Given a finding id, return what was measured, when, by whom, and the address it can be checked at. For an agent quoting a figure into a review. Requires a key; see https://sighttrue.com/pricing.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the need for an API key ('Requires a key; see https://sighttrue.com/pricing') and specifies the kind of information returned. It does not mention side effects or error behavior, but for a simple read-style tool this is adequate behavioral context.
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 compact and front-loaded: the first sentence states the primary purpose, the second sentence adds the use case and auth requirement. Every sentence earns its place, and there is no redundant content.
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 tool's simplicity (one parameter, no output schema, no annotations), the description does a good job: it explains what the tool does, when to use it, what it returns, and the auth requirement. It lacks details on failure modes or exact output formatting, but these are less critical for a straightforward lookup tool.
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 schema only defines 'id' as a string with no description, and schema coverage is 0%. The description compensates by clarifying that the id is a 'finding id', giving it semantic meaning beyond the raw type. However, it does not elaborate on the format or source of the id, so it only partially compensates for the missing parameter documentation.
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 function with a specific verb ('return') and resource ('what was measured, when, by whom, and the address'), and distinguishes it from siblings by focusing on explaining a single finding. It also names the input ('finding id'), making the purpose 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 provides a clear usage context: 'For an agent quoting a figure into a review.' This tells when to use the tool, but it does not mention alternatives or when not to use it, so it falls short of full explicit distinction from sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools overlap significantly: check_package, check_before_install, check_stack, and audit_manifest all inspect dependencies, while check_provider and provider_incidents both return incident data. Descriptions help somewhat, but the boundaries between these tools are unclear and could easily cause misselection.
Tool names follow no consistent pattern: some start with verbs (check_*, list_*, search_*), others are noun phrases (advisory_severity, domain_risk, provider_incidents), and one is a clause (who_can_publish). The mixed conventions reduce predictability and make it harder to infer tool behavior from the name.
With 31 tools, this is well above the 25-tool threshold for a single server, making the surface feel heavy and difficult to navigate. Even given the broad domain (packages, providers, models, registries), many tools could be consolidated or grouped more tightly.
The server provides extensive read coverage for packages, providers, models, and registries, but there are notable gaps such as no watchlist removal or model comparison, and some tools appear redundant rather than completing a lifecycle. Overall, it is broadly useful but not fully complete for its stated purpose.