agent-discovery
Optimize websites, docs, and product surfaces for agent discoverability and operator UX. Use when working on agent SEO/AEO/GEO, crawl policy, markdown or JSON projections, llms.txt, sitemap.md, AGENTS.md guidance, content negotiation, accessibility for browser agents, or any request to make a site easier for pi, OpenCode, Claude Code, ChatGPT, Perplexity, or other agent harnesses to find and use.
What this skill does
# Agent Discovery
This skill is about an opinionated blend of **traditional SEO**, **static truth in the initial response**, and **UX ergonomics for agents and operators**.
Don't reduce this to "AI SEO".
If a page can't be crawled, cited, parsed, navigated, or actioned by an agent harness, it is broken in a way normal SEO reports won't fully show.
## Thesis
Treat agent discoverability as four stacked layers:
1. **Search baseline** — crawlable pages, clean robots policy, sitemap, structured data, canonical answers, freshness.
2. **Initial-response truth** — the important facts must be present in the first HTML response.
3. **Machine-readable projections** — markdown/text/JSON surfaces that project the same canonical resource without drift.
4. **Operator ergonomics** — the site should be easy to drive from pi, OpenCode, Claude Code, ChatGPT, or a browser agent without guesswork.
If layer 1 is broken, you won't get found.
If layer 2 is broken, agents won't extract the truth.
If layer 3 is broken, harnesses waste tokens scraping HTML.
If layer 4 is broken, operators and browser agents hit dead ends.
## When to Use
Use this skill when the task mentions:
- agent SEO / AEO / GEO / LLM SEO / AAIO
- agent discoverability
- optimize site for ChatGPT / Claude / Perplexity / Copilot
- llms.txt / sitemap.md / markdown endpoints / content negotiation
- AGENTS.md / coding-agent docs / operator docs
- agent-friendly docs / machine-readable docs
- browser-agent UX / agent automation / accessible automation
- making a website easier for agent harnesses to use
## Core Rules
### 1. Do the boring SEO work first
Before fancy protocols, verify:
- `robots.txt` allows the crawlers you actually want
- sitemap exists and stays current
- pages that should never rank use `noindex`
- titles, descriptions, H1s, and headings agree on the topic
- JSON-LD matches visible content exactly
- author/date/source signals are visible where trust matters
- stale pages get refreshed, redirected, or archived
Useful mental model from the audit side:
1. crawlability and indexation
2. technical foundations
3. on-page clarity
4. content quality / trust
5. authority / citations / mentions
### 2. Initial HTML is the truth surface
The important facts must survive:
- `curl`
- a text browser
- no-JS mode
- cheap retrieval pipelines
Don't hide core facts behind:
- client-only fetches
- tabs and accordions with empty initial HTML
- modal-only disclosures
- images or PDFs with no HTML equivalent
- click handlers on `div`s pretending to be controls
Static rendering is a principle, not a framework fetish.
A static shell with small dynamic holes is fine.
A blank SPA shell is dogshit for both search and agents.
### 3. One resource, multiple truthful projections
Give the same resource multiple machine-friendly shapes:
- human page → `text/html`
- markdown twin or negotiated markdown → `text/markdown`
- API / structured route → `application/json`
- text hint surface (`llms.txt`, index text) → `text/plain`
The rule is **projection, not duplication**.
Do not maintain three separate truths for HTML, markdown, and JSON.
Project them from one canonical content source.
### 4. `llms.txt` is a hint surface, not a ranking hack
Use `llms.txt` or similar text hints as:
- a fast discovery point
- a cheap orientation surface
- a pointer to better machine-readable endpoints
Do **not** claim it boosts ranking by itself.
Google has been explicit: AI discovery does not require special AI-only markup.
### 5. AGENTS.md beats hoping skills trigger
For coding-agent surfaces, persistent repo context matters more than wishful tool invocation.
Vercel's evals are useful here:
- skills alone underperformed for general framework guidance
- explicit instructions improved triggering, but wording was fragile
- compressed `AGENTS.md` / repo-instruction context won for broad, always-on guidance
Use:
- **AGENTS.md** for persistent repo rules, paths, commands, retrieval hints
- **skills** for vertical, action-specific workflows
That split matters for pi, OpenCode, and Claude Code.
### 6. Accessibility is agent UX
Browser agents and automation stacks lean on the accessibility tree.
Prefer:
- real `<a>` links with `href`
- real `<button>` elements
- labels on form controls
- `autocomplete` where data entry matters
- proper landmarks and heading hierarchy
- explicit UI state (`aria-expanded`, `role=status`, `aria-live`)
If Playwright can't find it by role or label, an agent harness will likely struggle too.
### 7. Operator UX matters too
An operator using an agent harness should not need to reverse-engineer your product.
Good patterns:
- stable, guessable URLs
- obvious markdown twins or negotiated markdown
- copyable commands and prompts
- JSON responses that advertise next steps (`next_actions` / affordances)
- machine-readable discovery routes (`/api`, `/sitemap.md`, etc.)
- deterministic MIME types
Bad patterns:
- opaque blobs of JSON with no next move
- downloadable markdown buried behind UI chrome
- hidden routes that only work if you already know them
- HTML fallback pretending to be markdown
- "click around and figure it out" operator flows
## joelclaw Implementation Map
When you need concrete evidence, start here.
### Crawl + discovery surfaces
- `apps/web/app/robots.ts`
- allows crawl globally and advertises both XML and markdown sitemaps
- `apps/web/app/sitemap.md/route.ts`
- markdown discovery index with posts, ADRs, feeds, and `.md` twins
- `apps/web/app/llms.txt/route.ts`
- plain-text hint surface pointing agents to `sitemap.md`, `feed.xml`, and markdown access
### Markdown projections
- `apps/web/proxy.ts`
- canonicalizes `/{slug}.md` and rewrites to the markdown route handler
- `apps/web/app/[slug]/md/route.ts`
- renders real `text/markdown; charset=utf-8`
- prepends agent context
- rewrites internal links to other `.md` twins
### Structured discovery + navigation
- `apps/web/app/api/route.ts`
- API discovery endpoint with `nextActions`
- `apps/web/app/api/search/route.ts`
- HATEOAS JSON search envelope with markdown snippets
- `apps/web/components/clawmail-source-comment.tsx`
- source-visible navigation prompt telling agents which endpoints to hit and what MIME types to verify
### Trust + rendering truth
- `apps/web/app/[slug]/page.tsx`
- cached article shell, JSON-LD injection, visible metadata, copy-for-agent affordance
- `apps/web/lib/jsonld.ts`
- BlogPosting / Blog / Person / BreadcrumbList helpers
- `apps/web/lib/posts.ts`
- Convex-canonical content reads; HTML/markdown projections come from one source
- `apps/web/components/copy-as-prompt.tsx`
- operator-facing affordance to grab a prompt directly into a harness
### Static rendering example, not doctrine
- `apps/web/next.config.ts`
- `cacheComponents: true`
- `apps/web/app/[slug]/page.tsx`
- `'use cache'`, `cacheLife`, `cacheTag` for fast static shells with truthful invalidation
Use those as examples of the principle:
- cached shell
- canonical source
- small dynamic seams
- honest machine projections
Not as a claim that Next.js is the only valid way.
## Verification Checklist
### Crawl + indexing
```bash
curl -s https://example.com/robots.txt
curl -I -A 'OAI-SearchBot/1.3' https://example.com/
curl -I -A 'Googlebot' https://example.com/
```
Check Search Console and Bing Webmaster Tools too.
### Initial-response truth
```bash
curl -sL https://example.com/page | rg -n 'important fact|<h1>|<table>|application/ld\+json'
lynx -dump https://example.com/page
```
If `curl` cannot see the fact, many agents will not either.
### Markdown / text / JSON projections
```bash
curl -I https://example.com/sitemap.md
curl -I https://example.com/page.md
curl -sS https://example.com/api | jq
```
Verify exact MIME types:
- `text/markdown; charset=utf-8`
- `text/plain; charset=utf-8`
- `application/json; charset=utf-8`
If a markdown route returns `text/html`, treat it as broken.
### AcRelated in Ads & Marketing
ads
IncludedMulti-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Ads. 250+ checks with scoring, parallel agents, industry templates, and AI creative generation.
banana
IncludedAI image generation Creative Director powered by Google Gemini Nano Banana models. Use this skill for ANY request involving image creation, editing, visual asset production, or creative direction. Triggers on: generate an image, create a photo, edit this picture, design a logo, make a banner, visual for my anything, and all /banana commands. Handles text-to-image, image editing, multi-turn creative sessions, batch workflows, and brand presets.
rpg-migration-analyzer
IncludedAnalyzes legacy RPG (Report Program Generator) programs from AS/400 and IBM i systems for migration to modern Java applications. Extracts business logic from RPG III/IV/ILE source code, identifies data structures (D-specs), file operations (F-specs), program dependencies (CALLB/CALLP), and converts RPG constructs to Java equivalents. Generates migration reports, complexity estimates, and Java implementation strategies with POJO classes, JPA entities, and service methods. Use when modernizing AS/400 or IBM i legacy systems, analyzing RPG source files (.rpg, .rpgle, .RPGLE), converting RPG to Java, mapping data specifications to Java classes, planning legacy system migration, or when user mentions RPG analysis, Report Program Generator, RPG III/IV/ILE, AS/400 modernization, IBM i migration, packed decimal conversion, or mainframe application rewrite.
brand-library-architect
IncludedBuild a complete brand library for a product — visual asset render pipeline, brand documentation set (BRAND, COPY, MANIFESTO, BIOS, FAQ, GLOSSARY, TONE, PRICING), open-source convention files (README, CONTRIBUTING, SECURITY, CODE_OF_CONDUCT), and a self-contained press kit. This skill should be used when the user asks to "build a brand library / brand kit / press kit / brand assets" for a product, "set up a brand library workflow," "create a positioning manifesto plus visual identity," or any combination of brand documentation + visual asset pipeline. Apply phase-by-phase or run end-to-end. Templates are product-agnostic and use {{TOKEN}} placeholders the skill prompts the user to fill.
writing-tech-post
IncludedAuthors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces an evidence cadence (diagrams, benchmarks, profiles, traces, code, ablations), tunes voice against publisher house styles (Datadog, Vercel, GitHub, AWS, Meta, Cloudflare, Jane Street), and runs a pre-publish gate for narrative momentum and disclosure ethics. Use when drafting a new engineering post, restructuring a draft that feels flat, deciding which evidence form belongs where, validating that depth and product context are balanced, or preparing a postmortem, migration, or performance narrative for external publication. Do not use for API reference documentation, README authoring, marketing copy, release notes, generic SEO content, ghost-written executive thought leadership, or non-engineering long-form essays.
blog-google
IncludedGoogle API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".