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chat_history

Retrieve conversation history for Pickaxe agents to analyze interactions, identify knowledge gaps, and review performance metrics.

Instructions

Fetch conversation history for a Pickaxe agent. Use to analyze user questions, identify KB gaps, and review agent performance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
studioNoStudio name to use. Available: STAGING, MAIN, DEV, PRODUCTION. Default: PRODUCTION
pickaxeIdYesThe Pickaxe agent ID (from the agent URL or config)
skipNoNumber of conversations to skip (for pagination). Default: 0
limitNoMaximum conversations to return. Default: 10, Max: 100
formatNoOutput format. 'messages' is human-readable, 'raw' includes metadata. Default: messages

Implementation Reference

  • The execution handler for the 'chat_history' tool. It makes a POST request to the Pickaxe API '/studio/pickaxe/history' endpoint with parameters pickaxeId, skip, limit, and format, then returns the JSON-formatted result.
    case "chat_history": {
      const result = await pickaxeRequest("/studio/pickaxe/history", "POST", {
        pickaxeId: args.pickaxeId,
        skip: args.skip ?? 0,
        limit: args.limit ?? 10,
        format: args.format ?? "messages",
      }, studio);
      return JSON.stringify(result, null, 2);
    }
  • Input schema definition for the 'chat_history' tool, specifying parameters like studio, pickaxeId (required), skip, limit, and format.
    inputSchema: {
      type: "object",
      properties: {
        studio: studioParam,
        pickaxeId: {
          type: "string",
          description: "The Pickaxe agent ID (from the agent URL or config)",
        },
        skip: {
          type: "number",
          description: "Number of conversations to skip (for pagination). Default: 0",
        },
        limit: {
          type: "number",
          description: "Maximum conversations to return. Default: 10, Max: 100",
        },
        format: {
          type: "string",
          enum: ["messages", "raw"],
          description: "Output format. 'messages' is human-readable, 'raw' includes metadata. Default: messages",
        },
      },
      required: ["pickaxeId"],
    },
  • src/index.ts:120-146 (registration)
    Registration of the 'chat_history' tool in the tools array, including name, description, and input schema. This array is used by the ListToolsRequestHandler.
      name: "chat_history",
      description: "Fetch conversation history for a Pickaxe agent. Use to analyze user questions, identify KB gaps, and review agent performance.",
      inputSchema: {
        type: "object",
        properties: {
          studio: studioParam,
          pickaxeId: {
            type: "string",
            description: "The Pickaxe agent ID (from the agent URL or config)",
          },
          skip: {
            type: "number",
            description: "Number of conversations to skip (for pagination). Default: 0",
          },
          limit: {
            type: "number",
            description: "Maximum conversations to return. Default: 10, Max: 100",
          },
          format: {
            type: "string",
            enum: ["messages", "raw"],
            description: "Output format. 'messages' is human-readable, 'raw' includes metadata. Default: messages",
          },
        },
        required: ["pickaxeId"],
      },
    },
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions the tool fetches history and suggests use cases, it doesn't describe important behavioral aspects: whether this requires authentication, rate limits, what the return format looks like (beyond the 'format' parameter), pagination behavior beyond skip/limit parameters, or error conditions. For a tool with 5 parameters and no annotation coverage, this leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with two sentences that efficiently state the core purpose and three use cases. It's front-loaded with the main action ('Fetch conversation history') and wastes no words. However, the second sentence could be slightly more structured by separating the use cases with semicolons or bullet points for even clearer scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters, no annotations, and no output schema, the description provides adequate but incomplete context. It clearly states what the tool does and suggests use cases, but doesn't address behavioral aspects like authentication needs, rate limits, error handling, or what the return data structure looks like. For a data retrieval tool with multiple parameters, more complete behavioral context would be helpful despite the good schema documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with all parameters well-documented in the schema itself. The description doesn't add any meaningful parameter semantics beyond what's already in the schema - it doesn't explain parameter relationships, provide examples, or clarify edge cases. With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't need to given the comprehensive schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Fetch conversation history') and resource ('for a Pickaxe agent'), making the purpose immediately understandable. It distinguishes this tool from sibling tools (which are all about docs, memory, products, studios, or users) by focusing on chat history. However, it doesn't explicitly differentiate from potential non-existent siblings like 'chat_analytics' or 'chat_summary'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage context by listing three use cases: 'analyze user questions, identify KB gaps, and review agent performance.' This gives some guidance on when this tool would be appropriate. However, it doesn't explicitly state when NOT to use it or mention alternatives among the sibling tools (none of which appear to be direct alternatives for fetching chat history).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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