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Run a web query to discover candidate sources and return URLs with titles, snippets, and engine metadata. Each URL is registered, making it available for reading.

Instructions

Discover candidate sources. Runs a search-engine query and returns URLs with titles, snippets, and engine metadata. Registers each URL as discovered; this is the sole way a URL becomes readable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
sinceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full disclosure burden and does well on the non-obvious trait: it explicitly states the side effect that each URL is registered as discovered and that this is the only path to readability. It omits other behavioral context (rate limits, network/auth requirements), which is a gap but not a major one for a search tool.

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?

Three tight sentences, front-loaded with the purpose, then behavior, then the key constraint. Every sentence adds a distinct piece of information and nothing is repeated or padded.

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 need not be re-explained, and the description usefully still names what comes back. The remaining gap is the undocumented 'since' parameter, but for a two-parameter tool with a rich output schema the description is otherwise complete enough to call correctly.

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%, so the description must compensate for both parameters. It conveys the meaning of 'query' indirectly ('Runs a search-engine query') but says nothing at all about 'since' (the date-time filter), leaving one of two parameters completely unexplained in both the schema and the description.

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?

The description states a specific action ('Runs a search-engine query') and concrete output ('URLs with titles, snippets, and engine metadata'), plus the higher-level goal ('Discover candidate sources'). It reads clearly as the web-search entry point, but it never explicitly names or contrasts with siblings like corpus_search or grep, leaving the agent to infer the boundary.

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 context is implied: 'Discover candidate sources' and 'the sole way a URL becomes readable' signal this is the first step before read/open. However, it gives no explicit when-to-use vs alternatives (corpus_search, grep), no when-not-to-use, and no prerequisites, so the routing guidance is inferential rather than stated.

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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