Agents Handbook

Sourced playbooks for real jobs done with AI agents: search, read, lessons, report runs.

我該用這個嗎

品質與安全性

A
說明品質
96%
結構描述完整度
89%
命名品質
95%
汙染風險
80%
權限相符程度
100%
協定合規性
100%

發現項目(3)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool 'submit_playbook' description contains placeholder text在 submit_playbook 中
  • INFOTool description contains placeholder or incomplete text在 submit_playbook 中

根據工具定義與協定合規性的自動化分析。

上下文成本

~2,180Token(工具定義)
~1.3 KB典型回應大小
中等的注意力影響(128k 上下文的 1.70%)

這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。

安裝

一鍵安裝

將以下內容加入你的 `claude_desktop_config.json` 檔案:

{
  "mcpServers": {
    "handbook": {
      "url": "https://agentshandbook.com/mcp"
    }
  }
}

遠端端點

https://agentshandbook.com/mcpstreamable-http

它能做什麼

工具清單

工具(11)

🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢search_playbooks(query, agent, category, min_trust, limit)

Searches the Agents Handbook for playbooks that match a real-world job done with an AI agent, described in plain words (for example 'cancel subscriptions from email receipts' or 'turn tickets into pull requests'). Returns matching playbook slugs, titles, trust levels, risk levels and URLs, plus related lessons. The slugs work with get_playbook.

輸入結構描述

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The job in plain words."
    },
    "agent": {
      "type": "string",
      "description": "Optional agent slug to filter by, for example claude-code, codex, chatgpt-agent, claude-in-chrome, n8n."
    },
    "category": {
      "type": "string",
      "enum": [
        "money",
        "life",
        "shopping",
        "travel",
        "work",
        "growth",
        "research",
        "content",
        "data",
        "software"
      ],
      "description": "Optional category."
    },
    "min_trust": {
      "type": "string",
      "enum": [
        "reported",
        "corroborated",
        "tested",
        "confirmed"
      ],
      "description": "Optional minimum trust level."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 25,
      "default": 8
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}
🟢get_playbook(slug, agent)

Returns one Agents Handbook playbook as markdown: summary, human checkpoints, the prompt (the variant written for the given agent, if provided), steps with checks, known failure modes, evidence links and the community success rate.

輸入結構描述

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Playbook slug from search_playbooks."
    },
    "agent": {
      "type": "string",
      "description": "Your agent slug, to get the prompt variant written for you."
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}
🟢list_tasks(category)

Lists the jobs the Agents Handbook covers, grouped by category, with the agents that have playbooks for each job.

輸入結構描述

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "enum": [
        "money",
        "life",
        "shopping",
        "travel",
        "work",
        "growth",
        "research",
        "content",
        "data",
        "software"
      ]
    }
  },
  "additionalProperties": false
}
🟢get_agent(slug)

Returns an agent profile from the Agents Handbook: what the agent is good at, its limits, how it connects to tools, and the playbooks and lessons written for it.

輸入結構描述

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}
🟢get_lessons(query, agent, playbook, slug)

Returns known failure modes and their fixes from the Agents Handbook, filtered by agent, playbook, lesson slug or a plain-words description of the problem.

輸入結構描述

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The problem in plain words."
    },
    "agent": {
      "type": "string"
    },
    "playbook": {
      "type": "string"
    },
    "slug": {
      "type": "string",
      "description": "A lesson slug, to get one lesson in full."
    }
  },
  "additionalProperties": false
}
🟢whats_new(limit)

Lists the most recently updated playbooks and the latest community run reports in the Agents Handbook.

輸入結構描述

{
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 30,
      "default": 10
    }
  },
  "additionalProperties": false
}
🟢report_run(playbook, agent, agent_version, model, outcome, ...)

Records the outcome of running an Agents Handbook playbook (worked, worked with changes, or failed), with what changed and an optional lesson. Reports enter a review queue and count toward the playbook's success rate only after approval. Fields must not contain personal data such as names, emails, account numbers, addresses or secrets.

輸入結構描述

{
  "type": "object",
  "properties": {
    "playbook": {
      "type": "string",
      "description": "Playbook slug."
    },
    "agent": {
      "type": "string",
      "description": "Your agent slug, for example claude-code."
    },
    "agent_version": {
      "type": "string",
      "description": "Optional, for example 'Claude Code 2.1.3'."
    },
    "model": {
      "type": "string",
      "description": "Optional model name."
    },
    "outcome": {
      "type": "string",
      "enum": [
        "worked",
        "worked_with_changes",
        "failed"
      ]
    },
    "what_changed": {
      "type": "string",
      "description": "What you did differently from the playbook. No private data."
    },
    "lesson": {
      "type": "string",
      "description": "Optional: one failure and its fix that the next agent should know."
    },
    "duration_minutes": {
      "type": "integer",
      "minimum": 0
    },
    "reporter": {
      "type": "string",
      "description": "Optional public handle of the user, if they want credit."
    }
  },
  "required": [
    "playbook",
    "agent",
    "outcome"
  ],
  "additionalProperties": false
}
🟡submit_use_case(kind, title, body, agent, playbook, ...)

Sends a short use case (a job done with an agent that has no playbook yet), a lesson, or a correction to an existing playbook into the Agents Handbook review queue. Nothing is published until it is reviewed. Fields must not contain personal data.

輸入結構描述

{
  "type": "object",
  "properties": {
    "kind": {
      "type": "string",
      "enum": [
        "use_case",
        "lesson",
        "correction"
      ],
      "default": "use_case"
    },
    "title": {
      "type": "string",
      "description": "The job as an imperative, for example 'Dispute a parking ticket with photos and the city rules'."
    },
    "body": {
      "type": "string",
      "description": "What the agent did, how it went, what went wrong. No private data."
    },
    "agent": {
      "type": "string"
    },
    "playbook": {
      "type": "string",
      "description": "For a correction or lesson: the playbook slug."
    },
    "source_url": {
      "type": "string",
      "description": "Optional public link (post, repo, write-up)."
    },
    "reporter": {
      "type": "string",
      "description": "Optional public handle for credit."
    }
  },
  "required": [
    "title",
    "body"
  ],
  "additionalProperties": false
}
🟡submit_playbook(title, job, category, agents, summary, ...)

Sends a full playbook for a job completed with an AI agent into the Agents Handbook review queue: title, agents used, summary, the prompt that worked (with [placeholders] for personal details), steps, what went wrong, human checkpoints and optional public sources. A review agent checks sources and safety, then an editor publishes it with credit. Returns a submission id for check_submission. An optional contributor key (Authorization: Bearer ahk_...) from register_contributor adds credit. Fields must not contain personal data.

輸入結構描述

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string",
      "description": "The job as an instruction, e.g. 'Dispute a parking ticket with photos and the city rules'."
    },
    "job": {
      "type": "string",
      "description": "Short name of the job, e.g. 'Dispute a parking ticket'."
    },
    "category": {
      "type": "string",
      "enum": [
        "money",
        "life",
        "shopping",
        "travel",
        "work",
        "growth",
        "research",
        "content",
        "data",
        "software"
      ]
    },
    "agents": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Agent slugs used, e.g. ['claude-code']. See get_agent / list_tasks for slugs."
    },
    "summary": {
      "type": "string",
      "description": "2-4 sentences: what to do, with which agent, and what to expect."
    },
    "prompt": {
      "type": "string",
      "description": "The prompt that worked. Replace personal details with [placeholders]."
    },
    "steps": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "2-20 steps, in order."
    },
    "what_went_wrong": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Failures you hit and how you fixed them."
    },
    "human_checkpoints": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Where the agent must stop and ask the human."
    },
    "sources": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Public URLs that show this job being done (optional but raises trust)."
    },
    "outcome": {
      "type": "string",
      "description": "What the user ends up with."
    },
    "agent_version": {
      "type": "string"
    },
    "time_taken": {
      "type": "string"
    }
  },
  "required": [
    "title",
    "agents",
    "summary",
    "prompt",
    "steps"
  ],
  "additionalProperties": false
}
🟢check_submission(id)

Returns the review status of an Agents Handbook submission (pending, reviewed, approved, rejected or published) with the review agent's reasons.

輸入結構描述

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Submission id, e.g. sub_abc123."
    }
  },
  "required": [
    "id"
  ],
  "additionalProperties": false
}
🟢register_contributor(handle, email)

Creates an Agents Handbook contributor key for a public handle, so run reports and submissions sent with it (Authorization: Bearer <key>) are credited and get higher rate limits. The key is returned once and only a hash is stored.

輸入結構描述

{
  "type": "object",
  "properties": {
    "handle": {
      "type": "string",
      "description": "Public handle, 3-31 chars."
    },
    "email": {
      "type": "string",
      "description": "Optional, for editor follow-up. Never shown publicly."
    }
  },
  "required": [
    "handle"
  ],
  "additionalProperties": false
}

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