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datafood-mcp

by io.github.atmflow55
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datafood_watch_session

Open a watchable agent session — returns session_id and a public /watch/{id} URL for live observation. Free.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "datafood_watch_session"
  }
}

Input Schema

NameRequiredDescriptionDefault
intentNoOptional one-line intent string
agent_idNoOptional human-readable agent identifier

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It does disclose key behavior: returns session_id and a public URL, and notes it is 'Free'. However, it omits details about session lifecycle, prerequisites, or potential side effects (e.g., whether the agent starts executing). This is basic but not rich transparency.

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

Conciseness5/5

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

The description is a single, front-loaded sentence with no wasted words. It states the action, outputs, and a notable feature (Free) efficiently, earning a perfect score for conciseness and structure.

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

Completeness4/5

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

For a simple tool with no required parameters and no output schema, the description is fairly complete: it covers purpose, return values, and cost. It lacks usage exclusions and session lifecycle details, but given the low complexity, this is acceptable. A small gap in alternative guidance prevents a 5.

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?

Schema description coverage is 100% since both parameters have descriptions. The tool description itself does not add extra meaning beyond the schema, but the schema already documents each parameter adequately. Baseline 3 is appropriate as the description adds no value over the structured field descriptions.

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

Purpose5/5

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

The description clearly identifies the tool's purpose with a specific verb+resource: 'Open a watchable agent session'. It also distinctively notes the tool returns a session_id and a public /watch/{id} URL, setting it apart from siblings like datafood_query or datafood_bundle. The purpose is unambiguous and no tautology is present.

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

Usage Guidelines4/5

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

The description indicates the tool is for 'live observation' of an agent session, implying when to use it. However, it does not explicitly compare with alternatives or state when not to use it. Given the sibling tools, this is a clear but not fully explicit usage context.

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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