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consult_analyst

Read-only

Consult synthetic domain analysts, executive personas, or historical thinkers to get specialist answers, with optional deep research and session context.

Instructions

Use when consulting synthetic domain analysts, C-Suite executive personas, or classic historical thinkers grounded in specialist knowledge graphs. (For living practitioners e.g. Ben Dietz, use consult_human_agent or request_expert_intro.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNoSet true to have the agent conduct deep background research across specialist graphs and market data before answering (or detects 'do your homework' / 'deep breakdown' in multi-turn queries).
queryYesThe question or topic to discuss with the analyst
userIdNoOptional user identifier.
companyNoOptional company name or stock ticker (e.g., 'Nike', 'Tesla', or 'TSLA') to bind the analyst to a specific brand context. Automatically extracted if included in analyst_id (e.g. 'Nike CMO').
analyst_idYesThe internal ID of the agent (from list_analysts or find_expert, e.g. 'brand-cmo', 'john-ruskin', or 'retail-synthetic'). This is an internal identifier; the agent's display name is in the response.
session_idNoPass the session_id from a previous consult response to continue that engagement — the analyst keeps context across the session. Omit for a one-off question.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.3.3

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context beyond that — it doesn't explain the non-idempotent nature implied by idempotentHint=false, the conversational session behavior, or rate/latency traits. With annotations carrying safety, this is minimum viable.

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?

Two sentences, zero waste, with the primary scope front-loaded and the alternative-parenthetical second. Every clause carries routing value.

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?

Purpose, alternatives, and parameter meaning are all covered by description plus schema, and no output schema means return values needn't be explained (the schema itself references the response's display name and session_id). It stops short of explaining what an engagement yields or the non-idempotent behavior, a minor gap for a read-only consult tool.

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%, so the schema already documents all six parameters including deep, session_id, company, and analyst_id. The description adds no parameter-level meaning (e.g., how analyst_id relates to the entity types it describes), so the baseline 3 applies.

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?

States the specific verb (consulting) and the resources: synthetic domain analysts, C-Suite executive personas, and classic historical thinkers grounded in specialist knowledge graphs. It also names the sibling it is not for (living practitioners → consult_human_agent / request_expert_intro), so an agent can route without opening any schema.

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

Usage Guidelines5/5

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

Explicitly frames the when-to-use case (synthetic/historical analysts) and the when-not case (living practitioners), naming two concrete alternatives. The exclusion plus the named alternatives leave nothing to inference.

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