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

With no annotations provided, the description carries the full burden and does disclose key behavioral traits: a concrete cost ($0.25 Base USDC) and the guarantee that code is 'parsed/reviewed but never executed or retained'. That is meaningful safety and billing context, though it omits any latency, rate limit, or failure-mode detail.

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 tight sentences with no filler; price and safety posture are front-loaded before the capability list, so the agent sees the constraints immediately.

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?

Purpose, cost, and non-execution/non-retention are covered, but with no output schema the description says nothing about the shape of the review result (findings, severities, repair suggestions format), and the language parameter behavior is unexplained.

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 0%, so the description must compensate. It conveys that 'code' is the source under review and 'intent' is the intended behavior it is checked against, but the third parameter (language, defaulting to python) is never referenced, leaving a documented gap.

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 ('Review') and resource ('caller-supplied Python source') plus an explicit scope: high-confidence bugs, security issues, missing edge cases, and repair suggestions. No sibling tool overlaps with code review, so an agent can select it unambiguously.

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?

Usage is implied through 'caller-supplied Python source against its intended behavior', which hints that the caller must provide both code and intent, but there is no explicit when-to-use, when-not-to-use, or alternative routing guidance.

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