Read a whole dependency list at once and report what is archived, what carries advisories, what has a source-available licence, and what has not been pushed to in a year. Use when reviewing a package.json, requirements.txt, Cargo.toml, composer.json or Gemfile.
| Name | Required | Description | Default |
|---|---|---|---|
| names | Yes | ||
| registry | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states the tool 'reads' and describes the types of findings it reports (archived, advisories, source-available license, no push in a year), which is useful. However, it does not disclose network behavior, authentication requirements, error handling, or performance implications, leaving notable 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 two straightforward sentences. The first sentence front-loads the core functionality and outputs, the second provides usage context. No fluff, no redundant information, and 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 that there is no output schema, the description adequately conveys the return categories (archived, advisories, source-available licence, no push in a year). It also specifies the input formats (manifests). However, it omits details on parameter semantics and error behavior, so it is not fully complete for a tool that would benefit from such 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 has zero descriptions for the two required parameters ('names' and 'registry'). The description implies that 'names' is the list of package names from a dependency file and that the tool checks them against a registry, but it never explains the 'registry' parameter's possible values or format. This is insufficient for a 0% schema coverage case.
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: to read a whole dependency list and report on archived packages, advisories, source-available licenses, and stale packages. It uses a specific verb ('Read') plus a well-defined resource ('dependency list') and distinguishes itself from siblings like check_package by focusing on bulk analysis rather than individual packages.
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 explicit usage context: 'Use when reviewing a package.json, requirements.txt, Cargo.toml, composer.json or Gemfile.' This tells the agent when to invoke the tool, but it does not explicitly state when not to use it or mention alternative tools, so it falls short of a 5 but exceeds a 3.
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.