analyze_code

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states the tool 'analyzes' but does not clarify whether it is read-only, what output is produced, or if any side effects occur (e.g., report generation). This is a significant gap given the absence of 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 that is concise and front-loaded with the main action. It lists the issue categories efficiently without wasted words, though it could benefit from slightly more structure (e.g., bullet points).

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 lack of an output schema and annotations, the description is incomplete. It does not mention what happens after analysis (e.g., returns a report, saves results) or how the agent can access the results. Sibling tools like 'export_report' suggest downstream steps, but this connection is not made.

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 coverage is 100% with a single parameter that already has a description ('Absolute path to the frontend source directory'). The tool description adds no further parameter-specific meaning, meeting the baseline for high coverage.

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 analyzes frontend source code for a specific set of quality issues (accessibility, CSS, complexity, design, performance). It distinguishes itself from more specialized sibling tools like accessibility_audit or performance_audit by offering a broad, combined analysis.

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 a general analysis use case but provides no explicit guidance on when to choose this tool over the many specialized sibling tools. It lacks when-to-use/when-not-to-use context, leaving the agent to infer the appropriate scenario.

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