Advisories broken down by severity rather than counted, with identifiers and dates. Requires a key; see https://sighttrue.com/pricing.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Package name as the registry spells it. | |
| registry | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral disclosure. It discloses the need for a key (authentication requirement) and gives a sense of the output (identifiers and dates grouped by severity). However, it does not explicitly state whether this is a read-only operation, nor does it mention any rate limits, error conditions, or response shape. For a simple query tool, this is adequate but not thorough.
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 extremely concise: two sentences. The first states the core purpose, the second addresses the key requirement. No unnecessary words, and the information is front-loaded. Every sentence earns its place.
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 low complexity (2 params, no output schema, no annotations), the description provides a reasonable overview: it clarifies what the tool returns (advisories with identifiers/dates by severity) and the prerequisite (key). However, without an output schema or mention of the response structure, and with an undescribed 'registry' parameter, an agent may need additional inference to fully understand the expected input and 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?
The description does not mention any parameters, adding no meaning beyond the input schema. The schema describes 'name' but not 'registry', leaving 50% coverage. The description fails to compensate for the missing registry description or provide any parameter-specific context, making parameter understanding incomplete.
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 states that it provides advisories broken down by severity with identifiers and dates, which implies a listing/retrieval tool. However, it lacks a clear verb (e.g., 'list', 'get') and does not explicitly mention that it operates on a specific package/registry, leaving the scope to be inferred from the parameters. It does distinguish itself from a counting tool by saying 'rather than counted', but does not name the alternative.
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 only usage guideline is the requirement for a key, with a link to pricing. There is no explicit statement about when to use this tool versus sibling tools, nor any exclusions or prerequisites beyond the key. The 'rather than counted' hint suggests a contrast with a count-focused tool, but no alternative is named, so guidance is minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct query type: package status, stack review, provider incidents, model pricing, watchlist changes, etc. Even similar-sounding tools like check_package and check_stack are clearly differentiated by granularity (single package vs. whole manifest). The descriptions further remove ambiguity.
All names use lowercase snake_case, but the pattern is mixed: some are imperative verb_noun (check_package, find_model, watch_add) while many are noun phrases (advisory_severity, provider_incidents, runtime_deadlines). This is readable but not a consistent verb_noun style, so there is noticeable inconsistency.
At 31 tools, the count exceeds the 'too many' threshold (25+). While the domain is broad, the agent must navigate a large surface with many similarly scoped utilities, making selection harder. A more consolidated set (e.g., grouping related readings) would improve appropriateness.
The tool surface covers a wide range of supply-chain intelligence: package advisories, provider status, model pricing, runtime EOL, and watchlist changes. The only notable gap is lifecycle management for the private watchlist (e.g., no watch_remove or watch_list), but the overall coverage is strong.