find_code_hotspots

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

With no annotations, the description must disclose behavior itself. It explains the algorithmic approach and output type, but does not state whether the tool is read-only, performance expectations, or prerequisites (e.g., whether CodeRank data must exist). This is adequate but not rich.

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 compact and well-structured: an intro statement, a clear Args list, and a Returns line. No filler or redundant information, and every sentence adds value.

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 tool with no annotations and no output schema, the description covers purpose, parameters, and output sufficiently for initial understanding. It lacks edge-case behavior and dependencies, but the core functionality is well explained.

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 Args list provides concise explanations for all five parameters, which is crucial given 0% schema description coverage. Each parameter's role is clear (e.g., 'min_connections: Minimum import connections to consider'). However, explanations lack format constraints (e.g., path types) beyond what the schema defaults imply.

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 'Identify code hotspots by combining CodeRank with symbol usage frequency,' clearly specifying the verb, resource, and method. This differentiates it from sibling tools like coderank_analysis (likely CodeRank-only) and get_commit_hotspots (hotspots from commits).

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 implies the intended use (combined connectivity and usage) but does not explicitly state when to use this tool over alternatives or provide any exclusions. No direct comparison to sibling tools is given, so guidance is inferred rather than explicit.

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