analyze_dataflow

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

No annotations are provided, so the description must disclose behavioral traits. It states the tool follows variable assignments through code, but does not mention whether it modifies code, requires authentication, has rate limits, or any side effects. As a static analysis tool, it likely has no side effects, but this is not stated.

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 two sentences, front-loaded with the core action. Every sentence adds value: the first defines the operation, the second explains its benefit over regex rules. No wasted words.

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 description covers purpose and methodology well, but lacks details about output format or return value structure. Since no output schema exists, the description could briefly state what the tool returns (e.g., list of vulnerabilities). This is a minor omission.

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, with each parameter described. The description adds no additional parameter meaning beyond the schema, but it does set context for 'code' as the analysis target. Baseline 3 applies due to full schema 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's purpose: tracking user input into dangerous sinks to detect injection vulnerabilities. It specifies the types of sinks (SQL queries, eval, file operations, redirects) and distinguishes itself from regex-based approaches, but does not explicitly differentiate from sibling tool 'analyze_cross_file_dataflow' which likely handles multi-file 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 usage for detecting injection vulnerabilities that regex rules miss, but provides no explicit guidance on when to use this tool versus siblings or alternatives. It lacks context on prerequisites, such as requiring complete code or specific language support.

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