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autkucakan

market-research

by autkucakan

find_products

Extract product mentions and complaints from evidence to identify market opportunities and support analysis.

Instructions

Find all product mentions and associated complaints extracted across evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
run_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: it does not state read-only nature, ordering, pagination behavior of 'limit', whether results are run-scoped, or what happens for an incomplete run. Only the vague phrase 'extracted across evidence' hints at the data source.

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?

A single efficient sentence with the resource front-loaded and no filler. Brevity is good, though it borders on under-specification given the tool's missing behavioral and parameter detail.

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?

An output schema exists, so return values need not be described, and the tool has only two parameters. However, with no annotations and zero parameter documentation, the description leaves the run-scoping model and pagination semantics unexplained, which is a meaningful gap for a run-scoped extraction query.

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

Parameters2/5

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

Schema description coverage is 0% for both parameters (run_id, limit), and the description supplies no compensating meaning. It never explains that 'run_id' scopes results to an extraction run or that 'limit' caps returned mentions, so an agent gets no help interpreting required vs optional inputs.

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+resource: finding 'product mentions and associated complaints' extracted across evidence. It is clear what the tool returns, though it does not explicitly distinguish itself from the parallel find_needs / find_audiences / find_signals family, which follow the same naming pattern.

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

Usage Guidelines2/5

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

No guidance on when to use this versus the many sibling find_* retrieval tools, nor any prerequisites (e.g. that a completed extraction run is required). The reader must infer usage from the name alone.

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