Borrowing it
Nothing to install: this file belongs to gpt-cmdr/ras-commander. 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/gpt-cmdr/ras-commander/main/.claude/skills/ras-api-discovery/SKILL.mdgit clone --depth 1 https://github.com/gpt-cmdr/ras-commanderWrote 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/gpt-cmdr/ras-commander/ras-api-discovery)<a href="https://agentmods.dev/skills/gpt-cmdr/ras-commander/ras-api-discovery"><img src="https://agentmods.dev/badge/skills/gpt-cmdr/ras-commander/ras-api-discovery/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/gpt-cmdr/ras-commander/ras-api-discovery"><img src="https://agentmods.dev/badge/skills/gpt-cmdr/ras-commander/ras-api-discovery.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 | $0.00039 | $0.00504 |
| Opus 5.5 | $0.00016 | $0.00202 |
| Sonnet 5.5 | $0.00008 | $0.00101 |
| Haiku 4.5 | $0.00004 | $0.00050 |
Grade A, and why
ras-api-discovery 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 15d 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.
What it actually says
RAS API Discovery
Identify the requested capability and installed ras-commander version. Follow the runtime setup and MCP rules in the ras-commander skill: use the installed public Python API, and if ras_commander is not importable, install ras-commander[full] into a task-local environment (uv preferred) rather than answering from file searches. Distinguish installed behavior, current published behavior, and repository development work.
Use public exports, signatures, docstrings, canonical schemas, and examples from the matching package/release. Search source when these do not establish an answer. Source inspection is appropriate for API discovery; it does not authorize copying parsers or bypassing public APIs to extract project data. Treat website/main examples as potentially newer than the installed release.
For DataFrames, consult the installed schemas module and the actual return contract rather than repeating a cached column table. Check whether the selected method is static or instance-based, its required extras/runtime, input semantics, return type, and side effects. Do not invoke a setter, initializer, compute method, download, or export merely to inspect its signature.
Split large investigations into focused source, example, or contract reviews using the harness's native worker mechanism when useful. Select workers based on the task and available capabilities; do not hardcode provider models or import a fictitious Task module. Give each reviewer the package version, question, scope, and concise evidence format. Preserve notebook outputs; read source cells without execution for discovery.
Return the supported method and verified signature, canonical schema/return fields, a version-matched usage example when available, required dependencies, source locators, and any unresolved API gap. Label an unexecuted example as unexecuted. Keep large research artifacts in the caller's authorized workspace only when needed. No fixed drive, repository location, or global project object is assumed.
Use the fuller Python workflow for project data. Any project MCP query requires a bounded informational subagent under the ras-commander skill's MCP contract. A discovered API is not evidence that its output or side effects satisfy that boundary.
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.
- 15d ago Changed dde347593938
- 25d ago First seen · 23 lines · 39 tokens per session scan A 4e15413d258a
ras-api-discovery is a skill published in the GitHub repository gpt-cmdr/ras-commander (88 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 504 once invoked, about $0.0002 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 2026-10-04.
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