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confirm_themes

Confirm selected interview themes to generate a tailored questionnaire probing forward predictions, contrarian stances, and methodology edge cases; include flagged finding IDs and notes.

Instructions

Confirm the selected themes to generate the interview questionnaire tailored to probe forward predictions, contrarian industry stances, and practical methodology edge cases for the audio interview. Can pass flaggedFindingIds and flagNote if the expert flagged any research findings as wrong or not theirs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
themesYesArray of confirmed theme names
userIdNoOptional user identifier.
flagNoteNoOptional note from the expert explaining why certain findings were flagged.
flaggedFindingIdsNoIDs of any research findings the expert flagged as incorrect, outdated, or not theirs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.3.3

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=false, so the mutation profile is partly covered. The description usefully adds that confirming triggers questionnaire generation and that flagged findings can be attached, but says nothing about reversibility, permissions, or what confirmation commits to.

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?

Two sentences with the primary action and outcome front-loaded, followed by optional-parameter context. No filler, though the second sentence is slightly dense.

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?

There is no output schema, so return values need not be explained, but the description omits sequencing/prerequisites in what appears to be a multi-step onboarding flow (detect themes -> confirm -> interview). Adequate but leaves workflow position ambiguous.

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 the schema fully documents all four parameters. The description only adds a conditional usage note for flaggedFindingIds/flagNote ('if the expert flagged any research findings as wrong or not theirs'), which is close to what the schema already states – so the baseline 3 holds.

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?

States a specific verb (confirm) plus resource (themes) and the downstream outcome (generating a tailored interview questionnaire). This clearly separates it from siblings like get_detected_themes or schedule_interview, though it never names an alternative explicitly.

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 implies the workflow role – confirm themes so the questionnaire can be generated for the audio interview – but gives no explicit when-to-use/when-not or prerequisite (e.g. that themes must first be detected/selected). Usage must be inferred from context.

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