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

Beyond the readOnlyHint=true annotation, the description discloses substantial behavior: answers are grounded in codefmt's own content, returned with cited source URLs and a confidence score (0-1 weighted toward rarer terms), and refused rather than hallucinated when the match is too weak. This is far richer than the annotation alone and fully consistent with it.

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 dense and mostly front-loaded, with scope information first and behavioral constraints second; every clause carries useful information. However, it is a single long running sentence — a two-sentence structure would be easier for an agent to parse.

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 one parameter and no output schema, the description carries the full burden of explaining the return: a grounded answer, cited source URLs, a confidence score with a precise definition, and the refusal mode. Nothing essential to invoking the tool or interpreting its result is missing.

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 100% for the single query parameter, which is already defined as 'the natural-language question about codefmt'. The description adds no additional parameter-level meaning (format, length, examples, constraints), so the baseline of 3 is appropriate: schema does the heavy lifting and the description does not compensate further.

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 names a concrete action and resource: ask a natural-language question about codefmt, specifically its formatting and linting scope (JavaScript, Python, HubL, automation platforms). Its scope is explicit enough that an agent can distinguish it from the sibling formatting tools format_code and format_json without inspecting either schema.

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 gives clear routing context: the tool answers on-topic questions about codefmt formatting/linting for the listed languages and platforms, and off-topic or too-weakly-matched questions are refused rather than guessed. It does not explicitly name sibling tools or state 'use format_code instead for execution', so it stops short of a full when-to-use versus when-not-to-use treatment.

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