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Skill Discovery SEO

Improve a skill package so AI agents can find, select, and trust it across registries and ecosystems, including Codex, Claude-style agents, OpenClaw, and oth...
优化技能包,使AI智能体能够在Codex、Claude风格智能体、OpenClaw等各类注册表和生态系统中便捷发现、选择并信任该技能包。
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#agent-registry#agent-tools#discoverability#latest#metadata#prompt-design#search#semantic-retrieval#skill-seo

概述

Skill Discovery SEO

Overview

Improve a skill's discoverability for both humans and AI agents. Focus on triggerable names, dense metadata, realistic example prompts, clear scope, and packaging decisions that help registries and meta-skills choose the right skill reliably.

Load references/discoverability-guide.md before rewriting metadata or publish copy.

Workflow

1. Identify the discovery surface

Check which fields the registry or agent ecosystem will likely index:

  • skill name
  • frontmatter description
  • display_name
  • short description
  • default prompt
  • tags or categories
  • example prompts
  • listing copy or repository summary

If the platform is unknown, assume most systems use a mix of exact text match, semantic retrieval, and usage or trust signals.

2. Tighten the trigger language

Rewrite the discovery fields so they answer four questions fast:

  • what domain is this for
  • what job does it do
  • what inputs does it accept
  • what output or decision does it produce

Prefer literal wording over branding, slogans, or clever titles.

3. Expand query coverage without bloating

Include the main phrases a user or agent would search for:

  • primary nouns such as platform, artifact, or file type
  • major verbs such as review, check, create, revise, deploy, or analyze
  • important synonyms such as policy and compliance, or caption and script
  • edge-case phrases only if the skill truly handles them

Do not keyword-stuff. Add only terms that improve routing accuracy.

4. Check trust and scope

Make sure the skill:

  • has a narrow, believable scope
  • states boundaries clearly
  • promises outputs it can actually deliver
  • avoids agent-specific assumptions unless truly required

If the skill claims too much, narrow it until another agent could select it confidently.

5. Produce a publish-ready pack

Return:

  • recommended skill name
  • frontmatter description
  • display_name
  • short description
  • default prompt
  • optional tags
  • 3 to 8 realistic example prompts
  • one short note on what not to claim in the listing

Output Rules

  • Keep names literal, ASCII-safe, and easy to type.
  • Put the highest-signal trigger terms early in the description.
  • Match the wording users would naturally use, not internal jargon.
  • Keep agent-specific wording out of general-purpose skills unless the skill is actually tied to one ecosystem.
  • Prefer one strong promise over many weak ones.

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-30 22:27 安全 安全

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