Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/omgits0mar/awesome-claude-code-extensions/agents-mdgit clone --depth 1 https://github.com/omgits0mar/awesome-claude-code-extensionsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/omgits0mar/awesome-claude-code-extensions/agents-md)<a href="https://agentmods.dev/instructions/omgits0mar/awesome-claude-code-extensions/agents-md"><img src="https://agentmods.dev/badge/instructions/omgits0mar/awesome-claude-code-extensions/agents-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00574 | $0.00574 |
| Opus 5 | $0.00287 | $0.00287 |
| Sonnet 5 | $0.00115 | $0.00115 |
| Haiku 4.5 | $0.00057 | $0.00057 |
Grade A, and why
awesome-claude-code-extensions AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
Project Structure & Module Organization
scripts/contains the Python catalog pipeline: source parsing, normalization, generation, validation, discovery, and link checking.tests/contains standard-libraryunittestcoverage for parsers, URL normalization, merging, CSV safety, and link handling.research/holds reviewed source datasets and checksummed upstream snapshots. Treat snapshots as immutable inputs unless intentionally refreshing them.catalog/andCATALOG.mdare generated outputs, including JSON, CSV, statistics, schema, and per-kind indexes.docs/documents methodology, taxonomy, sources, licensing, and safety. GitHub workflows and issue forms live under.github/.
Build, Test, and Development Commands
Use Python 3.10 or newer; runtime code uses only the standard library.
make test # Run all test_*.py files.
make build # Regenerate catalog files from committed inputs.
make validate # Check schema, counts, generated views, and invariants.
make all # Test, build, then validate.
make check-links # Check a deterministic 250-link network sample.
make refresh-snapshots # Fetch upstream inputs; review every resulting diff.
After changing research data or parsers, run make all and commit the regenerated outputs. CI rejects stale generated files.
Coding Style & Naming Conventions
Follow conventional Python style: four-space indentation, snake_case functions and variables, PascalCase test classes, and uppercase module constants. Prefer type hints, pathlib.Path, small pure helpers, deterministic ordering, and standard-library dependencies. Keep catalog descriptions neutral, factual, original, and no longer than the schema permits. Do not hand-edit generated catalog views.
Testing Guidelines
Add focused regression tests in tests/test_<area>.py for parser, normalization, deduplication, safety, or schema changes. Use descriptive test_<behavior> methods. There is no numeric coverage threshold; changed behavior must be exercised directly. Run both make test and make validate before submitting.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 41 lines · 574 tokens per session scan A e1e4c53b954f
awesome-claude-code-extensions AGENTS.md is an instructions file published in the GitHub repository omgits0mar/awesome-claude-code-extensions (4 stars, last pushed 1mo ago), licensed CC0-1.0. It adds 574 tokens to every session, about $0.0029 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.