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ag9

作者 oyyblin · GitHub ↗ · v1.1.0 · MIT-0
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在 OpenClaw 中安装
/install ag9
功能描述
Know Your Agent — verifiable human ownership + reverse CAPTCHA for OpenClaw agents, powered by VeryAI palm verification.
使用说明 (SKILL.md)

ag9 — Know Your Agent

ag9 proves two things about an agent that no other layer proves together:

  1. A real human owns this agent — palm-bound via VeryAI. The human scans their palm once; the agent is now cryptographically tied to a verified person.
  2. A real model is operating — reverse CAPTCHA. Three challenge families (byte transforms, constrained generation, structured extraction) that capable LLMs can solve in seconds and humans/scripts cannot.

Both live at https://api.ag9.ai. Note the two base URLs:

  • Path A (human ownership) uses https://api.ag9.ai/v1/agent/...
  • Path B (reverse CAPTCHA) uses https://api.ag9.ai/challenge, /verify, and /.well-known/jwks.json at the root (not under /v1) to match existing OpenClaw/monkey-api integrations.

This URL split is intentional, not a typo — both endpoints are served by the same ag9-api service.

What this skill accesses on your machine

  • ~/.openclaw/identity/device.json (read). Used for Path A only. The skill reads deviceId, publicKeyPem, and privateKeyPem to sign registration/verification challenges. The private key never leaves your machine — only the base64 publicKey, message, and signature are sent to ag9. Path B (reverse CAPTCHA) does not touch this file.
  • No other filesystem access. No disk writes. No background processes. No outbound network calls other than https://api.ag9.ai.

Declared in the skill manifest as requires.config, so install tooling can prompt before first use.

CRITICAL: Never open browsers

Do not use open, xdg-open, start, or any command that opens a browser. Always output the registration URL as a text or markdown link for the user to click.

Key files

File Purpose
SKILL.md https://ag9.ai/skill.md — registration flow, reverse CAPTCHA, verification, full API
HEARTBEAT.md https://ag9.ai/heartbeat.md — periodic checklist: registration status, capability attestation
Identity ~/.openclaw/identity/device.json — OpenClaw deviceId and keys (never send private key)

Security

  • Private key: Used to sign the challenge. Never send the private key to ag9 or any server; only send publicKey, message, and signature.
  • Registration URL: Single-use and short-lived. Give it only to the human owner who will complete VeryAI palm verification.
  • deviceId: Use a stable identifier (e.g. from your identity store or hash of public key). It ties the agent to the registration and is used for lookup and verification.
  • Challenge token (reverse CAPTCHA): HMAC-signed, 15 seconds, single-use. The token carries the answer hash so the server does not keep any per-request state.
  • Capability JWT: Ed25519-signed attestation returned after a successful /verify. Public key at GET /.well-known/jwks.json so any party can verify offline.

Path A: Human ownership (agent ↔ human binding)

Use this when you need a third party to know the agent is owned by a verified human.

Generating the AgentChallenge

The AgentChallenge is a signed payload that shows you control an Ed25519 key. It has the shape used by standard OpenClaw identity flows: deviceId, publicKey, message, signature, timestamp. Generate it once and send it to /agent/register/init or /agent/verify/signature.

Where identity comes from (OpenClaw)

If you run on OpenClaw, device identity is stored at:

  • Path: ~/.openclaw/identity/device.json

That file contains (never send privateKeyPem to any server):

Field Use
deviceId Use as deviceId in the challenge. Stable id for this agent/device.
publicKeyPem Use to derive publicKey (see below).
privateKeyPem Use only locally to sign the message. Never include in API requests.

If you don't use OpenClaw, use your own identity store; ensure you have a stable deviceId, an Ed25519 key pair, and that you sign the exact string you send as message.

Build the challenge (step-by-step)

  1. Choose the message to sign For registration, use a one-time challenge to avoid replay, e.g.:

    • ag9-register-\x3Cunix_timestamp_ms> Example: ag9-register-1776646678000 For verify/signature, the message is whatever you are proving (e.g. a nonce from a third party).
  2. Sign the message with your Ed25519 private key. The signature must be over the exact UTF-8 bytes of message (no extra prefix/suffix).

  3. Encode for the API:

    • publicKey: Ed25519 public key in SPKI DER form, then base64 (no PEM wrapper).
    • signature: Raw Ed25519 signature bytes, base64.
    • timestamp: Unix time in milliseconds when the challenge was created (e.g. Date.now()).
  4. JSON body (AgentChallenge):

    • deviceId — from your identity (e.g. device.json)
    • publicKey — base64 DER SPKI
    • message — exact string that was signed
    • signature — base64 signature
    • timestamp — number (ms)

Example: Node.js

const crypto = require("crypto");
const fs = require("fs");

const identityPath = `${process.env.HOME}/.openclaw/identity/device.json`;
const identity = JSON.parse(fs.readFileSync(identityPath, "utf8"));

const message = `ag9-register-${Date.now()}`;
const privateKey = crypto.createPrivateKey(identity.privateKeyPem);
const signature = crypto.sign(null, Buffer.from(message, "utf8"), privateKey);

const publicKeyDer = crypto
  .createPublicKey(identity.publicKeyPem)
  .export({ type: "spki", format: "der" });

const challenge = {
  deviceId: identity.deviceId,
  publicKey: publicKeyDer.toString("base64"),
  message,
  signature: signature.toString("base64"),
  timestamp: Date.now(),
};
// POST challenge to https://api.ag9.ai/v1/agent/register/init

Using a script

If you have a script that already produces an AgentChallenge (e.g. signs a message and outputs JSON with deviceId, publicKey, message, signature, timestamp), you can reuse it for ag9:

  1. Generate a challenge string, e.g. ag9-register-$(date +%s)000 (seconds + "000" for ms) or use your script's convention.
  2. Run the script to sign that message and get the challenge JSON.
  3. POST that JSON to https://api.ag9.ai/v1/agent/register/init.

Same challenge format works for POST /agent/verify/signature when verifying a signature remotely.

Quick start — human ownership

1. Start registration (agent-initiated)

Build an AgentChallenge as above, then send it to ag9 to create a session and get a registration URL.

curl -X POST https://api.ag9.ai/v1/agent/register/init \
  -H "Content-Type: application/json" \
  -d '{
    "deviceId": "my-agent-device-id",
    "publicKey": "\x3Cbase64-DER-SPKI-Ed25519>",
    "message": "ag9-register-1776646678000",
    "signature": "\x3Cbase64-Ed25519-signature>",
    "timestamp": 1776646678000
  }'

Response (201):

  • sessionId — use to poll status
  • registrationUrloutput this as a link for the human; do not open it in a browser
  • expiresAt — session expiry (ISO 8601)

If the agent is already registered (deviceId exists), the API returns 409 Conflict.

2. Human completes verification

Tell the human owner to open the registrationUrl in their browser. They will go through VeryAI's palm verification via OAuth. When they finish, the agent is registered under their ownership.

3. Poll registration status

Poll until the human has completed or the session has expired:

curl "https://api.ag9.ai/v1/agent/register/SESSION_ID/status"

Response: status is one of pending | completed | expired | failed. When status is completed, the response includes deviceId and registration (e.g. publicKey, registeredAt).

4. Verify signatures or look up an agent

  • Verify a signature — check that a message was signed by the given key and whether that agent is registered under a verified human:
curl -X POST https://api.ag9.ai/v1/agent/verify/signature \
  -H "Content-Type: application/json" \
  -d '{
    "deviceId": "...",
    "publicKey": "...",
    "message": "...",
    "signature": "...",
    "timestamp": 1776646678000
  }'

Response: verified (signature valid), registered (agent under verified human).

  • Look up an agent by device id — get registration and verification status:
curl "https://api.ag9.ai/v1/agent/verify/device/DEVICE_ID"

Response: registered, verified, humanId, and optionally registeredAt.

  • Look up an agent by public key (base64 DER SPKI):
curl "https://api.ag9.ai/v1/agent/verify/public-key/$(printf '%s' "$PUBKEY_B64" | jq -sRr @uri)"

Path B: Reverse CAPTCHA (prove a real model is operating)

Use this when a relying party needs to confirm the requester is a capable agent (not a naive script), independent of any human binding. Stateless, no account needed.

Endpoint summary

Method Path Purpose
POST /challenge Issue a single-use HMAC-signed challenge (15s TTL).
POST /verify Submit {token, solution}; receive an Ed25519-signed capability JWT.
GET /.well-known/jwks.json Public key (JWKS) for offline JWT verification.

These live at the root, not under /v1, to match existing OpenClaw/monkey-api integrations.

1. Request a challenge

curl -s -X POST https://api.ag9.ai/challenge \
  -H "Content-Type: application/json" -d '{}'

Optional ?type=byte_transform|structured_extraction|constrained_gen pins the family. Omit for random.

Response (200):

{
  "challenge_id": "string",
  "challenge_type": "byte_transform | structured_extraction | constrained_gen",
  "difficulty": "medium",
  "payload": { /* shape depends on challenge_type — see below */ },
  "token": "base64url-encoded HMAC-signed token carrying the answer hash",
  "expires_at": 1776646678,
  "time_limit_secs": 30
}

2. Solve and submit

Compute the answer from payload (family-specific — see next section). Submit:

curl -s -X POST https://api.ag9.ai/verify \
  -H "Content-Type: application/json" \
  -d '{ "token": "...", "solution": "..." }'

Response (200):

{
  "success": true,
  "jwt": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9..."
}

The JWT is a capability attestation the relying party can verify offline using the public key at /.well-known/jwks.json. Claims include iss (api.ag9.ai), sub (agent_capability_attestation), challenge_type, difficulty, solved_at, solve_time_ms.

3. Family-specific payloads

byte_transform

{
  "data": "\x3Cbase64 of 256 random bytes>",
  "instructions": [
    "Transform every byte by XOR-ing it with 19 (decimal).",
    "Rotate all bytes left by 192 positions (with wraparound).",
    "Starting at byte 5, going up to byte 66, reverse the sub-array end to end."
  ]
}

Answer: Apply the transforms in order to the decoded bytes, then return sha256(final_bytes) as lowercase hex (64 chars). Typical approach: LLM writes Python, agent executes it. Time limit 30s.

structured_extraction

{
  "document": "\x3Cmalformed HTML/JSON/XML blob with authoritative and decoy values>",
  "fields": ["author_name", "price_usd", "publish_date"]
}

Answer: Extract each field's authoritative value, join with | (pipe), in the exact order listed. The document mixes current and stale/decoy values of the same type. Context clues to prefer: data-verified="true", data-primary="true", data-source="authoritative", data-kind="live", id="product-current", \x3Csection data-kind="live">, \x3Citem status="current">, \x3Cmain>. Clues to avoid: id="product-archive", status="draft", data-kind="historical", \x3Caside>, display:none, \x3Cnoscript>, HTML comments. Fields can live in \x3Cscript type="application/json"> or \x3Cmeta> tags — read them, decide by attributes. Time limit 30s.

constrained_gen

{
  "topic": "ocean waves",
  "lines": 4,
  "ascii_target": 419,
  "word_count": 20,
  "difficulty": "medium"
}

Answer: A plain-text block of exactly lines non-empty lines totaling word_count words, where the sum of ASCII codes of the first character of each trimmed line equals ascii_target (lowercase a=97 through z=122). Recommended approach: choose first letters l_1..l_n such that sum(ord(l_i)) == ascii_target, each in [97, 122]; then pad with short filler words until word_count is reached. Time limit 20s.

4. Verify the JWT offline

Any relying party can verify the attestation without calling ag9 back:

curl -s https://api.ag9.ai/.well-known/jwks.json

Then verify the JWT signature using the returned Ed25519 public key. Cache-Control is public, max-age=3600.


When to use which path

Need Path
Prove a human owns this agent A — registration + /agent/verify/device/{deviceId}
Prove a capable LLM is operating (no human/account needed) B/challenge + /verify
Prove both Run A first, then B on each outbound request
Third-party wants to check your agent They call either /agent/verify/device/{id} (A) or accept a JWT you present (B)

API reference

Base URL: https://api.ag9.ai/v1 (human-ownership endpoints) Base URL (root): https://api.ag9.ai (reverse-CAPTCHA endpoints) Local: http://localhost:3000

Endpoints

Method Endpoint Auth Description
POST /v1/agent/register/init None Start registration session; returns sessionId, registrationUrl, expiresAt.
GET /v1/agent/register/{sessionId}/status None Poll registration status: pending / completed / expired / failed.
POST /v1/agent/verify/signature None Verify a signature and whether the agent is registered under a verified human.
GET /v1/agent/verify/device/{deviceId} None Get agent registration and verification status by device id.
GET /v1/agent/verify/public-key/{publicKey} None Get agent registration and verification status by Ed25519 public key (base64url).
GET /v1/human/leaderboard None Top verified humans ranked by registered agents.
POST /challenge[?type=...] None Issue a single-use reverse-CAPTCHA challenge.
POST /verify None Submit {token, solution}; receive capability JWT.
GET /.well-known/jwks.json None JWKS for offline JWT verification.

Error shape

{
  "error": "Human-readable message",
  "code": "optional_code",
  "details": {}
}

Error codes

Code Meaning
400 Bad request (invalid or missing fields).
404 Session or device not found.
409 Agent already registered (device_id already exists).
429 Rate limit exceeded (10 req/min per IP on /challenge and /verify).
500 Server error.

What this proves

After a successful run through Path A and/or B, a relying party can conclude:

  • Human ownership (A) — The agent is bound to a human who passed VeryAI palm verification. Third parties verify by calling /agent/verify/device/{deviceId} or /agent/verify/signature.
  • Capability (B) — A capable LLM solved a single-use puzzle under time pressure, signed with a key only ag9 controls. Third parties verify the JWT offline via JWKS.
  • Key binding — Ed25519 signatures prove the agent controls its key; ag9 ties that key to the verified human (A) or to an attested capability solve (B).

When to use this skill

  • Registering an OpenClaw (or other) agent under a human owner before interacting with a platform that requires KYA.
  • Proving to a third party that an agent is owned by a verified human — or that it is a real model and not a naive script.
  • Running a self-check (see HEARTBEAT.md) to confirm registration + verification are healthy.

Need help?

安全使用建议
This skill is coherent with its described goal, but it is sensitive: it will read your local OpenClaw device identity and use your private key to sign challenges locally. Before installing, verify you trust the ag9.ai service and that ~/.openclaw/identity/device.json is stored securely and only accessible to you. Confirm the registration URL you hand to a human is single-use/short-lived (as described) and never paste or transmit your privateKeyPem. If you have policy concerns about biometric vendor VeryAI, review their privacy/terms before proceeding. If you prefer more control, perform the signing step manually outside the agent and only allow the agent to handle non-secret parts of the flow.
功能分析
Type: OpenClaw Skill Name: ag9 Version: 1.1.0 The skill 'ag9' (defined in SKILL.md) requires the agent to read and process an Ed25519 private key from ~/.openclaw/identity/device.json to sign identity challenges for the api.ag9.ai service. While the documentation explicitly instructs the agent not to exfiltrate the private key, the requirement for an AI agent to handle raw cryptographic secrets and perform outbound network calls to a third-party API presents a high-risk profile. Additionally, the 'Reverse CAPTCHA' feature requires the agent to solve computational puzzles (e.g., byte transforms) that may involve code execution. These capabilities are plausibly aligned with the stated purpose of identity verification but warrant a suspicious classification due to the sensitive nature of the data accessed.
能力标签
cryptorequires-walletrequires-oauth-tokenrequires-sensitive-credentials
能力评估
Purpose & Capability
The skill claims to prove human ownership and model capability. Requiring ~/.openclaw/identity/device.json (deviceId, publicKey/privateKey) and contacting api.ag9.ai is consistent with that purpose. No unrelated credentials or binaries are requested.
Instruction Scope
SKILL.md explicitly instructs the agent to read device.json and use the local private key to sign messages, then send only publicKey, message, and signature to the API. Reading and using the private key is sensitive but necessary for the claimed cryptographic attestation; the manifest documents this behavior and warns not to send the private key itself.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only, so nothing is written to disk or fetched at install time.
Credentials
Only HOME and the declared config path (~/.openclaw/identity/device.json) are required. No unrelated secrets, cloud creds, or extra environment variables are requested.
Persistence & Privilege
always is false and the skill declares no background processes or writes. It does not request permanent platform-wide presence or modify other skills' configs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ag9
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ag9 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
Declare sensitive config access (private key read from ~/.openclaw/identity/device.json) in skill manifest. Clarify the intentional URL split between Path A (/v1/agent/...) and Path B (root /challenge, /verify). Addresses LLM scanner concerns about undeclared config access.
v1.0.0
Initial ag9 release — Know Your Agent with human ownership + reverse CAPTCHA
元数据
Slug ag9
版本 1.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

ag9 是什么?

Know Your Agent — verifiable human ownership + reverse CAPTCHA for OpenClaw agents, powered by VeryAI palm verification. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 96 次。

如何安装 ag9?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ag9」即可一键安装,无需额外配置。

ag9 是免费的吗?

是的,ag9 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

ag9 支持哪些平台?

ag9 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 ag9?

由 oyyblin(@oyyblin)开发并维护,当前版本 v1.1.0。

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