mining
Skill93 starsChanged 3 months agoMITView on GitHub
Mine, compare, or re-crawl approved external robotics repositories into local evidence-cited Robium observations for later skill absorption.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- anthropics/cwc-workshopstheir own version, first seen Jun 4, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- anthropics/cwc-workshops★ 2.3ksame name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository32 other files it gives its agents.
- AGENTS.mdAGENTS.md
- learnings/AGENTS.mdAGENTS.md
- skills/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- learnings/CLAUDE.mdCLAUDE.md
- skills/CLAUDE.mdCLAUDE.md
- app-publishingSkill
- architectSkill
- cloud-runSkill
- dataSkill
- environmentsSkill
- foxgloveSkill
- gazeboSkill
- gemini-roboticsSkill
- huggingfaceSkill
- integrationSkill
- isaac-labSkill
- isaac-simSkill
- learning-loopSkill
- lerobotSkill
- live-demoSkill
- mujocoSkill
- navigationSkill
- rerunSkill
- ros2Skill
- runpodSkill
- rviz2Skill
- simulationSkill
- skill-authorSkill
- test-assetsSkill
- testingSkill
- visualizationSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 6 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 15
Start with a survey of the tree, active code paths, documentation, examples, tests, and license.
- Distinctive: line 18
Prefer official/vendor sources.
- Distinctive: line 21
Read WORKFLOW.md for the survey, deep-read, comparative, and re-crawl mechanics.
- Distinctive: line 26
Keep patterns, orderings, failure discriminators, integration shapes, and configuration decisions that transfer beyond the source project.
- Distinctive: line 30
Every observation cites a pinned repository commit, path, line range, and a verbatim source excerpt that the citation verifier can find.
- Distinctive: line 32
Read EVIDENCE.md for source-authority thresholds, conflicts, licensing, placement, and new-skill proposals.
- Distinctive: line 45
Do not crawl issue trackers or commit history as part of the current mining workflow.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Mining
Mine for transferable decisions, not code volume.
Choose what is worth reading
- Candidate discovery and a one-line registry entry are read-only triage.
Survey or deep-read only a repository the user named or approved in
learnings/SOURCES.md. - Start with a survey of the tree, active code paths, documentation, examples, tests, and license. Spend deep-reading effort only where the survey finds a decision that could change a Robium skill.
- Prefer official/vendor sources. Use comparative reads when independent projects answer the same question; use a re-crawl when a previously mined source changed.
- Read WORKFLOW.md for the survey, deep-read, comparative, and re-crawl mechanics.
Keep only reusable evidence
- Keep patterns, orderings, failure discriminators, integration shapes, and configuration decisions that transfer beyond the source project.
- Drop project names, incidental ports, arbitrary tuning, style, and other local choices unless they explain a reusable boundary.
- Every observation cites a pinned repository commit, path, line range, and a verbatim source excerpt that the citation verifier can find.
- Read EVIDENCE.md for source-authority thresholds, conflicts, licensing, placement, and new-skill proposals.
Preserve the learning boundary
- Output gitignored local observations and source-registry updates, never
direct skill edits. Absorption belongs to
learning-loopand remains separately reviewed. - Compare findings with existing skills and observations. Record disagreement with both provenances; do not silently replace Robium field evidence with an upstream idiom.
- Point to source code by default. Vendor code only when it is short, genuinely useful as a maintained example, and its license and attribution permit it.
- Do not crawl issue trackers or commit history as part of the current mining workflow.
Done
- The registry records the pinned commit, crawl date, status, and the skill or reference files that ultimately retained the finding. Local observation IDs are not repository history.
- Citation and observation checks pass for every retained finding.
- Each finding names the owning skill or explains why no current skill owns it.
- Temporary clones and survey reports remain outside the committed plugin.
- End with a short handoff: report how many local observations were saved and
how many are
readyversustentative, then say that the next step is to runlearning-loopto distill ready findings into existing skills or route a justified new-skill proposal throughskill-author. Ask whether the user wants that absorption run in a background subagent; do not start it without approval.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

