generate_codebase_analysis_prompt

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'generates' a prompt, implying a creation or assembly action, but doesn't clarify if this involves data processing, API calls, or other behaviors. Missing details include potential side effects, error handling, or output format, which are critical for a tool with no output schema.

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 efficiently conveys the core action and parameters without unnecessary words. It's front-loaded with the main purpose, making it easy to parse quickly. Every part of the sentence earns its place by specifying key elements like 'assembled,' 'codebase analysis prompt,' and the parameters.

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?

Given the tool's complexity (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the output (e.g., what the generated prompt looks like), behavioral traits, or parameter details. For a tool that generates content, more context is needed to guide effective use, especially with siblings that might overlap in functionality.

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 description mentions parameters ('technology stacks and analysis focus areas'), but with 0% schema description coverage, it doesn't add meaningful semantics. It fails to explain what 'technology_stack' and 'analysis_focus' arrays should contain (e.g., strings, objects), their expected formats, or examples. This leaves the two required parameters largely undocumented, not compensating for the schema 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?

The description clearly states the tool's purpose: 'Generate an assembled codebase analysis prompt with specified technology stacks and analysis focus areas.' It uses specific verbs ('generate,' 'assembled') and resources ('codebase analysis prompt'), making the action clear. However, it doesn't differentiate from siblings like 'get_codebase_analysis_template' (which might retrieve a template rather than generate a prompt), leaving room for improvement.

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 guidance on when to use this tool versus alternatives. It doesn't mention siblings such as 'generate_bug_analysis_prompt' or 'get_codebase_analysis_template,' nor does it specify prerequisites, contexts, or exclusions. This lack of comparative information makes it harder for an agent to choose correctly among related tools.

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