technical-learning-note
Skill0 starsChanged 7 months agoMITView on GitHub
Use when a repository keeps technical learning notes and the output should explain implementation mechanisms, key code, and tradeoffs instead of just listing completed features. Trigger after meaningful engineering work or when the user asks for a study-oriented explanation.
In this repository9 other files it gives its agents.
- AGENTS.mdAGENTS.md
- decision-recordingSkill
- harness-bootstrapSkill
- issue-driven-workflowSkill
- planning-workflowSkill
- review-workflowSkill
- spec-writingSkill
- subagent-workflowSkill
- troubleshooting-workflowSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is 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.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Write learning notes that help a future reader understand how something works technically.
- Distinctive: line 25
no explanation of why the code works
- Very specific: line 40
Use decision-recording when the main value is why a durable choice was made, and issue-driven-workflow when the note is really task status.
≈ “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
Technical Learning Note
Write learning notes that help a future reader understand how something works technically.
This skill is for mechanism and tradeoff understanding, not decision logging or issue tracking.
Required qualities
- explain the mechanism, not just the user-visible feature
- mention the key code paths
- describe state, events, processing flow, or rendering flow when relevant
- explain why this approach was chosen
- note tradeoffs and remaining risks
Reject these patterns
- feature list only
- release-note style summary only
- no file references
- no explanation of why the code works
Suggested structure
- problem
- mechanism
- key code
- why this approach
- alternatives considered
- remaining risks
- validation
Resources
- See
references/note-rubric.mdfor the quality bar. - Use
decision-recordingwhen the main value is why a durable choice was made, andissue-driven-workflowwhen the note is really task status.
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.

