source-qa
Skill1 starsChanged 23 days agoMITView on GitHub
How to find the questions, errors and confusing behaviour learners hit with a technology — GitHub issues and discussions of the official repo, Stack Overflow, forums — as pitfalls material for a codelabgen course. Source type `qa`.
In this repository24 other files it gives its agents.
- code-authoringSkill
- codelabgen-orchestratorSkill
- course-extensionSkill
- curriculum-designSkill
- diagrammingSkill
- example-designSkill
- lesson-reviewSkill
- notes-writingSkill
- readalong-writingSkill
- runtime-strategySkill
- site-assemblySkill
- source-articlesSkill
- source-books-coursesSkill
- source-digestSkill
- source-evaluationSkill
- source-github-reposSkill
- source-official-blogSkill
- source-official-docsSkill
- source-package-internalsSkill
- source-papers-specsSkill
- source-talks-workshopsSkill
- source-universitySkill
- state-protocolSkill
- topic-extractionSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
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 16
Look for patterns: the same misunderstanding asked many times, errors with confusing messages, behaviour that surprised people, breaking …
- Distinctive: line 21
Prefer high-voted questions with an accepted answer that still holds for the pinned version.
- Distinctive: line 25
Don't record single issues.
≈ “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
Questions and problems (qa)
This hunter finds what goes wrong in practice. Its sources feed the "common mistakes" callouts in the notes and the experiments in the read-along. The role is almost always pitfalls.
GitHub issues and discussions
- The official repo is in
research/overview.md. codelabgen github issues <repo>saves the most-reacted issues as Markdown in the cache and prints the path. Read it. Narrow it down with--query, for example--query "label:question",--query "checkpointer", or the names of core concepts.codelabgen github issues <repo> --discussionsdoes the same for discussions (Q&A and ideas), if the repo uses them. Many projects keep their help forum elsewhere (a Discourse forum, Discord); search for it, and if it is public and indexable, treat it like Stack Overflow.- Look for patterns: the same misunderstanding asked many times, errors with confusing messages, behaviour that surprised people, breaking changes that hit many users.
Stack Overflow
- WebSearch
site:stackoverflow.com <topic> <concept>for the core concepts, or browse the tag (https://stackoverflow.com/questions/tagged/<tag>?tab=Votes). - Prefer high-voted questions with an accepted answer that still holds for the pinned version. Answers for older versions are still pitfalls ("this used to work"), but say so.
What to record
Don't record single issues. Record collections that are useful as a whole:
- the cached top-issues file as one source: url
https://github.com/<repo>/issues?q=sort%3Areactions-%2B1-desc, with areasonsummarizing the main recurring problems - a topic-specific issue search, when one concept clearly causes many problems
- the Stack Overflow tag, sorted by votes, and individual Q&As only when they are excellent explanations
- the official forum's FAQ or most-viewed threads
In reason, name the concrete pitfalls found, for example: "Recurring: msgpack serialization errors for custom state types; confusion between updates and values stream modes; thread_id missing from config."
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.

