review-and-recommend
Skill64 starsChanged 27 days agoMITView on GitHub
Review data, issues, code, and git history; present options with effort and one-way/two-way door labels; recommend one path and name the right fix (explain if they differ). Use before implementing when a decision needs evidence-backed options.
In this repository6 other files it gives its agents.
- autopilotSkill
- friction-logSkill
- prefer-local-kody-executeSkill
- ship-prSkill
- use-kodySkill
- visual-recapSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
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 17
Call out the right fix. If it differs from the recommendation, explain why.
- Distinctive: line 19
Stop and wait for a choice.
≈ “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
Review and recommend
- Review the relevant data, issues, code, and git history.
- Present real options (numbered) with associated effort (
Easy·Medium·Hard). Label each as a one-way door or a two-way door (hard-to-reverse vs reversible). - Make a recommendation.
- Call out the right fix. If it differs from the recommendation, explain why.
- Stop and wait for a choice; do not implement yet.
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.