ffuf

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

With no annotations, the description carries the full burden. It discloses the output format (matched URLs with status codes and response sizes) and implies active scanning, but does not warn about potential intrusiveness, rate limiting, or authentication requirements. It provides basic behavioral context but omits safety/operational caveats that an agent should know for an active fuzzing tool.

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 four sentences with zero redundancy. It front-loads the core purpose, immediately gives usage guidance, then routes to alternatives, and ends with output format. Every sentence earns its place.

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 no output schema and no annotations, the description covers the essentials: purpose, usage, alternatives, output format, and key parameter semantics. It does not mention operational caveats like network scanning noise or permission requirements, but for a well-known tool with clear input schema, it is largely complete.

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%, so baseline is 3. The description adds value by explaining the FUZZ keyword placement, giving examples for target, and clarifying the default for match_code. This goes beyond the schema's bare descriptions, particularly for the target parameter where the FUZZ concept is critical.

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 is a web fuzzer with specific capabilities (directory discovery, vhost enumeration, parameter/header fuzzing) and differentiates it from siblings like gobuster and wfuzz by naming them explicitly. The verb 'fuzz' and resource 'web' are specific and unambiguous.

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 explicitly tells when to use ffuf ('high-performance fuzzing tasks'), how to use it (place FUZZ keyword), and when not to use it ('simpler directory scans use gobuster or dirb', 'HTTP parameter brute-force use wfuzz'). This is exemplary guidance with named alternatives.

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