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timmKal01

ke-tenders-audit-mcp

by timmKal01

supplier_profile

Profile a supplier company to see bids listed, awards won, win rate, buyers, and single-bidder wins via fuzzy company-name matching. Returns company records only, never personal details.

Instructions

Profile a supplier company: bids listed, awards won, win rate, buyers, single-bidder wins.

Uses fuzzy matching on the company name. Company records only, never personal details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose two non-obvious traits: input is resolved by fuzzy matching (so the name need not be exact), and output is restricted to company records with no personal details. It stops short of confirming read-only status, coverage limits, or rate/cost behavior.

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 short sentences with zero filler. The output contents are front-loaded and the two caveats (fuzzy matching, no personal data) follow immediately. Every clause earns its place.

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?

An output schema exists, so return values needn't be explained, and input semantics are covered. The remaining gap is temporal scope — win rate, buyers, and single-bidder wins are period-dependent, and the description never states the time window covered.

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

Parameters4/5

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

Schema coverage is 0% for the single 'name' parameter, so the description must compensate — and it does, specifying that matching against the supplied name is fuzzy rather than exact. That is the key semantic an agent needs, though no example format or minimum-length guidance is given.

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 (Profile) and resource (supplier company), then enumerates exactly what the profile contains: bids listed, awards won, win rate, buyers, single-bidder wins. This distinguishes it implicitly from siblings like search_awards (raw award lookup) and check_red_flags (anomaly detection), though no sibling is named 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?

Usage is only implied — an agent can infer you call this to get an aggregate picture of one company, versus search_awards for individual records. There is no explicit when-to-use, when-not-to-use, or named alternative among the five siblings, and no stated prerequisites.

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