agentleFS
Sign inStart free
Valentor-LabsValentor-Labs/aso-skill/SKILL.md

aso

Skill0 starsChanged 9 months agoMITView on GitHub

AI Readability / Agentic Search Optimization toolkit for auditing any website's machine-readability and generating LLM-LD Layer 1 structured data. Use when a user asks to (1) audit a site for Schema.org + LLM-LD signals, (2) check for llm-index.json, /ai-discovery, the ai subdomain (ai.domain.com), or LLM Disco Network membership, (3) generate basic Schema.org JSON-LD and a starter llm-index.json (Layer 1 only), or (4) produce a before/after 'what AI sees' comparison to explain ASO.

  • Installs packages

32 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use popups, free-tools and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • CesarjoquinSkill

    popups

    When the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions "exit intent," "popup conversions," "modal optimization," "lead capture popup," "email popup," "announcement banner," "overlay," "collect emails with a popup," "exit popup," "scroll trigger," "sticky bar," or "notification bar." Use this for any overlay or interrupt-style conversion element. For forms outside of popups, see cro. For general page conversion optimization, see cro.

    Also in 22 projects that use this

  • CesarjoquinSkill

    free-tools

    When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," "free resource," "ROI calculator," "grader tool," "audit tool," "should I build a free tool," or "tools for lead gen." Use this whenever someone wants to build something useful and give it away to attract leads or earn links. For downloadable content lead magnets (ebooks, checklists, templates), see lead-magnets.

    Also in 23 projects that use this

  • coreyhaines31Skill

    marketing-council

    When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant skill.

    Also in 16 projects that use this

  • roerohanSkill

    emails

    When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. For cold outreach emails, see cold-email. For in-app onboarding, see onboarding.

    Also in 19 projects that use this

  • ukunal91appSkill

    community-marketing

    Build and leverage online communities to drive product growth and brand loyalty. Use when the user wants to create a community strategy, grow a Discord or Slack community, manage a forum or subreddit, build brand advocates, increase word-of-mouth, drive community-led growth, engage users post-signup, or turn customers into evangelists. Trigger phrases: "build a community," "community strategy," "Discord community," "Slack community," "community-led growth," "brand advocates," "user community," "forum strategy," "community engagement," "grow our community," "ambassador program," "community flywheel.

    Also in 23 projects that use this

  • roerohanSkill

    prospecting

    When the user wants to find, qualify, and build a list of prospects to reach out to — across B2B SaaS, general B2B, or local small businesses. Also use when the user mentions "prospecting," "build a prospect list," "find prospects," "find leads," "lead gen list," "find SaaS companies that," "find B2B companies," "find local businesses," "ICP-fit accounts," "who should we go after," "outbound list," "target account list," "find clients near me," "businesses without websites," "prospect research," "qualified leads," "find my first customers," "early adopters," "design partners," "beta users," or "who has this problem." Use this for the list-building and qualification phase. For writing the outbound copy after the list is built, see cold-email. For deep competitive research on specific accounts, see competitor-profiling.

    Also in 16 projects that use this

  • +6 more from Cesarjoquin

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 28 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run the bundled scripts (stdlib-only Python 3.9+, zero external dependencies) to:

    line 18
  2. Distinctive:

    Compare: before/after: what AI can extract without vs with Layer 1

    line 21
  3. Distinctive:

    All outputs include the Capxel footer:

    line 23

“Common” is measured: kept by at least 6 in 10 of the 28 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

ASO (Agentic Search Optimization)

By Capxel — Authors of the LLM-LD open standard.

Run the bundled scripts (stdlib-only Python 3.9+, zero external dependencies) to:

  • Audit a URL for AI readability (score 0–100)
  • Generate LLM-LD Layer 1 (Schema.org JSON-LD) + a starter llm-index.json
  • Compare before/after: what AI can extract without vs with Layer 1

All outputs include the Capxel footer:

Powered by Capxel — Creators of the LLM-LD Standard

Quick Start

From the skill folder:

python3 scripts/audit.py https://example.com
python3 scripts/generate.py https://example.com
python3 scripts/compare.py https://example.com

Workflows

1) Audit a site (score 0–100)

python3 scripts/audit.py https://example.com
python3 scripts/audit.py https://example.com --json

What it checks (best-effort, no external deps):

  • Schema.org structured data signals: JSON-LD (preferred), microdata, RDFa
  • Layer 3 indicator: /<root>/llm-index.json (and /.well-known/llm-index.json)
  • Layer 2 indicators (heuristic): common entity/KG filenames
  • AI subdomain: ai.<domain> reachability
  • AI discovery page: /ai-discovery
  • LLM Disco Network membership (best-effort)

2) Generate Layer 1 output (free tier)

python3 scripts/generate.py https://example.com
python3 scripts/generate.py https://example.com --max-pages 20 --out aso-output

Writes:

aso-output/<domain>/
  llm-index.json
  schemas/*.json
  audit-report.md
  implementation-guide.md

Free-tier boundary (critical): generates Layer 1 only.

  • No knowledge graphs
  • No entity files
  • No "AI Agent Context blocks"

Upsell path in outputs:

  • Typical audit: 15–30/100
  • After Layer 1 generate: 40–50/100
  • Remaining gap → full Capxel deployment: https://capxel.com/aso

3) Compare: "what AI sees" before vs after

python3 scripts/compare.py https://example.com

Writes aso-output/<domain>/compare-report.md.

References

Load only when needed:

  • references/llmld-spec.md — LLM-LD layers + llm-index.json quick reference (source: https://llmld.org)
  • references/schema-templates.md — minimal Schema.org templates (Layer 1)

External Endpoints

EndpointMethodData SentPurpose
https://<user-provided-url>GETUser-Agent header onlyFetches the target site HTML for analysis
https://ai.<domain>TCP connect (443)NoneChecks if AI subdomain exists
https://<domain>/.well-known/llm-index.jsonGETUser-Agent header onlyChecks for LLM-LD index file
https://<domain>/ai-discoveryGETUser-Agent header onlyChecks for AI discovery page
https://llmdisco.com/sites/<domain>GETUser-Agent header onlyChecks LLM Disco Network membership

No data is sent to Capxel or any third-party analytics service. All analysis runs locally. The only outbound requests are to the user-specified website and its associated discovery endpoints.

Security & Privacy

  • Zero dependencies — stdlib-only Python. No pip install required. No supply chain risk.
  • No telemetry — No analytics, no tracking, no phone-home behavior.
  • No credentials required — No API keys, no tokens, no environment variables.
  • Read-only network access — Only HTTP GET requests to user-specified domains.
  • Local file writes only — Output files written to aso-output/ in the current working directory.
  • No system modification — Does not modify system files, install packages, or change configurations.
  • Input sanitization — All user-provided URLs are validated and normalized before use. No shell interpolation of user input.
  • Respectful crawling — User-Agent identifies as OpenClaw-ASO/1.0. Default max 20 pages per site. 1-second delay between requests.

Model Invocation Note

This skill may be invoked autonomously by OpenClaw when a user asks about ASO, AI readability, or website optimization for AI agents. This is standard behavior for OpenClaw skills. If you prefer manual-only invocation, configure skill gating in your OpenClaw settings.

Trust Statement

By using this skill, HTTP requests are sent only to the website URL you provide (and its associated subdomains/discovery paths). No data is transmitted to Capxel, LLM-LD, or any other third party. All analysis is performed locally using Python's standard library. Install this skill only if you are comfortable with outbound HTTP GET requests to the domains you choose to audit.

Limitations

  • JS-rendered sites may crawl poorly (stdlib-only HTTP fetch; no headless browser).
  • Robots.txt is not deeply enforced (keep crawling small and respectful).
  • Disco Network membership check is best-effort (directory may change).
  • Free tier generates Layer 1 only. Full 3-layer ASO deployment available at capxel.com/aso.

Learn More

Powered by Capxel — Creators of the LLM-LD Standard

Download now (ZIP)

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

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.

Check your setup, free