yq-clear-context
Skill11 starsChanged 54 days agoMITView on GitHub
Use when writing or changing a model-facing tool definition (name, description, parameter schema, or its system-prompt section), and when designing skills, context loading, or multi-step workflows, to make information discoverable and use context efficiently.
In this repository57 other files it gives its agents.
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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 7
Make discovery explicit: every deferred resource needs a clear description and a reliable way to retrieve it.
- Distinctive: line 18
Say each fact once: Do not repeat the tool definition in its system-prompt section, a parameter description in the tool description, or one …
≈ “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
- Start with minimal context: expose purpose, available actions, and constraints first; load detailed instructions when needed.
- Make discovery explicit: every deferred resource needs a clear description and a reliable way to retrieve it.
- Keep critical constraints visible: permissions, destructive effects, and required validation should appear before the relevant action.
- Prefer bounded outputs: return concise results with identifiers or paths for retrieving details; avoid dumping entire logs or documents.
- Use locality: include a bounded amount of likely needed adjacent context with an operation’s result. For example, deliver a thread reply with a few preceding messages. Mark omissions and truncation explicitly, and provide a way to retrieve more.
- Evaluate total work: saving context is useful only if it does not cause more searches, repeated reads, or mistakes.
Tool definitions
- Delete obvious constraints. Omit rules the model learns from the call result, such as a missing file failing to read or a failed send not being delivered.
- Describe behavior, not implementation. State what the tool does and returns; omit internal mechanisms, output markers the model sees in results, and enforcement details.
- Put parameter rules on the parameter. Defaults, ranges, pairing, and when-to-set rules belong in that parameter's description or schema; a description that varies with configuration usually means the varying part belongs to a parameter.
- Say each fact once. Do not repeat the tool definition in its system-prompt section, a parameter description in the tool description, or one tool's rules in another tool.
- Measure the change. Compare first-turn prompt tokens before and after a tool-definition change.
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.

