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/rf-mcp --skill rf-robotcodegit clone --depth 1 https://github.com/manykarim/rf-mcpWrote 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/rf-mcp/rf-robotcode)<a href="https://agentmods.dev/skills/manykarim/rf-mcp/rf-robotcode"><img src="https://agentmods.dev/badge/skills/manykarim/rf-mcp/rf-robotcode/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/rf-mcp/rf-robotcode"><img src="https://agentmods.dev/badge/skills/manykarim/rf-mcp/rf-robotcode.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 | $0.00051 | $0.00897 |
| Opus 5.5 | $0.00020 | $0.00359 |
| Sonnet 5.5 | $0.00010 | $0.00179 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
rf-robotcode 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 2d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Robot Framework with rf-mcp
The rf_* tools run robotcode in the project's environment. Use them instead of shell commands, file greps or reading output.xml.
Pick the mode first
| Intent | Tool | Details |
|---|---|---|
| What tests, tags, suites, files, profiles exist? | rf_discover |
large-projects |
| Why did X fail? Fix this test. | rf_results first, then rf_debug |
triage |
| A real test is involved and must be inspected live | rf_debug - never a REPL copy |
debugging |
| Explore a library, page or API; write a new test | rf_repl |
repl-authoring |
| Check files without running | rf_analyze |
analyze |
| Keyword names, arguments, docs | rf_doc, .kw, .doc |
repl-authoring |
| Run tests and report | rf_run, then rf_results |
results |
| Profiles, robot.toml, environment | rf_discover action=profile_show |
config-profiles |
Several modes chain: explore, then author, then run, then inspect.
Rules that save the most turns
- Longnames, not files. Select with
by_longnametaken fromrf_discover. A single.robotfile inpathsbecomes the top suite: parent__init__.robotsetups are skipped and longnames lose their prefix. - Recorded run first. For "why did X fail?" call
rf_results(action="show", failed_only=true, thenaction="log", by_longname=[...]) before reading files or debugging. Never read or grepoutput.xml. - Debugger for real tests. If an existing test is involved,
rf_debugit; a REPL copy runs a misleading imitation. - Analyze before running.
rf_analyzeafter every edit; fixKeywordNotFoundand argument errors beforerf_run. - Look keywords up.
rf_doc action=keywords(several name patterns at once) or.kw <text>in the REPL; never guess names or argument order. - One session, reused. Start one
rf_replsession, send several known steps per send, and stop it at the end (or say it is still open). - Every test stands alone. Each test creates its own data and passes when run alone by longname.
- Done means verified. A task is done only when
rf_analyzeis clean andrf_runpasses.
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.
- 2d ago First seen · 46 lines · 51 tokens per session scan A 782966632d68
rf-robotcode is a skill published in the GitHub repository manykarim/rf-mcp (118 stars, last pushed yesterday), licensed Apache-2.0. It adds 51 tokens to every session and 897 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 2026-11-12.
rf-robotcode compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| rf-robotcodemanykarim/rf-mcp | Skill | 118 | yesterday | Apache-2.0 | A | 51 | Claude Code, Codex |
| schema-explorationlangchain-ai/deepagents | Skill | 31k | today | MIT | A | 57 | Claude Code, Codex |
| mempalace-recallMemPalace/mempalace | Skill | 61k | yesterday | MIT | A | 94 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 57k | 5d ago | MIT | A | 44 | Claude Code |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 69k | 8d ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| analyze-marketlangchain-ai/deepagents | Skill | 31k | today | MIT | A | 34 | Claude Code, Codex |
| haikuagno-agi/agno | Skill | 43k | today | Apache-2.0 | A | 0 | Claude Code, Codex |