urlhaus_lookup_url

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

With no annotations provided, the description carries the burden of behavioral disclosure. It discloses that the tool performs a lookup and returns specific data types plus pivot suggestions, which is useful. However, it does not mention any rate limits, authentication needs, or behavior when no results are found. For a read-only lookup tool this is adequate but not exceptional.

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 short sentences with no filler. The core action and purpose are front-loaded, followed by the return values and the pivot-generation feature. Every sentence adds distinct value without redundancy.

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?

For a single-parameter lookup tool with no output schema and no annotations, the description covers the core need: what it does, what it returns, and how it can feed further analysis. It could be more complete by describing the response format or empty-result handling, but the listed outputs and pivot suggestion make it sufficiently actionable.

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 already provides 100% coverage for the single 'url' parameter, including a concrete example. The description does not add meaning beyond what the schema offers—it restates that the tool looks up a URL without adding format constraints, normalization rules, or edge-case guidance. Baseline 3 is appropriate given the schema's completeness.

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 uses a specific verb ('Look up') with a clear resource ('a URL in URLhaus') and states the investigative purpose ('check if it distributes malware'). It also enumerates the return contents (payload hashes, imphashes, malware tags) and pivot suggestions, which distinguishes it from sibling URLhaus tools that look up by host or tag.

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 when to use this tool: when you have a URL and want to check it against URLhaus. The mention of 'Generates pivot suggestions for chained analysis' gives some context for integration into a workflow, but it does not explicitly state when not to use it or name alternatives like urlhaus_lookup_host or urlhaus_lookup_tag.

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