Agents

Layer ships agent skills as files, in the hev/layer repository. They are plain SKILL.md documents with YAML frontmatter — no harness-specific format and nothing to install beyond putting the directory where your agent looks.

git clone https://github.com/hev/layer.git

Skill	Use it for
hevlayer-search-app	Building a search application: schema design, connecting a source, chunking, indexing, querying, generating the UI.
hevlayer-docs	Answering Layer questions from the docs instead of from memory.
hevlayer-layer-cli	Driving the layer CLI — environments, indexes, pipelines, install.

hevlayer-search-app also carries store-capabilities.md, a generated table of which wire features each backend serves — the answer to “can I do this?”, so an agent reads coverage instead of guessing and hitting a 422 UnsupportedByStore.

Install the skills

Claude Code picks the skills up from a clone with no setup: .claude/skills/ in the repository links to skills/.

For any other harness that reads a skill directory:

scripts/install-skills.sh

That copies the skills into $AGENT_SKILL_HOME, defaulting to ${CODEX_HOME:-~/.codex}/skills. Point it elsewhere with the variable:

AGENT_SKILL_HOME=~/.config/my-agent/skills scripts/install-skills.sh

If your harness has no skill directory, paste the body of a SKILL.md into AGENTS.md or the equivalent. The files are written to work either way. The repository’s own AGENTS.md is the starting point.

Query the docs from the command line

These docs are queryable from the command line. The same engine behind the ⌘K search on this site ships as a CLI, so your coding agent can search, read, and cite the Layer docs directly — no scraping, no MCP server, no API key. This is what hevlayer-docs drives. The layer CLI, which hevlayer-layer-cli drives, also lets agents operate environments, indexes, pipelines, UDFs, and Function runs.

go install github.com/hev/ask/cmd/ask@latest

The ask binary is self-contained; any agent harness that can run a shell command can use it.

From a Layer checkout, build the layer CLI when the agent should operate Layer environments instead of only searching docs:

go build -o layer ./apps/layer-cli

Ask

ask --endpoint https://hevlayer.com/api/ask/pro search "cache is down"

{
  "results": [
    {
      "title": "Concepts",
      "heading": "Document cache",
      "url": "/docs/pro/concepts#document-cache",
      "group": "Overview",
      "snippet": "The document cache does two jobs: pull-through document reads..."
    }
  ]
}

From here your agent typically runs section get on the winning id and answers with the citation.

The verbs

Verb	Returns
overview	Orientation context plus the full section map with stable ids
search "<query>"	Ranked sections with snippets and deep links
section get "<id>"	One section: summary, exact identifiers, source URL
glossary get "<term>"	A product term resolved through its aliases (watermark → stable watermark)

Why answers stay grounded

Search runs over a committed, reviewable digest of these docs — the same corpus, heading by heading, that renders on this site. Every anchor in it is verified against the rendered pages in CI, so a cited deep link like /docs/api/query#stable-reads always resolves. When the docs change, the digest is rebuilt and recommitted with them.

The docs are also available as plain text for direct ingestion: /docs/pro/llms.txt (index) and /docs/pro/llms-full.txt (full corpus). The CLI is the better path for agents that can run commands — it ranks, resolves aliases, and costs a fraction of the tokens.