lookup-disclose-io

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

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds 'No network calls — instant response,' which is valuable behavioral context. However, it does not describe the output format or any side effects, leaving some uncertainty for the agent.

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 very concise with three short sentences that front-load the purpose. No unnecessary words or repetition; every sentence adds value.

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 simple tool (one param, no output schema, annotations present), the description covers purpose, behavior, and usage context. However, it lacks explicit mention of the return value format or classification categories, which would help an agent interpret the output.

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% with one required string parameter described as 'The input to classify.' The description adds meaning by listing example input types (domain, IP, package, repository), which clarifies what the parameter accepts beyond the generic schema description.

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 verb 'classify' and the resource 'input as a domain, IP, package, repository, etc.', providing specific examples. It distinguishes from the sibling tool 'lookup_security_contact' by emphasizing classification before a full lookup.

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 gives explicit context for use: 'Useful for understanding what an asset is before performing a full lookup.' It also notes 'No network calls — instant response' to set expectations. However, it does not explicitly state when not to use or list alternatives, though the sibling is different enough.

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

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

The description adds behavioral context beyond the annotations by explaining that results are 'ordered by applicability to the queried owner and asset' and that the information is 'informational only — not legal advice.' This complements the readOnlyHint and openWorldHint annotations without contradicting them. It does not mention error handling or rate limits, but for a read-only lookup this is reasonably 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 three sentences long, front-loaded with the primary purpose, and each sentence adds distinct value: what it does, what inputs it accepts, what outputs it returns, and a caveat. There is no redundancy or filler, making it concise and well-structured for an AI agent to process quickly.

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?

Since there is no output schema, the description compensates by listing the return categories (bug bounty programs, security.txt contacts, VDP links, abuse contacts, CERT fallbacks) and the ordering rule, which gives the agent a good sense of what to expect. It does not detail the exact result structure or behavior on empty results, but for a simple lookup tool this is sufficient context.

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 describes both parameters thoroughly, including example values for 'asset' and the full enum for 'asset_type'. The description's list of supported asset types largely mirrors the schema's 'asset_type' enum and adds no new semantic meaning beyond what is already in the schema. With 100% schema description coverage, the description does not need to compensate, so baseline 3 is appropriate.

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 with a specific verb ('Find') and resource ('security reporting channels for responsible vulnerability disclosure'). It also lists a wide range of supported asset types and output categories, distinguishing it from the sibling tool 'classify_asset' by its focus on contact lookup rather than classification.

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 the tool through its clear purpose statement and asset type list, but it does not explicitly contrast it with sibling tools or provide exclusions (e.g., 'use classify_asset for asset classification'). There's no direct when-to-use/when-not-to-use guidance, making it adequate but not strong.

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