arjun_discover

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

With no annotations, the description carries the burden of behavioral disclosure. It notes that Arjun sends many requests and that JSON/XML modes test parameters in the request body, giving useful insight into runtime behavior. It does not cover potential auth or side effects, but the core behavior is transparent.

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 with Args, Returns, and Note sections. Every sentence adds value; no redundancy or fluff. The main purpose is front-loaded, and the notes are concise but informative.

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 presence of an output schema and 4 relatively simple parameters, the description fully covers prerequisites, behavior, and parameter semantics. It even includes return value information despite the output schema existing, making it self-contained.

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 0%, so the description must explain all parameters. It does: url, method with options, optional wordlist, and timeout override. This adds meaning beyond raw types, though it omits default timeout details and wordlist format specifics.

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 opens with a specific verb and resource: 'Discover hidden HTTP parameters in web endpoints using Arjun.' This clearly distinguishes it from sibling tools like ffuf_fuzz or gobuster_scan, which focus on fuzzing or directory enumeration.

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 clear usage context: target must be in allowed_hosts, and it warns about rate-limited endpoints. It does not explicitly name alternative tools or state when not to use it, but the context is sufficient for selection.

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