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

No annotations are present, so the description carries the full burden of behavioral disclosure. It transparently states the filtering rule (title contains 'Claude Code') and the time window (last 90 days), but it does not explicitly affirm that the tool is read-only or side-effect-free. Given the tool's name ('show') and the nature of the query, this is a minor omission rather than a serious gap, but it still prevents a higher score.

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 a single, well-structured sentence that front-loads the primary subject and packs all essential details (scope, time range, and output metrics) without any filler. Every word contributes to the agent's understanding.

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 zero-parameter tool with no output schema, the description lists every output dimension the agent will receive (count, median, p75, p90, share reaching 50 points, top posts) and the exact input scope. Nothing essential for invoking the tool and interpreting its results 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?

The tool has zero parameters, and the input schema confirms this (100% coverage vacuously). With no parameters to document, the baseline score of 4 applies; the description adds no parameter semantics because none are needed.

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 resource (Show HN launches with 'Claude Code' in the title over the last 90 days) and enumerates the exact output metrics (count, median, p75, p90, share reaching 50 points, top posts). This clearly distinguishes it from sibling tools like github_trending or issue_gap_map, which target different datasets and questions.

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 name when to use it over alternatives, but the precise scoping ('every Show HN launch with 'Claude Code' in the title over the last 90 days') makes the intended context unmistakable. An agent can easily infer this tool is for Show HN-specific Claude Code stats, and no sibling offers a similar focused view.

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