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 Aicoo-Team/AICOO-Skills --skill discovergit clone --depth 1 https://github.com/Aicoo-Team/AICOO-SkillsWrote 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/aicoo-team/aicoo-skills/discover)<a href="https://agentmods.dev/skills/aicoo-team/aicoo-skills/discover"><img src="https://agentmods.dev/badge/skills/aicoo-team/aicoo-skills/discover/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/aicoo-team/aicoo-skills/discover"><img src="https://agentmods.dev/badge/skills/aicoo-team/aicoo-skills/discover.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 54 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 140 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 152 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 163 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00125 | $0.02158 |
| Opus 5 | $0.00063 | $0.01079 |
| Sonnet 5 | $0.00025 | $0.00432 |
| Haiku 4.5 | $0.00013 | $0.00216 |
Grade A, and why
discover scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://www.aicoo.io/api/square?q=<TERMS>&limit=10&sort=most_asked" | jq . How it starts
The opening of the file, as written. The whole thing — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discover — Find Interesting People on Square
Search Aicoo Square and surface the most relevant people — either by inferring what the user cares about (auto) or from an explicit description (manual). Present results immediately: username, what they're building, why they're interesting.
Design goal: Minimize time-to-first-aha. The user should see N interesting people (default 10) within seconds, not minutes.
Parameters
| Param | Default | Meaning |
|---|---|---|
N |
10 | Number of people to return. Claude Code keeps searching until N interesting matches are found (or Square is exhausted). |
User can override: "discover 5 people", "find me 20 builders", etc.
Modes
Auto Mode (default when no explicit query)
Claude Code infers search intent from available context:
- User's current project / tech stack
- Memory (skills, interests, goals)
- Recent conversation topics
- CLAUDE.md / package.json / repo signals
Then fires 2-3 searches to cover different angles and presents a curated list.
Example triggers:
- "discover people"
- "who should I connect with?"
- "who's interesting on square?"
- "find me people" (no further specification)
Manual Mode (user states intent)
User provides a description. Claude Code extracts 2-3 key terms and searches.
Example triggers:
- "find someone who knows Rust + WebRTC"
- "discover people building dev tools"
- "who's doing ML infra?"
Execution
Regardless of mode, Claude Code does the work and presents results. Never ask the user to refine a query before showing results.
Step 1: Search Square
# Primary search
curl -s "https://www.aicoo.io/api/square?q=<TERMS>&limit=10&sort=most_asked" | jq .
# Broaden if sparse (try different angle)
curl -s "https://www.aicoo.io/api/square?subsquare=builders&sort=most_asked&limit=10" | jq .
Query params:
| Param | Use |
|---|---|
q |
Free-text (matches title, content, username, name, tags) |
subsquare |
builders, hiring, events, general, projects, feedback |
tag |
Exact tag match |
sort |
recent, most_liked, most_asked |
limit |
Max results (up to 50) |
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.
- 12d ago First seen · 252 lines · 125 tokens per session scan A af2d8f07fb91
discover is a skill published in the GitHub repository Aicoo-Team/AICOO-Skills (35 stars, last pushed 1mo ago), licensed MIT. It adds 125 tokens to every session and 2,158 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
artifact-deploy
One-click deploy a user's pre-built app/artifact into their OWN AWS account and get a global public HTTPS link (Vercel-like), with a default TTL and promote-to-persistent. Use when the user says "deploy this", "ship this demo", "give me a public link", "share this externally", or "deploy to AWS".
explain-for
Explain a topic, a piece of code, an error, or a design decision calibrated to one named audience — a 5-year-old, a 5th grader, a manager, a designer, a graduate student, a parent. Resolves who the explanation is for (from the request, or from what memory already records about that person), establishes the ground…
learn-from-sage
Detection-gap (miss) analysis for Code Review Sage. Learn from shipped fixes, acted-on human comments, and design outcomes to close reviewer blind spots. Inline during review stages a candidate; a human triggers a one-shot AI consolidation into the live ruleset.
papyrus-latex-suggestions
Propose actual inline replacement text (old → new) as accept/reject suggestions — LaTeX "suggesting mode" / track changes — that render directly in the PDF. Use when the author wants concrete edit proposals they can see and accept or reject. For remarks ABOUT the text (notes, not replacements), use…
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.
agent-initialization
Initialize an Agent's settings from a user requirement by writing AGENTS.md, setting identity metadata, and installing only needed Skills.