How many accounts hold publish rights on a package, as the registry lists them. Answers who can put code on your machine, which is a different question from who writes it. Requires a key; see https://sighttrue.com/pricing.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Package name as the registry spells it. | |
| registry | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool reflects registry-listed rights, implying a read-only operation, and notes the authentication key requirement. However, it does not specify output format (count vs. list), potential errors, or rate limits, leaving some behavioral gaps.
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, front-loading the core function in the first sentence. The second sentence adds valuable context, and the third provides an actionable requirement. Every sentence earns its place, with no redundancy or fluff.
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 simple two-parameter tool with no output schema, the description is reasonably complete. It conveys the tool's purpose, scope, and a key dependency. The main gap is the ambiguous output type (count vs. list) and lack of detail on how the registry parameter is used, but the description is adequate for basic invocation.
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 has 50% coverage: the 'name' parameter has a description, but 'registry' does not. The tool description adds minimal parameter meaning, only implicitly referring to a 'package' and 'registry' without clarifying the 'registry' parameter's valid values or format. It does not sufficiently compensate for the missing 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 tool's function: it counts accounts with publish rights on a package. It further distinguishes from related concepts by noting it answers 'who can put code on your machine' rather than 'who writes it,' which differentiates it from author-related queries. This makes the purpose specific and distinct from sibling tools.
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 clear context for when to use the tool: to determine publish rights as opposed to authorship. It also mentions the prerequisite of requiring a key, which is a usage condition. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.
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.