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 onfire7777/universal-ai-skills-library --skill attio-automationgit clone --depth 1 https://github.com/onfire7777/universal-ai-skills-libraryWrote 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/onfire7777/universal-ai-skills-library/attio-automation)<a href="https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/attio-automation"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/attio-automation/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/onfire7777/universal-ai-skills-library/attio-automation"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/attio-automation.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 | $0.00046 | $0.01577 |
| Opus 5.5 | $0.00018 | $0.00631 |
| Sonnet 5.5 | $0.00009 | $0.00315 |
| Haiku 4.5 | $0.00005 | $0.00158 |
Grade A, and why
attio-automation 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.
This is a copy
100% identical to Attio Automation — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attio Automation
Manage your Attio CRM workspace -- fuzzy search across people and companies, run complex filtered queries, browse notes, discover object schemas, and list records -- all through natural language commands.
Toolkit docs: composio.dev/toolkits/attio
Setup
- Add the Composio MCP server to your client configuration:
https://rube.app/mcp - Connect your Attio account when prompted (OAuth authentication).
- Start issuing natural language commands to manage your CRM data.
Core Workflows
1. Fuzzy Search Across Records
Search for people, companies, deals, or any object by name, domain, email, phone, or social handle.
Tool: ATTIO_SEARCH_RECORDS
Example prompt:
"Search Attio for anyone named Alan Mathis"
Key parameters (all required):
query-- Search string (max 256 characters). Empty string returns default results.objects-- Array of object slugs to search (e.g.,["people"],["people", "companies"],["deals"])request_as-- Context: use{"type": "workspace"}for full workspace search, or specify a workspace member
2. Advanced Filtered Queries
Query records with server-side filtering, sorting, and complex conditions -- far more powerful than fuzzy search.
Tool: ATTIO_QUERY_RECORDS
Example prompt:
"Find all companies in Attio created after January 2025 sorted by name"
Key parameters:
object(required) -- Object slug or UUID (e.g., "people", "companies", "deals")filter-- Attio filter object with operators like$eq,$contains,$gte,$and,$orsorts-- Array of sort specifications withdirection("asc"/"desc") andattributelimit-- Max records to return (up to 500)offset-- Pagination offset
Filter examples:
{"name": {"first_name": {"$contains": "John"}}}
{"email_addresses": {"$contains": "@example.com"}}
{"created_at": {"$gte": "2025-01-01T00:00:00.000Z"}}
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.
- 1mo ago First seen · 161 lines · 46 tokens per session scan A 345458ee86e8
attio-automation is a skill published in the GitHub repository onfire7777/universal-ai-skills-library (16 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 1,577 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to Attio Automation, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
Attio Automation
Automate Attio CRM operations -- search records, query contacts and companies with advanced filters, manage notes, list attributes, and navigate your relationship data -- using natural language through the Composio MCP integration.
wttr-weather
Weather via wttr.in GET (no key). Use for weather/forecast; prefer os.http.request.
jk
Manage Jenkins controllers with jk, including jobs, runs, logs, artifacts, credentials, nodes, queues, and plugins.
ground-state
Before starting any non-trivial implementation, run a pre-flight reconnaissance pass to triangulate git state, project infrastructure, and prior-session memory. Auto-assembles a verified grounding preamble — a session-scoped artifact the orchestrator pastes verbatim into every subsequent sub-agent brief — eliminating…
engineering-principles
Practical engineering judgement: smallest change, subtract before adding, data structures before logic, idempotent operations, migrate callers then delete. Use when designing, building, or reviewing changes.
financial-analysis
Financial figures done carefully: periods and fiscal calendars, units and currencies, reconciliation, magnitude sanity checks, sourced assumptions. Use for statements, budgets, pricing, and diligence numbers.