databutler-provenance

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

Annotations already declare read-only, idempotent and open-world behavior, so the description is not carrying the safety burden. It adds real value beyond them by disclosing the returned data set (registration age, registrar, nameservers, status, registrant redaction) and the edit-distance/brand-substring typosquat logic, plus an interpretation caveat. It omits failure behavior (e.g. no RDAP record, rate limiting).

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?

Front-loaded with the core question, then mechanism, then outputs, then the interpretive caveat. Three sentences, each carrying distinct information with no repetition of the name or title.

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?

With no output schema, the description compensates by enumerating what the lookup returns, and the single parameter is trivial. For a one-argument read-only lookup, an agent has everything needed to call it and interpret the result.

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?

Single required 'domain' parameter with 100% schema description coverage, so the schema already documents the input. The description adds no format or normalization guidance beyond the schema's 'example.com' example — baseline 3 applies.

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?

States a specific question ('Who runs this domain?') and a concrete mechanism ('Live RDAP lookup'), then enumerates the resource attributes returned (registration date/age, registrar, nameservers, status, redaction) plus a typosquat check. The domain-vs-package distinction from the sibling package_provenance is obvious from the resource itself.

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?

Gives clear usage context — recently registered domains resembling banks or big brands as a phishing signal — and instructs how to report the result ('as a signal, not a conclusion'). It does not name alternatives or state exclusions, so it stops short of full when/when-not guidance.

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?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: this is a live network lookup (freshness/latency implication) and it enumerates the fields returned, including a typosquat heuristic. It does not mention failure modes for unknown packages.

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?

Front-loaded with the two questions an agent actually has, then the data returned, then the usage condition. Dense but every clause carries information; the interrogative opener is slightly less efficient than a declarative verb phrase.

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?

With no output schema, the description compensates by enumerating the returned fields (first-publish date/age, release count, latest version, maintainers, linked repo, typosquat result) and the scenario that warrants a call. Nothing an agent needs to decide or invoke 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 100% with only two parameters, so the schema already documents name and the npm/pypi enum. The description reinforces the ecosystem scope but adds no syntax, format, or edge-case detail beyond it; baseline 3 applies.

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?

States a specific verb and resource (publishers of a package, typosquat status) plus the exact lookup source (live npm or PyPI). It is clearly distinguishable from the sibling domain_provenance because it names the artifact type it operates on.

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?

"Use when an agent is about to install or recommend an unfamiliar dependency" gives a concrete triggering condition. There are no explicit exclusions or alternatives named, but the context is unambiguous.

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