analyze_project

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 analyzes and suggests, but doesn't describe what 'analyze' entails (e.g., file scanning, dependency parsing), potential side effects (e.g., no changes made), performance considerations (e.g., time-intensive for large directories), or output format. This is inadequate for a tool with no annotation coverage, leaving key behavioral traits unspecified.

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, efficient sentence: 'Analyze project directory to detect technologies and suggest missing tasks.' It is front-loaded with the core purpose and avoids unnecessary details. However, it could be slightly more structured by separating the two outcomes (detection and suggestion) for clarity, but overall it's concise and to the point.

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 complexity of analysis tasks, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'technologies' are detected (e.g., programming languages, frameworks), how 'missing tasks' are suggested (e.g., based on best practices), or the return format. For a tool with no structured behavioral or output information, this leaves significant gaps for an AI agent to understand and use it effectively.

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% description coverage, with the single parameter 'projectPath' documented as 'Path to project directory to analyze (defaults to current directory).' The description adds no additional meaning beyond this, such as path format requirements or validation rules. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to given the schema's completeness.

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: 'Analyze project directory to detect technologies and suggest missing tasks.' It specifies the verb ('analyze'), resource ('project directory'), and outcomes ('detect technologies and suggest missing tasks'). However, it doesn't explicitly distinguish this from sibling tools like 'check_devpipe' or 'validate_config', which might have overlapping analysis functions, so it doesn't reach the highest score.

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 prerequisites, context (e.g., use for initial project setup or periodic reviews), or exclusions (e.g., not for real-time monitoring). With many sibling tools like 'check_devpipe' and 'validate_config', the lack of differentiation leaves the agent guessing about appropriate usage scenarios.

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