count_word_occurrences

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool scrapes a web page and returns a dictionary, which is useful, but it omits caveats about network dependency, page size limits, site accessibility, or what the vague 'additional info' actually contains.

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: a one-line summary, brief explanation, Args section, and Returns section. However, the first two sentences are somewhat redundant ('Count occurrences...' and 'This tool scrapes... counts...'), which slightly reduces tightness.

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?

For a simple tool with three parameters, the description covers inputs, behavior, and return type adequately. It does not specify the exact structure of the returned dictionary or note edge cases such as unavailable pages, but given the tool's simplicity, the remaining gaps are relatively minor.

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 for the schema's bare types. The Args section clearly explains all three parameters, including the url to analyze, the word to count, and the case_insensitive behavior with its default. It fully adds meaning beyond the structured schema.

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 states a specific verb-resource combination ('Count occurrences of a specific word on a web page') and clearly distinguishes the tool from siblings: scrape_web (raw content retrieval) and search_docs (searching documentation). The purpose is immediately obvious.

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 purpose makes the tool's usage context clear: use it when you need word frequency from a web page. However, it does not explicitly contrast with alternatives or state exclusions for when another tool would be better, so it stops short of full usage guidance.

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