status; - the posted ledger: issues labeled
status:posted, with the poster's posted markers; - the pause state: whether any open issue is labeled
pipeline:paused.
- the registry (
- A read-only token. After the snapshot is written, the run switches to a read-only forge token for all outside research and patch work. It reads the queue only from the snapshot.
- Filing. Filing the finished item into the queue is a separate, internal step on the user's normal login.
- Posting. Posting to the outside repo happens only through the queue's poster, and only on approved items.
- Freshness. The poster revalidates everything at post time, so the snapshot is never the last check.
- A local clone of the target repo on a branch the user's fork can push later.
- A local clone of the queue repo. The queue-item format, the poster's docs and its hash helper are read from the user's local clone of their private queue repo, pulled before the run. The read-only token cannot read that repo, so the run never fetches those files over it.
What ships with it
6 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.
- today First seen · 177 lines · 200 tokens per session scan A 48316e3d7c87
oss-contribution-research is a skill published in the GitHub repository rampstackco/claude-skills (976 stars, last pushed yesterday), licensed MIT. It adds 200 tokens to every session and 4,438 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-10-20.
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