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

With no annotations provided, the description carries the burden. It discloses the tool's output areas (downloads, size, dependencies, quality scores) and implies a read-only comparison, but does not discuss potential limitations, rate limits, or error conditions. Sufficient for most purposes but not exhaustive.

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?

Two short sentences, front-loaded with the verb 'Compare,' and every word adds value. Excellent structure with no 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 tool with a single parameter and no output schema expected, the description sufficiently explains purpose, inputs, and the nature of the comparison, making it complete for an agent to decide invocation. No critical information 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?

The input schema fully describes the 'names' parameter with clear constraints (2-10 package names), and schema coverage is 100%. The description adds context about the comparison context, complementing the schema without redundancy, slightly enhancing the baseline.

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 uses a specific verb ('Compare') and resource ('npm packages'), clearly stating it shows downloads, size, dependencies, and quality scores, which differentiates it from sibling tools like search_packages and get_package.

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?

While the description implies use for evaluating alternatives ('to help choose between alternatives'), it does not explicitly state when to use this tool over search_packages or get_package, nor any exclusions. The usage context is only implied.

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?

No annotations are present, so the description carries the full burden. It is transparent about the kind of data returned (latest version, dependencies, download stats, size, repository links), implying a read-only operation. However, it does not disclose behavior on errors, network failures, or any rate limits—common gaps for a 'get' tool.

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?

A single sentence that is front-loaded with the verb and resource, followed by a concise list of details. Every word earns its place; 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 tool with one parameter and no output schema, the description covers the main output categories well. However, it does not provide any context about how this tool relates to search_packages or compare_packages, leaving a gap in tool selection guidance that would make it fully complete.

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 fully documents the single 'name' parameter with examples ('express', '@types/node', 'zod'). The description adds no new semantic detail beyond calling it a 'specific npm package', so baseline 3 is appropriate.

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 uses the verb 'Get' with a specific resource 'detailed information about a specific npm package' and enumerates content areas (version, dependencies, download stats, size, repository links). This clearly distinguishes it from sibling tools like search_packages and compare_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?

No explicit when-to-use guidance is provided. The description implies you already know the package name ('specific npm package') but does not state that search_packages should be used for discovery or compare_packages for comparisons. There are no exclusions or alternatives mentioned.

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?

With no annotations provided, the description carries the full burden. It discloses that this is a read-only search operation and enumerates the return fields, which is genuinely useful. However, it omits details like result ordering (by score? popularity?), pagination behavior beyond the limit param, or rate implications of querying the registry — modest but not rich behavioral disclosure.

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?

Two sentences, both earning their place: the first states action + return format, the second gives usage guidance. Front-loaded with the core purpose, zero filler or redundant restatement of the tool name.

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 read-only search with fully-documented params, this is nearly complete. The explicit enumeration of return fields (name, description, version, score, links) compensates for the missing output schema. The only gaps: no mention of result ordering, and the limit cap (50) is only in the schema — but the description is adequate for the tool's low complexity.

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 coverage is 100% — both query and limit are documented with descriptions and constraints in the schema itself. The description's mention of 'matching a query' adds nothing beyond the schema's 'Search query (e.g. 'markdown parser'...)'. Baseline 3 is correct since the schema does the lifting and the description doesn't need to compensate.

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 verb ('Search'), resource ('npm registry'), and return payload (name, description, version, score, links). It's unambiguous what search_packages does. However, it doesn't explicitly differentiate from siblings (get_package, compare_packages) — the distinction is only implied by the tool name 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?

'Use this to find packages for a specific task or compare options' gives explicit context for when to invoke this tool. It hints at the discovery-before-comparison workflow but doesn't state when NOT to use it (e.g., when you already know the exact package name and should use get_package instead).

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