web_search

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses that SearXNG is lazily started as a local Docker container on 127.0.0.1:8888, that results are unverified candidates/snippets, and that web_read should be used for verification.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded and dense: each sentence has a distinct job, covering purpose, usage, reliability caveat, research strategy, service behavior, and engine/category pinning without waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema exists, so return values need not be explained. However, with 8 parameters and 0% schema description coverage, the description is enough for basic query invocation but incomplete for advanced controls like pagination, language, time_range, and safe_search.

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

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. It only adds meaning for engines and category, leaving page, limit, language, time_range, safe_search, and query semantics largely unexplained, including valid value formats for time_range and safe_search.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource: 'Searches the public web through the user's local SearXNG service.' It also distinguishes this from the sibling tool by noting results are candidates/snippets and that important sources should be read with web_read.

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

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

It explicitly says when to use the tool ('when current or external information materially helps the task') and when to switch to web_read ('before relying on them'). It also advises multiple targeted queries for comprehensive research and gives examples for engine/category pinning.

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