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Agent Identity

OrganizationPopular
openonion
agent-identity

Verify an agent's live address and billing account before sharing a chat link, diagnosing a deploy mismatch, or deciding why two hosts share an identity.

Overview

Publisheropenonion
Repositoryconnectonion
Skill nameagent-identity
Stars
1.5K
Forks
218
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by openonion on GitHub. Read the source before you install it.

Installation

Install the Agent Identity AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/openonion/connectonion.git /tmp/connectonion
mkdir -p .claude/skills
cp -r /tmp/connectonion/connectonion/useful_skills/agent-identity .claude/skills/agent-identity
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Identity in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Identity on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Identity is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent identity

Read the signing identity, model payer, and env metadata from their own sources. Never print tokens, private keys, or recovery phrases in diagnostics.

1. Verify the live agent

Query the configured Host /info endpoint and read address. Use the actual service port, not an assumed hostname or a copied AGENT_ADDRESS value.

bash
curl --fail --silent --show-error http://localhost:8000/info \
  | python3 -c 'import json,sys; print(json.load(sys.stdin)["address"])'

The key determines the address. AGENT_EMAIL and IS_EMAIL_ACTIVE are email metadata. Env address notes, server inventories, and DNS names can be stale.

2. Check the selected account

All env settings default to $AGENT_CONFIG_PATH/keys.env, normally ~/.co/keys.env. Entering a project never loads its .env. co --env-file /path/to/app.env … explicitly selects a different file; inherited process settings win. With explicit selection, CLI identity readers use an existing key in the file's adjacent .co/, falling back to the global key when it has none. co init initializes global configuration; project creation requires co create or an explicit co init ./.

Run this diagnostic in the target process's environment. Decoding alone does not verify a JWT. The GET checks the same backend used by auth and models, refuses redirects, and prints only the account and balance.

python
import base64
import json
import os
from pathlib import Path
import requests
from connectonion.backend import backend_url
from connectonion.environment import load_environment, select_env_file

# Optional explicit selection, equivalent to co --env-file /path/to/app.env:
# select_env_file(Path("/path/to/app.env"))
load_environment()
token = os.environ.get("OPENONION_API_KEY")
if not token:
    raise SystemExit("No managed-model token in the selected environment")
try:
    payload = token.split(".")[1]
    claims = json.loads(base64.urlsafe_b64decode(payload + "=" * (-len(payload) % 4)))
    print("Token account (unverified claim):", claims["public_key"])
except (IndexError, KeyError, ValueError, UnicodeError):
    raise SystemExit("Token is not a decodable account JWT; do not print it") from None

# Resolve the same backend as auth/models. Never put a token in shell arguments.
response = requests.get(
    f"{backend_url()}/api/v1/auth/me",
    headers={"Authorization": f"Bearer {token}"},
    timeout=15,
    allow_redirects=False,
)
if response.status_code != 200:
    raise SystemExit(f"Account lookup failed (HTTP {response.status_code})")
account = response.json()
print("Verified account:", account.get("public_key"))
print("Balance:", account.get("balance_usd"))

co status authenticates the selected signing identity, which may differ from a separately supplied model token. POST /api/v1/auth may create a new account; do not use it just to inspect an existing token.

3. Explain a deploy mismatch

Deployment derives a candidate from the normalized name and operator phrase, but preserves an existing server key. --own-identity creates a server-owned key only when none exists. The deployment authenticates the live server key and uses its account token/email; a different derived candidate is not a reason to delete it.

Default deployment filters global personal provider credentials and operator identity. An explicit env file opts into that file's provider credentials; operator identity still comes from the live server account. If authentication fails, deploy does not substitute the operator's account. Check its failure output and repair the intended account through the normal auth workflow after obtaining approval.

4. Investigate duplicate hosts

The same name and phrase can produce one key on two machines. Compare live /info addresses, deployment records, and business-state timestamps. Separate hosts can repeat work because their delivery ledgers are separate. Agree which instance should run before stopping either one; never infer that one is disposable from the address alone.

Report the live address, selected env source, token account, configured backend, and evidence for any mismatch. Omit all secret values. Keep corrections in the selected deployment source so a later deploy does not undo them.

References

  • docs/agent-identity.md
  • docs/key-derivation.md
  • docs/network/deploy.md

Frequently asked questions

What does the Agent Identity AI skill do?

Verify an agent's live address and billing account before sharing a chat link, diagnosing a deploy mismatch, or deciding why two hosts share an identity.

Why use Agent Identity on TypingMind?

Because you install it once and use it with any model. Agent Identity is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Identity in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openonion/connectonion/tree/main/connectonion/useful_skills/agent-identity. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Identity?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Identity?

As many as you like. As long as a model supports skills, you can use Agent Identity with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Identity AI skill free?

Yes. It is published on GitHub by openonion under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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