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Agent Skill · 开发

ag9(抗原 9)

ag9 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ag9 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,744 个 Skill 里排第 9,118。

总安装 2,856周安装 119GitHub Stars 公开资料未说明下载 952核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.1.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ag9(抗原 9)
来源仓库:https://github.com/oyyblin/ag9
安装命令:
openclaw skills install ag9
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ag9

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

了解您的代理 — 可验证的人类所有权 + OpenClaw 代理的反向验证码,由 VeryAI 手掌验证提供支持。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install ag9;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ag9 怎么安装?

在终端执行 openclaw skills install ag9。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ag9 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ag9 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

ag9 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

ag9 用的人多吗?

公开数据是累计安装 2,856 次,近一周安装 119 次,下载 952 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ag9 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
ag9

抗原 9 · 本页

2,856—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
ag9
version
1.1.0
description
Know Your Agent — verifiable human ownership + reverse CAPTCHA for OpenClaw agents, powered by VeryAI palm verification.
homepage
https://ag9.ai
requires
config
env
metadata
category
identity
api_base_human_ownership
https://api.ag9.ai/v1
api_base_reverse_captcha
https://api.ag9.ai
reads_private_key
true

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. - WRONG: open "https://api.very.org/oauth2/..." - CORRECT: "Open this link to complete verification: https://api.very.org/oauth2/..."

Key files

FilePurpose
SKILL.mdhttps://ag9.ai/skill.md — registration flow, reverse CAPTCHA, verification, full API
HEARTBEAT.mdhttps://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):

FieldUse
deviceIdUse as deviceId in the challenge. Stable id for this agent/device.
publicKeyPemUse to derive publicKey (see below).
privateKeyPemUse 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-<unix_timestamp_ms> Example: ag9-register-1776646678000 For verify/signature, the message is whatever you are proving (e.g. a nonce from a third party).

  1. Sign the message with your Ed25519 private key. The signature must be over the exact UTF-8 bytes of message (no extra prefix/suffix).
  1. 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()).

  1. 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": "<base64-DER-SPKI-Ed25519>",
    "message": "ag9-register-1776646678000",
    "signature": "<base64-Ed25519-signature>",
    "timestamp": 1776646678000
  }'

Response (201):

  • sessionId — use to poll status
  • registrationUrl — output 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

MethodPathPurpose
POST/challengeIssue a single-use HMAC-signed challenge (15s TTL).
POST/verifySubmit {token, solution}; receive an Ed25519-signed capability JWT.
GET/.well-known/jwks.jsonPublic 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": "<base64 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": "<malformed 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", <section data-kind="live">, <item status="current">, <main>. Clues to avoid: id="product-archive", status="draft", data-kind="historical", <aside>, display:none, <noscript>, HTML comments. Fields can live in <script type="application/json"> or <meta> 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

NeedPath
Prove a human owns this agentA — registration + /agent/verify/device/{deviceId}
Prove a capable LLM is operating (no human/account needed)B — /challenge + /verify
Prove bothRun A first, then B on each outbound request
Third-party wants to check your agentThey 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

MethodEndpointAuthDescription
POST/v1/agent/register/initNoneStart registration session; returns sessionId, registrationUrl, expiresAt.
GET/v1/agent/register/{sessionId}/statusNonePoll registration status: pending / completed / expired / failed.
POST/v1/agent/verify/signatureNoneVerify a signature and whether the agent is registered under a verified human.
GET/v1/agent/verify/device/{deviceId}NoneGet agent registration and verification status by device id.
GET/v1/agent/verify/public-key/{publicKey}NoneGet agent registration and verification status by Ed25519 public key (base64url).
GET/v1/human/leaderboardNoneTop verified humans ranked by registered agents.
POST/challenge[?type=...]NoneIssue a single-use reverse-CAPTCHA challenge.
POST/verifyNoneSubmit {token, solution}; receive capability JWT.
GET/.well-known/jwks.jsonNoneJWKS for offline JWT verification.

Error shape

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

Error codes

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

  • API base: https://api.ag9.ai
  • Homepage: https://ag9.ai
  • Interactive demo: https://ag9.ai/demo
  • OpenAPI spec: https://api.ag9.ai/openapi/v1.yaml

平台分布

OpenClaw

76.8%
按下载量换算731

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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