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Afrotech.guide

Find networking targets

find_networking_targets
Read-onlyIdempotent

Rank approved public attendee profiles against a professional goal using stated role/company/bio/tag context only. Never infer sensitive traits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
goalsNo
limitNo
queryNoNatural-language search terms, e.g. AI founders, cybersecurity recruiters, dinner.
rolesNo
companiesNo
preferPhotosNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
guideYes
dataPolicyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / preferPhotos
      Added value: +{
      +  "default": true,
      +  "type": "boolean"
      +}
  2. First observed

TDQS

A3.6/5.0
Behavior4/5

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

The description adds critical behavioral context beyond annotations: it discloses the ranking is based on 'stated role/company/bio/tag context only' and the constraint 'Never infer sensitive traits.' Annotations already declare readOnly/idempotent, so this ethical/scope disclosure is valuable additional transparency. It doesn't cover output format, but output_schema exists.

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 tight sentences with no waste. The core ranking operation and the critical constraint are both front-loaded.

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 7-param read-only ranking tool with an output schema, the description adequately states the scope and ethical boundary. It is missing parameter usage guidance, but the output schema handles returns and annotations handle safety. The context is complete enough for an agent to invoke correctly, though not richly detailed.

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 14%, so the schema documents only the 'query' parameter. The description does not explain the other six parameters (tags, goals, limit, roles, companies, preferPhotos) or how they interact. Baseline 3 is generous given the low coverage; description adds little parameter meaning.

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?

Clear specific verb 'Rank' and resource 'approved public attendee profiles' distinguished from the sibling search_people which finds people rather than ranking them against a goal. However, it doesn't explicitly name search_people as the alternative or clarify why an agent would rank rather than search.

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 explicit when/when-not guidance. The description implies usage when you have a professional goal, but never states when to use this vs search_people or other discovery tools. Sibling differentiation is absent.

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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