analyze_headers

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

With no annotations, the description carries the full burden. It discloses key behavioral traits: uses httpx directly, pure Python, performs a single GET request, and returns scores/grades/recommendations. This is more transparent than many tools, though it doesn't explicitly state it is read-only or non-destructive. The single GET detail effectively communicates the operational behavior.

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 well-structured: a clear one-line purpose, a brief elaboration, then sections for Args, Returns, and Note. Every sentence adds value, and it is concise without being too short. The organization makes it easy to scan.

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 the tool's purpose, how it works, parameters, and return value. Given that an output schema exists and the tool is a simple read-only analyzer, the description is sufficiently complete for an agent to use it correctly. No critical information is missing.

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 description coverage is 0%, and the description compensates by explaining each parameter in the Args section: url, follow_redirects, and timeout_seconds. It adds meaning beyond the bare schema types/defaults, clarifying that follow_redirects affects destination and timeout_seconds controls request duration.

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 HTTP security headers for a web application.' It further specifies it checks for critical security headers and flags information disclosure headers, which is specific and distinguishes it from sibling tools like ssl_tls_check (SSL/TLS) or whatweb_scan (technology detection).

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 through its stated functionality (e.g., 'Checks for the presence and correctness of critical security headers'), but it does not explicitly state when to use this tool versus alternatives or when not to use it. Sibling tools include many scanners, but no direct alternative for header analysis; still, no explicit usage guidance is provided.

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