Idx.md

Markdown registry for AI agent libraries with indexed HEAD/BODY content.

Install

npx -y skills add Keith-CY/idx.md

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

AgentSkill for https://idx.md. Use the index to locate AI agent library topics and fetch HEAD/BODY markdown.

SKILL.md

4.8 KB, as published. Nobody here has run it

idx.md

Purpose

Markdown registry for AI agent libraries and resources.
Agents can browse to learn everything they could use, then fetch the exact markdown.

Index locations

All topics (full listing, alphabetical): https://idx.md/data/index.md (canonical) or https://idx.md/index.md (alias)
Capability navigation (browse by what the agent can do): https://idx.md/category/index.md
Scenario navigation (browse by workflow / use-case): https://idx.md/scenario/index.md
Industry navigation (browse by domain / vertical): https://idx.md/industry/index.md

How to choose a navigation mode

If you know what you want: start from /data/index.md and search by keywords in titles/tags.
If you want tools by capability: start from /category/index.md.
If you have a specific workflow/use-case: start from /scenario/index.md.
If you're operating in a specific domain: start from /industry/index.md.

Index entry format

Each entry is a HEAD frontmatter block followed by a topic line.
Topic line format: |/data/{topic}|
The index may start with a short HTML comment preamble; entries begin at the first --- frontmatter block.

...frontmatter...

|/data/openclaw|

How to fetch

Read https://idx.md/data/index.md (or https://idx.md/index.md).
Choose {topic} from the |/data/{topic}| line.
HEAD metadata: https://idx.md/{topic} (or /data/{topic}/HEAD.md)
Vector shard (for embedding recall): https://idx.md/{topic}/vectors.json
BODY content: https://idx.md/{topic}/BODY.md
After download, compute SHA-256 on the raw BODY bytes and compare to content_sha256 in HEAD frontmatter.
Use retrieved_at to decide whether a cached BODY needs refresh.

Vector-based retrieval (recommended)

Use /{topic}/vectors.json as the retrieval layer, then fetch /{topic}/BODY.md only for top candidates.
Each vectors.json currently contains one head record derived from HEAD metadata.
Build/query embeddings on records[].text.
Use records[].metadata.content_sha256 as your embedding cache key; only re-embed when it changes.
Suggested flow:

Collect topic candidates from /data/index.md or category/scenario/industry indexes.
Fetch each candidate's /{topic}/vectors.json.
Rank by vector similarity (optionally hybrid with lexical/tag score).
Fetch /{topic}/BODY.md for top-k and generate final answer from BODY.

URL map

/, /skill.md, /SKILL.md -> this document
/index.md, /data/index.md -> index listing
/category/index.md -> category index listing
/category/{category}/index.md -> category topic listing
/scenario/index.md -> scenario index listing
/scenario/{scenario}/index.md -> scenario topic listing
/industry/index.md -> industry index listing
/industry/{industry}/index.md -> industry topic listing
/{topic} -> /data/{topic}/HEAD.md
/{topic}/HEAD.md -> HEAD metadata
/{topic}/vectors.json -> vector shard for embedding recall
/{topic}/BODY.md -> BODY content

Constraints

.md only; .mdx rejected by filename.

Integrity / Hash

content_sha256 lives in the HEAD frontmatter.
content_sha256 is the SHA-256 of the exact BODY bytes (no normalization).
Format: lowercase hex string.
Verify by hashing the downloaded BODY.md bytes and comparing to content_sha256.
If the hash differs, re-download BODY.md.

Example flow

Read /index.md -> pick openclaw -> fetch /openclaw/HEAD.md -> fetch /openclaw/BODY.md.

Contribute

If you find a high-quality markdown resource that agents should know about, please open a PR to add it. Repo: https://github.com/Keith-CY/idx.md

What to add

Add new sources to sources/general.yml.
Use a direct markdown URL (.md) and prefer raw.githubusercontent.com for GitHub content.
.mdx files are rejected.
Choose a type and slug that match ^[a-z0-9][a-z0-9-]*$.
Avoid editing auto-generated registries (sources/openclaw.yml, sources/openai.yml, etc.) or data/ outputs directly.

Minimal entry example

- type: skills
  slug: acme-awesome-skill
  source_url: https://raw.githubusercontent.com/acme/awesome-skill/main/SKILL.md
  title: Awesome Skill (optional)
  summary: One-line summary (optional)
  tags:
    - skills
  license: MIT (optional)
  upstream_ref: https://github.com/acme/awesome-skill/blob/main/SKILL.md (optional)

How to submit

Fork the repo: https://github.com/Keith-CY/idx.md
Add your entry to sources/general.yml.
Open a PR with a short note on why the source is valuable for agents.
If you can run the build, include generated data/ updates; otherwise the maintainer will handle it.

Thanks for helping keep idx.md useful and current.