progressive-disclosure-agents-md
Design, review, or create progressive-disclosure and layered AGENTS.md instruction systems for agentic coding workflows.
Skill by minfengyuan
Chalk Labs
Need help deploying progressive-disclosure-agents-md?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/minfengyuan-progressive-disclosure-agents-md
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: design, security, productivity, agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/progressive-disclosure-agents-md
What's inside
- Skill name
progressive-disclosure-agents-md- Description
- Design, review, or create progressive-disclosure and layered AGENTS.md instruction systems for agentic coding workflows. Use when Codex needs to organize root and nested AGENTS.md files, route context by directory or task, split always-needed guidance from conditional docs, audit agent instructions for context bloat or conflicts, or help with AGENTS.md, agent instructions, progressive disclosure, layered instructions, 分层 AGENTS.md, 渐进式披露, or 多层代理说明.
- License
- MIT
- Instructions
- 43 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- agents-md-patterns.md · references/
SKILL.md (first lines)
# Progressive Disclosure AGENTS.md Design `AGENTS.md` systems that keep global instructions compact and route agents to deeper context only when a task needs it. Optimize for discoverability, low context cost, and clear precedence among explicit user requirements, reusable Skill workflows, root instructions, nested instructions, and referenced guidance. ## Workflow 1. Inventory the repository shape, agent audiences, recurring task types, and domains that need special handling. 2. Separate always-needed rules from conditional guidance. Keep root `AGENTS.md` for universal behavior, setup, safety, authority boundaries, and routing. 3. Choose layers deliberately: - Use root `AGENTS.md` for repo-wide principles, common commands, definitions of done, and context routing. - Use nested `AGENTS.md` when instructions apply to every file under a directory and should refine or explicitly override parent guidance. - Use `agent_docs/` or similar references for long domain guides that should be read only for matching task types. - Use skills when the workflow is reusable across repositories or needs bundled references, scripts, or assets. 4. Write explicit routing conditions. Prefer "If touching data loading, read `agent_docs/data_pipeline.md`" over vague instructions such as "read relevant docs." 5. Audit precedence and stopping behavior. Ensure a generic Skill workflow does not accidentally override an explicit user request or create an extra approval gate, while higher-priority safety and permission boundaries remain intact. 6. Validate that no required context is hidden in optional docs, no layer conflicts silently with another, and the root file stays short enough to scan. ## Design Rules - Keep the first screen of root `AGENTS.md` useful without additional reads. - Put precedence and authority rules near the top when the repository combines reusable Skills with layered instructions. - Route by task intent, directory, file type, or risk area. Avoid routing by broad labels the agent cannot reliably infer. - Make every routed document answer: when to read it, what it governs, and what decisions it should not change. - Avoid duplicating the same rule across layers. Put shared rules higher; put exceptions lower. - Recast broad ask/confirm/stop rules around the material decision or risk that actually requires user input. - Make verification and delegation proportional to the work unless a concrete repository gate requires otherwise. - Preserve public APIs, schemas, defaults, and behavior unless the user explicitly asks for changes. ## Output Shape When creating or revising an instruction system, produce only the artifacts and analysis needed for the request. Commonly useful outputs are: - A proposed root `AGENTS.md` structure. - Nested `AGENTS.md` locations and their exact scope. - Reference docs to add, with read conditions. - A conflict, precedence, approval-gate, and context-bloat review. - Validation prompts covering a small action, a subsystem-specific task, a consequential decision, and any important Skill interaction. ## Reference Read `references/agents-md-patterns.md` when concrete templates, anti-patterns, or a review checklist would materially help.
From minfengyuan/harness-knowledge-base, MIT.
More from minfengyuan/harness-knowledge-base
- 0.589score
tailscale-api
Hermes Agent
Tailscale REST API v2 (api.tailscale.com/api/v2) — devices, keys, ACL, DNS, webhooks, OAuth scopes.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
dev-mode
minfengyuan
Coordinate the project's seven specialized agents through planning, execution, review, debugging, and final acceptance for substantial software-development…
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
conventional-branch-naming
minfengyuan
Generate one descriptive Git branch name from a task using Conventional Commits 1.0.0 types.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
clarifying-requirements
minfengyuan
Turn vague ideas or requirements into a shared, actionable brief through iterative questions and confirmation.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
tailscale-cli
minfengyuan
Complete tailscale CLI usage — all subcommands, flags, and common workflows (v1.96+)
SkillAFreshness: A★ 1Claude Code +9 - 0.552score
photo-illustration-styles
minfengyuan
Photo-to-illustration style transfer.
SkillBFreshness: B★ 1Claude Code +9 - 0.552score
optimize-astra-instructions
minfengyuan
Audit or revise Skills, AGENTS.md files, and agent task prompts specifically for GPT-6 Astra.
SkillBFreshness: B★ 1Claude Code +9 - 0.549score
pi-coding-agent
minfengyuan
Guides agents using Pi coding-agent: install, authenticate, run, configure, automate, and extend the pi CLI.
SkillBFreshness: B★ 1Claude Code +9 - 0.548score
recipe-formatter
minfengyuan
将用户提供的菜谱文字或明确要求保存的菜谱整理为结构化 Obsidian 菜谱,自动分类并打标签。Use when the user wants recipe text formatted, normalized, tagged, or saved as a recipe note.
SkillBFreshness: B★ 1Claude Code +9 - 0.547score
plan-ceo-review
minfengyuan
Use when a user wants product-level review of a plan, especially to challenge scope, ambition, and user value before implementation
SkillBFreshness: B★ 1Claude Code +9 - 0.547score
conventional-commits
minfengyuan
Generate Conventional Commits 1.0.0 messages from staged git changes.
SkillBFreshness: B★ 1Claude Code +9 - 0.546score
tdd
minfengyuan
Use when the user requests test-driven development, red-green-refactor, integration tests, or a test-first bug fix.
SkillBFreshness: B★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 23, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from minfengyuan
- 0.587score
dev-mode
minfengyuan
Coordinate the project's seven specialized agents through planning, execution, review, debugging, and final acceptance for substantial software-development…
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
clarifying-requirements
minfengyuan
Turn vague ideas or requirements into a shared, actionable brief through iterative questions and confirmation.
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
conventional-branch-naming
minfengyuan
Generate one descriptive Git branch name from a task using Conventional Commits 1.0.0 types.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
tailscale-cli
minfengyuan
Complete tailscale CLI usage — all subcommands, flags, and common workflows (v1.96+)
SkillAFreshness: A★ 1Claude Code +9 - 0.552score
photo-illustration-styles
minfengyuan
Photo-to-illustration style transfer.
SkillBFreshness: B★ 1Claude Code +9 - 0.552score
optimize-astra-instructions
minfengyuan
Audit or revise Skills, AGENTS.md files, and agent task prompts specifically for GPT-6 Astra.
SkillBFreshness: B★ 1Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get progressive-disclosure-agents-md running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
progressive-disclosure-agents-md skill. Agent Mart. https://agentmart.dev/skills/minfengyuan-progressive-disclosure-agents-md (last updated 2026-10-24)