agentsclimarketplace

Agent rules skill author

Skill ytvee-dev/webdev-agent-kit/skills/agent-rules-skill-author

Create, evaluate, or edit this .agents WebDev Agent Kit, including AGENTS.md, common/**, project/**, skills/**, metadata, validators, and progressive-disclosure rules.From its SKILL.md

Install
npx -y skills add ytvee-dev/webdev-agent-kit --skill agent-rules-skill-author

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

7.5 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it

Agent Rules And Skill Author

Purpose

Create or revise repo-local agent rules and .agents-compatible skill packages without leaking project-specific instructions into the wrong layer.

When To Use

  • The user asks to create, evaluate, rename, delete, or edit skills.
  • The user asks to change AGENTS.md, manifests, validators, common/**, project/**, or skills/**.
  • The user explicitly asks for user-facing README documentation changes.
  • The screenshot-to-frontend pipeline rules, tool contracts, or skill routing need maintenance.

When Not To Use

  • The user asks to write a design implementation spec from screenshots. Use design-screenshot-spec.
  • The user asks to implement a frontend layout from a spec. Use frontend-layout-implementer.
  • The user asks to visually verify rendered UI. Use frontend-visual-qa.
  • The user asks to adapt a new project in Plan Mode. Use project-onboarding-adapter.

Required Context

  1. Read AGENTS.md.
  2. Confirm the classified task is skill-documentation-refactor, documentation, or another .agents rule-maintenance task.
  3. Read common/documentation-maintenance.md.
  4. Read affected common/**, skills/**, project/**, manifests, validators, templates, examples, and root pointer files for the requested change.
  5. Apply common/readme-policy.md: read targeted README sections when the request concerns README, public setup guidance, or docs/implementation drift; verify technical claims through higher evidence.
  6. Read relevant references from this skill only when their topic is in scope.
  7. Read current OpenAI Codex docs when native skill behavior, AGENTS.md, MCP, plugins, or agents/openai.yaml behavior may have changed.

Tool Contract

  • Use filesystem reads and targeted search for local bundle facts.
  • Activate openai_platform_docs when current OpenAI or Codex behavior affects the change; follow common/codex-official-docs-policy.md.
  • Use context7 and mdn only when authoring rules depend on current framework or web platform behavior.
  • Do not use Figma MCP for this bundle.

Workflow

  1. Classify the target layer: AGENTS.md, manifests, validators, common/**, project/**, templates/**, examples/**, or skills/**.
  2. Treat README as optional human-facing context, never runtime policy or validator truth. Do not edit it unless the current user explicitly requests that README change.
  3. Confirm whether a new skill is needed or an existing skill/reference/common rule should be edited.
  4. Define trigger surface, non-trigger cases, inputs, outputs, defaults, tool contract, failure modes, and validation gates.
  5. Keep skill packages in the standard section order used by this bundle.
  6. Keep graph frontmatter and Codex UI/invocation metadata synchronized; keep capability declarations in tool-capabilities-manifest.json.
  7. Remove stale links after renames or deletions.
  8. Validate changed skill packages and run documentation checks.

Output Contract

Final response: return only facts that affect the user's understanding, confidence, or next action. Omit empty fields and workflow narration.

Report:

  • files changed;
  • skill routing or trigger changes;
  • tool dependency changes;
  • validation performed;
  • unresolved risks or blocked checks.

Validation Gates

  • name and description stay first in SKILL.md frontmatter.
  • Every skill has Purpose, When To Use, When Not To Use, Required Context, Tool Contract, Workflow, Output Contract, Validation Gates, Trigger Evals, and Reference Map.
  • New references are linked from the owning SKILL.md.
  • agents/openai.yaml matches skill UI and invocation policy. Only true hard client-tool dependencies belong there; optional providers belong in the capability manifest.
  • No Figma MCP or Figma whiteboard workflow is introduced.
  • README is not used as runtime policy, routing input, validator truth, or sole technical evidence, and is not edited without an explicit current user request.

Trigger Evals

Should trigger:

  • "Create a new skill for visual QA."
  • "Audit and rewrite the .agents skill routing."
  • "Update AGENTS.md, manifests, and graph links for renamed skills."

Should not trigger:

  • "Implement this Design Implementation Spec."
  • "Compare the rendered page to the screenshot."
  • "Write a layout spec from these screenshots."

Authoring Mode

Default to the source-bundle contract: native name and description plus local graph metadata. Use strict native-portable frontmatter only when the user explicitly requests a standalone skill outside this bundle.

Before material skill changes:

  1. Use references/skill-design.md to choose the smallest correct intervention and package shape.
  2. Use references/trigger-and-metadata.md to align the description, invocation policy, and agents/openai.yaml.
  3. Use references/skill-quality-rubric.md for trigger and workflow evals.
  4. Use references/rules-writing.md when policy scope or precedence changes.
  5. Use references/documentation-maintenance.md for graph, manifest, rename, or publication changes.
  6. Use references/validation-checklist.md before final reporting.

For new skills, use the local scaffolder only after the workflow, resources, compatibility target, and trigger boundary are defined. Keep examples and scripts only when they implement repeatable behavior.

Reference Map

  • references/codex-native-skill-contract.md
  • references/rules-writing.md
  • references/skill-design.md
  • references/skill-quality-rubric.md
  • references/trigger-and-metadata.md
  • references/validation-checklist.md
  • common/readme-policy.md
  • common/codex-official-docs-policy.md
  • references/figma-derived-conventions.md
  • references/source-backed-prompting.md
  • references/documentation-maintenance.md

What ships with it: 15 files

68.2 KB alongside SKILL.md, 4 of them executable

agents/

Gives 0 of the 12 instructions most context ai engineering skills give in ~1.3k tokens

Counted across 1,328 of the 2,349 authors here whose files we hold, read 2026-09-06

  • Dispatch a fresh subagent for each taskin 76 of 1328, across 59 files
  • Perform spec compliance review before code quality reviewin 44 of 1328, across 34 files
  • Dispatch a final code reviewer after all tasksin 38 of 1328, across 26 files
  • Answer subagent questions before allowing implementationin 36 of 1328, across 26 files
  • Use the least powerful model capable of the taskin 33 of 1328, across 26 files
  • Create a TodoWrite list for all tasksin 32 of 1328, across 22 files
  • Perform a task review after each implementationin 31 of 1328, across 24 files
  • Extract all tasks and context from the planin 29 of 1328, across 20 files
  • Provide full task text to subagentsin 28 of 1328, across 20 files
  • Use git worktrees for isolated workspacesin 25 of 1328, across 20 files
  • Specify the model explicitly when dispatching a subagentin 23 of 1328, across 18 files
  • Execute all tasks from the plan without stoppingin 21 of 1328, across 16 files

Said here and by no other author read

  • Classify the target layer before editing
  • Keep skill packages in standard section order
  • Synchronize graph frontmatter and Codex metadata
  • Remove stale links after renames or deletions
  • Validate changed skill packages
  • Run documentation checks

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.