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 skills add bh-rat/context-awesome --skill find-awesome-toolsgit clone --depth 1 https://github.com/bh-rat/context-awesomeWrote 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/skills/bh-rat/context-awesome/find-awesome-tools)<a href="https://agentmods.dev/skills/bh-rat/context-awesome/find-awesome-tools"><img src="https://agentmods.dev/badge/skills/bh-rat/context-awesome/find-awesome-tools/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bh-rat/context-awesome/find-awesome-tools"><img src="https://agentmods.dev/badge/skills/bh-rat/context-awesome/find-awesome-tools.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00195 | $0.01415 |
| Opus 5.5 | $0.00078 | $0.00566 |
| Sonnet 5.5 | $0.00039 | $0.00283 |
| Haiku 4.5 | $0.00019 | $0.00142 |
Grade A, and why
find-awesome-tools 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 1mo 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Find Awesome Tools
Curated discovery of tools, libraries, frameworks, and resources across thousands of community-maintained awesome-lists. Reach for this skill when the user is deciding what to use in a technology space — not when they already have a specific library in hand and need its API or configuration.
When to Use This Skill
Activate this skill when the user:
- Asks "what are good X for Y" or "recommend X"
- Wants a comparison of options in a category
- Explores an unfamiliar space and needs to see what exists
- Mentions "awesome list", "curated list", or names a broad category
Do not use this skill when the user already knows the library and needs docs, configuration help, or debugging for it — that belongs to a documentation skill.
Workflow
Three tools mirror one concept: find sections, search items, fetch items from a list. Pick the path based on the user's intent.
| User intent | Path |
|---|---|
| "What exists in category X?" | find_awesome_section → get_awesome_items |
| "Find me a keyword or concept" | search_awesome_items (one-shot) |
| "Give me everything from list Y" | get_awesome_items directly (when repo/listId is known) |
MCP callers invoke the tools directly. CLI callers use the matching subcommand: sections, search, items. Both transports hit the same backend.
Tools
find_awesome_section / context-awesome sections
Discovers sections (categories) matching a query across every indexed awesome-list. Call this before get_awesome_items unless you already know the githubRepo or listId.
Inputs:
query(required) — search termsconfidence(optional, default0.3) — minimum match confidence, 0–1limit(optional, default10) — maximum sections returned
MCP:
{ "query": "graph databases", "limit": 5 }
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.
- 1mo ago First seen · 146 lines · 195 tokens per session scan A 3362e2e0165e
find-awesome-tools is a skill published in the GitHub repository bh-rat/context-awesome (61 stars, last pushed 4mo ago), licensed MIT. It adds 195 tokens to every session and 1,415 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-08-30.
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