closelook-intelligence

Ask the research seat

session_message

Sends a research question into an open Closelooknet session. The answer cites each figure with its cl: source and data date; wording by AI is marked with the model. If the question needs a personal recommendation, the session moves to advice_required and lists the next actions.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "session_id": "<session_id>",
      "text": "<text>"
    },
    "name": "session_message"
  }
}

Input Schema

Name	Required	Description	Default
`text`	Yes	The question
`session_id`	Yes	From open_session (ses_…)

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 3, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Beyond the annotations, the description discloses meaningful behavior: answers cite figures with cl: sources and data dates, AI wording is marked with the model, and recommendation-style questions move the session into advice_required with next actions. It does not describe permissions or rate limits, but it adds useful state-transition and output context that annotations do not provide.

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 three sentences, front-loaded with the core action and followed by answer-format and state-change details. It is efficient, with no obviously wasted wording, though it could be slightly tighter.

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 two-parameter mutation-style tool with no output schema, the description covers the key output behavior and a significant side effect. It does not cover error handling or session prerequisites in depth, but the essential operational context is present.

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 coverage is 100%, so both parameters are already documented in the input schema. The description reinforces that text is a research question and that session_id belongs to an open session, but adds no syntax, constraints, or format details beyond the schema baseline.

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 states a specific action and target: sending a research question into an open Closelooknet session. This is clearly distinct from opening a session, though it does not explicitly name sibling tools or contrast with session_action.

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?

Usage is implied by the requirement that the session be open, and the description explains what happens when a personal recommendation is needed. However, it does not explicitly say when to use this versus session_action or other siblings, nor does it state exclusion conditions.

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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