refine
Skill14 starsChanged 36 days agoMITView on GitHub
Refine one existing skill's overall structure and guidance while preserving its intended outcome. Use when a skill is verbose, redundant, overprescriptive, unclear, or needs to be redefined around essential requirements and model autonomy.
42 other projects use a version of this.
Adopted by
Most recently taken up by
- ryanportfolio/winuse-mcptheir own version, first seen Nov 8, 2026
- ghostdogpr/skillstheir own version, first seen Nov 7, 2026
- ryanportfolio/Harness-Firmwaretheir own version, first seen Nov 7, 2026
- ryanportfolio/HarnessFirmware.comtheir own version, first seen Nov 5, 2026
- ryanportfolio/Corewise.Academytheir own version, first seen Nov 5, 2026
- Blakeem/aipromptguide-workflowstheir own version, first seen Nov 4, 2026
Used with
Projects with it also use addskill, apply-firmware and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
ryanportfolioSkilladdskill
Create, import, update, or install repo or personal skills: runtime ownership, resources, discovery checks.
Also in 6 projects that use this
ryanportfolioSkillapply-firmware
Bring current folder (plain folder, existing repo, old or partial firmware copy) up to full Harness Firmware in place. Mirror external repo → adopt-repo.
Also in 6 projects that use this
- +10 more from ryanportfolio
Other versions42 projects use a version of this.
Word for word · 1
- boaz-hwang/skilloom★ 14100% same
Edited · 0
None found.
Wrote their own version · 41
- PrimeIntellect-ai/prime-agent★ 23ksame name
- windmill-labs/windmill★ 18ksame name
- skyllwt/OmegaWiki★ 1.7ksame name
- DAIR-AutoResearch/AutoSci★ 1.7ksame name
- PKU-DAIR/AutoSci★ 1.7ksame name
- skyllwt/AutoSci★ 1.7ksame name
- rsi-gear/gear★ 422same name
- AlexPEClub/ai-coding-starter-kit★ 382same name
- automagik-dev/genie★ 351same name
- namastexlabs/automagik-genie★ 351same name
31 more not listed
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 repository3 other files it gives its agents.
- consolidateSkill
- distillSkill
- evolveSkill
The file
We split this skill into the rules it gives an agent
8 rules. 0 are common, 8 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 36 edited versions we read keep these.
8
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
Read the target's instructions and linked templates, references, and scripts.
- Distinctive: line 20
When intent or conflicting requirements would change the rewrite, propose an interpretation and ask a focused question.
- Distinctive: line 23
Keep the existing name unless renaming is requested or agreed.
- Distinctive: line 27
Keep a recoverable baseline and prepare the revision separately.
- Distinctive: line 46
Check the revision against the original purpose, essential requirements, metadata, and referenced resources.
- Distinctive: line 55
Use comparable task conditions if claiming better execution quality or efficiency.
- Distinctive: line 56
Do not weaken acceptance criteria to make the revision pass.
- Distinctive: line 62
If a material requirement or necessary quality judgment remains unresolved, retain the candidate separately and ask for the specific …
“Common” is measured: kept by at least 6 in 10 of the 36 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Refine
Make one skill clear and sufficient for a capable agent. Review deletion first; preserve what quality depends on. Whole-skill restructuring is in scope, combining multiple skills is not. Discuss in the user's language.
1. Establish the intended result
Read the target's instructions and linked templates, references, and scripts. Infer its intended output, essential constraints, and quality criteria from the skill, available accepted examples, and user feedback. Execution records can help but are not required. Do not confuse today's inputs with reusable requirements.
When intent or conflicting requirements would change the rewrite, propose an interpretation and ask a focused question. Ask before changing the purpose or essential quality criteria unless the user has already authorized that change. Keep the existing name unless renaming is requested or agreed.
2. Refine the whole skill
Keep a recoverable baseline and prepare the revision separately. Find the shortest sufficient process for the intended result. Review deletion, merging/shortening, and revision before adding instructions. Remove repeated or irrelevant guidance and implementation detail a capable agent can decide; preserve non-obvious domain knowledge, fragile operations, and essential exceptions.
For each step, retain necessary inputs, decisive constraints, and what completion looks like. Keep required user decisions and permissions, without inventing extra approval gates. Reorganize the whole structure when it improves clarity; do not rewrite sound instructions merely for stylistic uniformity.
Inspect resources before removing or changing them. Bundle only what the revised skill needs, using relative paths; do not hide excess prose in supporting files. Reuse or derive needed templates from accepted artifacts. Ask for a missing resource only when it cannot be faithfully reconstructed. Make incidental values inputs. Choose languages and tools for the task, without adding unnecessary dependencies.
3. Check what changed
Check the revision against the original purpose, essential requirements, metadata, and referenced resources. Retain meaningful checks and their invocation in the skill; add missing evaluation only where it measures actual quality. Instruct the skill to run checks before delivery, report failed or untested criteria, and present concrete review questions only for judgments code cannot establish.
Match verification to the impact of the edit. Clear wording or duplicate removal may need only a requirements comparison. Changes to behavior, templates, or code need relevant checks and representative examples, including rare affected cases. Use comparable task conditions if claiming better execution quality or efficiency. Do not weaken acceptance criteria to make the revision pass. Distinguish structural cleanup from measured behavioral improvement; agent judgment is not human approval.
4. Deliver the revision
Apply a supported revision without overwriting unrelated edits. If a material requirement or necessary quality judgment remains unresolved, retain the candidate separately and ask for the specific missing decision. If nothing useful needs changing, keep the original.
Report the significant deletions or revisions, what was verified, and any remaining human review.
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.

