agent-contacts

agent-contacts is a skill for Claude Code from aAAaqwq/AGI-Super-Team. It costs 33 tokens per session (1,325 once invoked), scanned A, original, MIT.

Instructions for keeping a contact book of other AI agents that can communicate through MCP, a standard way for AI tools to exchange requests and data. It supports adding, listing, and removing agent contacts.

In plain words
What is it for?
Use it when someone provides an agent URL, or when you need to add a contact, view the contact list, or remove an existing agent.
Why use it?
It keeps agent connection details in a consistent format, making it easier to reuse and manage communication endpoints.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: reads .claude/ paths; positional $N argument; mentions Claude Code.

Part of the agi-super-team plugin — 194 skills, 1 agent shipped together

Good fit Use it when someone provides an agent URL, or when you need to add a contact, view the contact list, or remove an existing agent.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aaaaqwq/agi-super-team/agent-contacts
Install

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.

Any agent
npx skills add aAAaqwq/AGI-Super-Team --skill agent-contacts
Clone the repo
git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team

Made for: Claude Code.

Or install agi-super-team, the plugin that ships this one along with the rest of its 194 skills, 1 agent.

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.

agentmods badge for agent-contacts

README.md
[![agentmods](https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/agent-contacts/github.svg)](https://agentmods.dev/skills/aaaaqwq/agi-super-team/agent-contacts)
Your own site
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/agent-contacts"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/agent-contacts/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.

agentmods 80×15 button for agent-contacts

Your own site · 80×15
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/agent-contacts"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/agent-contacts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,325 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.01325
Opus 5 $0.00016 $0.00662
Sonnet 5 $0.00007 $0.00265
Haiku 4.5 $0.00003 $0.00133

Measured 10d ago against content hash 077ac537ce93, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

agent-contacts 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 10d 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.

skills/agent-contacts/SKILL.md · 180 lines

How it starts

The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Contacts

Contact book for AI agents. Add an MCP address and your Claude Code can communicate with other agents.

When to use

  • /agent-contacts add <url> — add a new contact
  • /agent-contacts list — show all contacts
  • /agent-contacts remove <name> — remove a contact
  • When someone gives you an agent/bot URL

Paths

What Path
Contacts DB ~/.claude/agent-contacts.json

contacts.json format

[
  {
    "name": "Your Name",
    "slug": "ivan-schedule",
    "mcp_url": "https://your-agent.example.com/mcp/",
    "discovery_url": "https://your-agent.example.com/.well-known/agent.json",
    "capabilities": ["scheduling"],
    "description": "Scheduling agent for Your Name",
    "added": "2026-02-26"
  }
]

How to execute

Parse $ARGUMENTS to determine the command: first word is the command (add, list, remove), the rest is the argument.

Add: /agent-contacts add <url>

import json, re
from datetime import date
from pathlib import Path

CONTACTS_FILE = Path.home() / ".claude" / "agent-contacts.json"

# 1. Load existing contacts
if CONTACTS_FILE.exists():
    contacts = json.loads(CONTACTS_FILE.read_text())
else:
    contacts = []

# 2. Normalize URL — $ARGUMENTS[1] is the URL
url = "$1".strip().rstrip("/")
if not url.endswith("agent.json"):
    discovery_url = url + "/.well-known/agent.json"
else:
    discovery_url = url
    url = url.rsplit("/.well-known/agent.json", 1)[0]

# 3. Use WebFetch to get agent.json content, then parse:
# - name = agent_data["name"]
# - description = agent_data.get("description", "")
# - capabilities = list(agent_data.get("capabilities", {}).keys())
# - mcp_url = agent_data["capabilities"][first_cap]["url"]
#   Ensure mcp_url ends with "/"

# 4. Generate slug
slug = re.sub(r"[^a-z0-9-]", "", name.lower().replace(" ", "-"))

# 5. Check for duplicates
if any(c["slug"] == slug for c in contacts):
    print(f"Contact '{name}' already exists.")
else:
    contacts.append({
        "name": name,
        "slug": slug,
        "mcp_url": mcp_url,
        "discovery_url": discovery_url,
        "capabilities": capabilities,
        "description": description,
        "added": str(date.today()),
    })
    CONTACTS_FILE.write_text(json.dumps(contacts, indent=2, ensure_ascii=False))

Read the full file on GitHub · 180 lines

Changes

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.

  1. 10d ago First seen · 180 lines · 33 tokens per session scan A 077ac537ce93

Subscribe to this mod's changes

agent-contacts is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 1,325 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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