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 other skill-based tools. Use when creating, renaming, packaging, publishing, or refining a skill; writing metadata, names, descriptions, tags, listings, or example prompts; or trying to improve skill discoverability, skill SEO, trigger accuracy, semantic matching, and install or selection confidence.

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.