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coeus_web_search

Run web searches across configured providers to retrieve fresh, domain-filtered results for engineering research and verification tasks.

Instructions

Requires a configured retrieval backend and returns an error without one; does not search the web by prompting a chat model

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel
queryYesQuery
languageNoLanguage
num_resultsNoNum results
safe_searchNoSafe search
freshness_daysNoFreshness days
allowed_domainsNoAllowed domains
blocked_domainsNoBlocked domains

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

C2.6/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It discloses a key prerequisite (configured retrieval backend) and a failure mode (returns error without one), and clarifies the mechanism (not chat-based). However, it omits other important behaviors such as output format, rate limits, or error handling beyond the missing backend. It adds some value but not comprehensive transparency.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it is somewhat cryptic and not front-loaded with the core purpose. It leads with a prerequisite rather than the action, and the exclusion clause could be confusing. It is not verbose, but the structure could be improved for clarity.

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

Completeness2/5

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

Given 8 parameters, no output schema, and no annotations, the description is significantly under-specified. It does not explain what the tool returns, how results are formatted, or how parameters interact. An agent would lack critical information to call the tool correctly and interpret results.

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?

The input schema has 100% coverage, but each parameter description is merely the parameter name itself (e.g., 'Model', 'Query'), providing negligible semantic value. The tool description adds no parameter explanations, so it fails to compensate for the schema's lack of meaningful descriptions. The agent receives no clarity on expected formats, constraints, or relationships between parameters.

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

Purpose3/5

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

The description focuses on prerequisites and exclusions rather than explicitly stating that the tool performs web searches. It implies the function through 'retrieval backend' and the tool name, but lacks a clear verb+resource statement like 'Searches the web using a configured retrieval backend.' It distinguishes itself from chat-based search but does not directly say what it does.

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?

The description mentions a requirement (configured retrieval backend) and clarifies it is not chat-model based, but does not provide explicit when-to-use guidance or name alternative tools. With siblings like coeus_web_fetch and coeus_ask, it leaves the agent to infer when to choose this tool over others.

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