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Search AI deployments

search_deployments
Read-onlyIdempotent

Rows of The Deploy Log whose company, subject or what shipped contains the words given, newest first. Each row carries the publisher's own source URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many rows, 1 to 25, default 10
queryYesWords to find, for example a model, a product or a company

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare a safe, idempotent, closed-world read, so the safety bar is met structurally. The description adds real behavioral context beyond that: results are ordered newest-first, matching is restricted to company/subject/what-shipped fields, and each row exposes the publisher's source URL. It stops short of stating limits or result-count behavior, but the additions are substantive.

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, no filler, with the resource and ordering constraint front-loaded and the return-content note last. 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?

With only two parameters, full schema coverage, and annotations covering safety, the description supplies the remaining essentials: match scope, ordering, and that rows include a source URL (useful given no output schema). It could note result-count/pagination behavior but no critical gap remains.

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 100%, so the baseline is 3. The description goes beyond the schema by naming which fields the query term is matched against (company, subject, what shipped), which the schema's generic 'Words to find' text does not convey. It does not elaborate on limit, which the schema handles.

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: returning rows of 'The Deploy Log' whose text fields match a query. The keyword-match framing implicitly separates it from the recency-oriented siblings (deployments_in_week, recent_deployments), but it never names them, so the differentiation is inferred rather than stated.

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 implied: this is the free-text search tool, so an agent can guess it is for keyword lookups rather than time-window listings. However, there is no explicit 'use this when... use X instead when...' routing against the two sibling tools, leaving the choice to inference.

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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