agent-context
Skill3 starsChanged 37 days agoMITView on GitHub
Retrieve concise, graph-backed design context from AI Design Context with the local CLI. Use before implementing or reviewing a user-facing flow, reference fixture, prompt output, or known knowledge object when an agent needs relevant research, rules, patterns, checklists, and evidence limits without reading every index.
5 other projects use a version of this.
Adopted by
Most recently taken up by
- amaranthic/skillstheir own version, first seen Oct 20, 2026
- cote-star/agent-contexttheir own version, first seen Oct 15, 2026
- kimgea/agent-kittheir own version, first seen Oct 15, 2026
- cote-star/agent-chorustheir own version, first seen Sep 28, 2026
- InnovationMachineTeam/skillstheir own version, first seen Aug 1, 2026
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 5
- cote-star/agent-chorus★ 14same name
- cote-star/agent-context★ 2same name
- amaranthic/skills★ 1same name
- InnovationMachineTeam/skills★ 1same name
- kimgea/agent-kit★ 0same name
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 repository21 other files it gives its agents.
- AGENTS.mdAGENTS.md
- starter-kit/AGENTS.mdAGENTS.md
- accessibility-checkSkill
- accessibility-reviewerSkill
- design-evidence-researcherSkill
- design-reviewerSkill
- design-system-architectSkill
- design-understandSkill
- information-architectSkill
- interaction-designerSkill
- knowledge-graph-architectSkill
- mobile-ux-expertSkill
- motion-designerSkill
- performance-reviewerSkill
- product-designerSkill
- prompt-architectSkill
- reference-driven-designSkill
- responsive-checkSkill
- ux-reviewerSkill
- visual-designerSkill
- visual-qaSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
3
Distinctive
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
Run this skill before a user-facing implementation or review when the applicable knowledge is not already explicit.
- Distinctive: line 23
Read the selected files before proposing product guidance or code.
- Distinctive: line 26
If the resolver returns no match, create an observation or research need rather than inventing a rule.
- Very specific: line 33
Use --format json for another agent or script.
“Common” is measured: kept by at least 6 in 10 of the 5 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
Agent Context
Run this skill before a user-facing implementation or review when the applicable knowledge is not already explicit.
Workflow
- In a product repository with the npm package installed, verify
npx --no-install ai-design-context context --help. In the knowledge-source checkout, usenpm run context -- --help. Resolve the task, review target, or stable object:
npm run context -- --task quick-capture --platform mobile --intent implement --format json npm run context -- --review examples/todo-reference --intent qa npm run context -- --object PAT-00002 --format jsonFor the installed npm package, replace
npm run context --withnpx --no-install ai-design-context contextin these examples. Markdown provides absolute reading paths; JSON addsabsolutePathwhile retaining relative graphpath.- Read the selected files before proposing product guidance or code.
- Apply only the returned rules and patterns that fit the task.
- Preserve every returned evidence boundary;
draftandseeddo not justify broad product claims. - If the resolver returns no match, create an observation or research need rather than inventing a rule.
- Inspect each object's selection reason. Required dependencies are complete, while optional links in broad review gates must be followed explicitly when the review needs them.
Boundaries
- The CLI is read-only and does not replace
npm run check. --platformadds relevant context; it does not prove that a pattern applies.- Use
--format jsonfor another agent or script; errors are machine-readable on stderr. - Task matching is lexical. Simple English task wrappers are supported; arbitrary paraphrases and translation are not. Prefer an exact known slug or ID when available.
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
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- 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.

