fetch_robots

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

No annotations are provided, so the description must disclose behavioral traits. It only says 'Fetch and analyze' without detailing network behavior (e.g., redirects, timeouts, error handling) or the output format. This leaves significant uncertainty for an agent.

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 two sentences, efficiently covering purpose and return. It is not verbose, but could be more structured (e.g., bullet points) for clarity. Still, it earns a high score for brevity.

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?

Given the tool is simple (1 param, no output schema), the description covers core purpose and return. However, it lacks details on error conditions (e.g., missing robots.txt) and does not explain how analysis works, which with siblings like 'analyze_robots' creates ambiguity.

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 100% with one parameter 'url' described as 'The website URL to fetch robots.txt from'. The description repeats this purpose but adds no new semantics like expected format restrictions or handling of fragments. It meets the baseline but adds no extra value.

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 fetches and analyzes a robots.txt file from a URL and returns which AI bots are blocked or allowed. It differentiates from siblings like 'analyze_robots' (which likely works on already fetched content) and 'generate_robots' (which creates files).

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 does not explicitly state when to use this tool versus alternatives like 'analyze_robots' or 'check_bot_status'. It implies usage for fetching from a URL but provides no exclusions or context for choice.

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