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

No annotations are provided, so the description carries the burden of behavioral disclosure. It only states the basic function (analyze, detect, return) without explaining side effects, read-only status, error handling, or what exactly 'validation rules' means. This leaves significant ambiguity for a tool with no annotations.

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 sentence of 12 words, front-loaded with the core action ('Analyze project architecture'). Every word contributes meaning, and there is no redundancy or filler.

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?

The tool has one simple parameter and no output schema or annotations, so the description must carry the full context. It covers the main function but leaves key details unexplained, such as what 'validation rules' are, how they are returned, and any prerequisites or limitations. This makes it adequate but incomplete.

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 schema already provides a description for the 'path' parameter (100% coverage). Since there is only one parameter and its meaning is fully documented in the schema, the description adds no additional param semantic value. Baseline 3 is appropriate.

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 clear verb ('analyze') and resource ('project architecture'), and adds expected outputs (detect language, return validation rules). It does not explicitly distinguish from find_similar_code, but the purpose is unambiguous enough that a 4 is appropriate.

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 its usage by stating what it does, but it provides no explicit guidance on when to use this tool versus find_similar_code, nor any exclusions or alternative recommendations. This is a case of implied usage.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to state that the tool is read-only, how 'similar' is determined, or whether there are any side effects. The description is minimal and does not add meaningful behavioral context beyond the basic action.

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 sentence that front-loads the action ('Find existing similar') and clearly states the scope ('in the project'). It contains no extraneous information and is appropriately sized for the tool's simplicity. Every word 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?

The tool is relatively simple with three optional parameters and no output schema. The description explains the core purpose but omits details about what the results look like, how the search behaves, or any limitations. For a basic search tool, this is adequate but not comprehensive, leaving the agent without expectations for return format or edge cases.

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 input schema has 100% coverage: each parameter has a description (path, search_term, component_type). The tool description itself adds little beyond the schema, but it does align with the 'component_type' parameter by mentioning 'components, functions, or patterns'. Since the schema already explains parameters, a baseline of 3 is appropriate.

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 clearly states the tool's function: 'Find existing similar components, functions, or patterns in the project'. It uses a specific verb and resource, effectively differentiating it from the sibling tool 'analyze_architecture' by focusing on finding similar code rather than analyzing architecture. However, it does not explicitly name alternatives or contrasts, so it stops short of a 5.

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 provides no explicit guidance on when to use this tool versus alternatives. It implies usage for locating reusable code but omits any context about scenarios where it would be preferred over 'analyze_architecture' or other approaches. There are no exclusions or prerequisites mentioned.

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