fetch_verified_context

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

No annotations are provided, so the description carries full burden. It explains the output format (verified_context block with STRICT RULES) and parameter constraints (max_results default/max). However, it does not explicitly state that the tool is read-only or non-mutating, nor mention failure modes or rate limits. This leaves minor ambiguity, but the overall behavior is well described.

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 well-structured with a purpose sentence, usage paragraph, and parameter definitions. It is front-loaded with the key action. While clear, it could be slightly more concise (e.g., combining the usage instructions). Every sentence is valuable, so minor trim could improve.

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?

With no annotations or sibling tools, the description adequately covers all aspects: purpose, usage, parameters, and expected output format (<verified_context> block with rules). It lacks explicit mention of edge cases (e.g., no results) but is sufficient for an agent to understand and use the tool effectively.

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 coverage is 0%, so the description must compensate. It does so effectively: query is described as 'the factual topic or question to ground,' and max_results as 'how many web sources to pull (default 3, max 5).' This adds contextual meaning beyond the schema's titles and types, making the parameters fully understandable.

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 clearly states the tool's purpose: 'Fetch real, source-of-truth web text for a topic and wrap it in a strict fact-anchoring guardrail.' It specifies the action (fetch), resource (web text), and outcome (guardrail for fact-anchoring). With no sibling tools, differentiation is not needed.

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?

The description explicitly instructs: 'Use this tool BEFORE answering any factual question. Then answer the user strictly from the returned <verified_context> block.' It includes detailed rules (never guess, cite sources, avoid pre-trained knowledge), providing clear guidance on when and how to use the tool.

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