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 manykarim/robotframework-agentskills --skill rf-libdocgit clone --depth 1 https://github.com/manykarim/robotframework-agentskillsWrote 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/manykarim/robotframework-agentskills/rf-libdoc)<a href="https://agentmods.dev/skills/manykarim/robotframework-agentskills/rf-libdoc"><img src="https://agentmods.dev/badge/skills/manykarim/robotframework-agentskills/rf-libdoc/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/manykarim/robotframework-agentskills/rf-libdoc"><img src="https://agentmods.dev/badge/skills/manykarim/robotframework-agentskills/rf-libdoc.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 | $0.00031 | $0.01453 |
| Opus 5.5 | $0.00012 | $0.00581 |
| Sonnet 5.5 | $0.00006 | $0.00291 |
| Haiku 4.5 | $0.00003 | $0.00145 |
Grade A, and why
rf-libdoc 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Robot Framework Libdoc
Find keywords for a use case and explain how to call them, from libdoc data of libraries, resources, suites and spec files. Output is JSON only.
robotcode first: check
robotcode --versiononce. If it is on PATH, preferrobotcode libdoc <Lib> list "*text*",robotcode libdoc <Lib> show "<Keyword>"or the REPL's.kw <text>— quicker, and they use the project'srobot.toml. Seerf-robotcode. Userf-libdocwhen robotcode is not installed, or when you need a ranked search across several sources or the structured JSON contract below.
When to use
Load this skill first, instead of answering from memory or grepping files, when a Robot Framework answer depends on an exact keyword name, its arguments or its documentation:
- which keyword does something in an installed library (BuiltIn, Collections, SeleniumLibrary, Browser, RequestsLibrary, ...) or in the project's own .resource files;
- what arguments, types or defaults a keyword takes (its signature);
No keyword with name '...' found, or a wrong-argument-count error.
The bundled libdoc script returns exact names, signatures and docs.
Not this skill: writing whole tests belongs to the library skills (rf-browser, rf-requests, ...). When the robotcode CLI is installed or the user asks for robotcode libdoc, use rf-robotcode.
Which command
Run the bundled script through the project environment so the project's libraries are importable. Script paths are relative to this skill's directory (the folder containing this SKILL.md), not to the project.
| Question | Command | mode |
|---|---|---|
| Which keyword does X? | --search "<use case>" |
search |
| How do I call keyword X? | --keyword "<Keyword>" |
explain |
| Not sure of the exact name | --keyword "<guess>" --search "<use case>" |
explain, or fallback with suggestions |
| What does library X offer? | no --keyword / --search |
list |
Find keywords for a use case (ranked; tune with --weights, cap with --limit):
What ships with it
1 file 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.
- 11d ago Changed · -2 tokens per session 7c5cfd64e1b7
- 17d ago First seen · 89 lines · 33 tokens per session scan A 6240dcace119
rf-libdoc is a skill published in the GitHub repository manykarim/robotframework-agentskills (38 stars, last pushed 5d ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,453 once invoked, about $0.0001 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 2026-10-01.
Other skills, from other repositories
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
eval-dataset-design
A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.
tika-eval-compare
Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".
cua-driver
Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.
jetson-validate-image
Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.