Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/rustykuntz/clideck/awesome-lists)<a href="https://agentmods.dev/skills/rustykuntz/clideck/awesome-lists"><img src="https://agentmods.dev/badge/skills/rustykuntz/clideck/awesome-lists.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 5.1 | $0.00037 | $0.01498 |
| Opus 5 | $0.00018 | $0.00749 |
| Sonnet 5 | $0.00007 | $0.00300 |
| Haiku 4.5 | $0.00004 | $0.00150 |
Grade A, and why
awesome-lists 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 8d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Publish to GitHub Awesome Lists
Get our repo listed in popular GitHub awesome lists to drive organic discovery.
Step 1: Craft the entry message
Before searching for lists, decide what to say. Read our README.md carefully — match its tone exactly (lowercase, direct, Karpathy-style, no marketing language).
Write three versions of the entry description:
- Long (~2 sentences) — for lists that allow detailed entries
- Medium (~1 sentence) — for standard lists
- Short (under 15 words) — for tight table formats
Rules:
- No "your" — it's a marketing trap
- No adjectives like "powerful", "seamless", "cutting-edge", "revolutionary"
- Lead with what it looks like to use (e.g. "WhatsApp-like interface") — concrete references everyone understands
- Highlight the three differentiators: chat-style multi-agent UI, autopilot routing while afk, mobile remote
- State what it does, not what it "enables" or "empowers"
Show the drafts to the user for approval before proceeding.
Step 2: Search for awesome lists
Use the internal search tool to find candidate lists:
(cd /Users/rusty/Projects/temp/gpt-oss-20b-MXFP4-Q8 && npm run search:cli -- '{"queries":[
"awesome AI coding agents CLI tools github list site:github.com",
"awesome AI development tools terminal agents github site:github.com",
"awesome list claude code codex gemini CLI agents site:github.com",
"awesome open source AI tools agents frameworks github site:github.com",
"awesome AI code assistants IDE tools github list site:github.com",
"awesome terminal tools developer productivity AI github site:github.com",
"awesome AI agents autonomous coding tools curated list site:github.com"
]}')
You can send up to 7 queries at once. Results arrive as JSON with results[].items[].link and .title.
Extract unique GitHub repo URLs from results.
Step 3: Evaluate candidates
For each repo found, get the star count:
gh api "repos/OWNER/REPO" --jq '.stargazers_count'
Run this in a batch for all candidates. Sort by stars descending.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 149 lines · 37 tokens per session scan A 513f3dd263d2
awesome-lists is a skill published in the GitHub repository rustykuntz/clideck (154 stars, last pushed 19d ago), licensed MIT. It adds 37 tokens to every session and 1,498 once invoked, about $0.0002 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 2026-08-30.
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