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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered structurally. The description adds only the 'current' freshness implication — it says nothing about caching, staleness, or what happens when a slug isn't found.

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?

Two short sentences with the usage condition front-loaded, followed by a callable example. Zero filler; every element earns its place.

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 one-parameter read tool with no output schema and full annotation coverage, the description is nearly complete. It tells the agent what domain of data comes back ('pricing or facts'), though it could hint at the response shape or missing-slug behavior.

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% and the slug parameter already carries examples in the schema. The description's example {"slug":"cursor"} mirrors the schema rather than adding new meaning, so baseline 3 is appropriate for a single fully-documented parameter.

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?

States a specific verb+resource ('facts for one AI coding tool or agent harness by slug') and gives concrete slug examples. This scope (single tool, keyed by slug) implicitly separates it from siblings like compare_tools, find_tool_for_task, and get_tool_trends, though none are named explicitly.

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?

'Use when you need current pricing or facts' gives a clear triggering condition, which is better than nothing. However it names no exclusions and does not route to alternatives such as compare_tools or find_tool_for_task, leaving the agent to infer when a different sibling is more appropriate.

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