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 states the tool returns 'Cache statistics and information', which implies a read-only operation, but doesn't clarify aspects like whether it requires authentication, has rate limits, or what specific statistics are included. This leaves gaps in understanding the tool's behavior beyond its basic function.

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 concise and well-structured, with two sentences that efficiently convey the tool's purpose and return value. It avoids unnecessary details, making it easy to parse. However, it could be slightly more front-loaded by integrating the return information into the first sentence for better clarity.

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 (0 parameters, no annotations, but has an output schema), the description is adequate but incomplete. It explains what the tool does and what it returns, but lacks context on usage guidelines and behavioral traits. The presence of an output schema reduces the need to detail return values, but more guidance on when to use this tool would enhance completeness.

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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter details, and it appropriately doesn't mention any. This meets the baseline for tools with no parameters, as there's nothing to compensate for.

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 with a specific verb ('Get') and resource ('statistics about the documentation cache'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'refresh_cache' or 'scan_dependencies', which also relate to the cache but perform different operations.

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 no guidance on when to use this tool versus alternatives. It doesn't mention scenarios for usage, prerequisites, or comparisons to sibling tools such as 'refresh_cache' (which might update the cache) or 'get_package_docs' (which might retrieve cached documentation). This lack of context leaves the agent without clear direction.

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 of behavioral disclosure. It adds value by mentioning 'version-based caching', which hints at performance optimization and data freshness considerations. However, it lacks details on error handling, rate limits, authentication needs, or what 'formatted documentation' entails structurally. For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.

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 well-structured and front-loaded: the first sentence states the core purpose, followed by a clear 'Args' and 'Returns' section. Every sentence earns its place by providing essential information without redundancy. It's appropriately sized for a tool with three parameters and an output schema.

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 moderate complexity (3 parameters, no annotations, but with an output schema), the description is reasonably complete. The output schema handles return value details, so the description doesn't need to explain 'formatted documentation' further. It covers the tool's purpose and parameter semantics adequately, though usage guidelines and deeper behavioral context are lacking.

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 description coverage is 0%, so the description must compensate. It provides semantic context for all three parameters: 'package_name' is for fetching documentation, 'version_constraint' ties to dependency scanning, and 'query' filters documentation sections. This adds meaningful interpretation beyond the bare schema, though it doesn't specify format details (e.g., what a valid 'version_constraint' looks like).

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: 'Retrieve formatted documentation for a package with version-based caching.' It specifies the verb ('retrieve'), resource ('documentation'), and a key behavioral trait ('version-based caching'). However, it doesn't explicitly differentiate from sibling tools like 'scan_dependencies' or 'get_cache_stats', which could help an agent understand when to choose this tool over others.

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 no guidance on when to use this tool versus alternatives. It mentions 'version-based caching' but doesn't explain how this relates to sibling tools like 'refresh_cache' or 'get_cache_stats'. There's no mention of prerequisites, typical use cases, or exclusions, leaving the agent with minimal context for tool selection.

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 of behavioral disclosure. It states the tool refreshes a cache and returns statistics, but lacks details on side effects (e.g., whether it blocks other operations, requires permissions, or has rate limits). This is a significant gap for a mutation tool with zero annotation coverage.

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 and front-loaded, with two sentences that directly state the action and return value without any waste. Every sentence earns its place by providing essential information efficiently.

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 complexity (a mutation operation with no annotations) and the presence of an output schema (which covers return values), the description is minimally adequate. It explains the core action but lacks behavioral context like side effects or prerequisites, making it incomplete for safe agent use.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter semantics, and it appropriately avoids redundant information, earning a high baseline score.

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 with a specific verb ('Refresh') and resource ('local documentation cache'), making it immediately understandable. However, it doesn't explicitly differentiate this from sibling tools like 'get_cache_stats' or 'scan_dependencies' beyond the refresh action, which prevents a perfect score.

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 no guidance on when to use this tool versus alternatives like 'get_cache_stats' or 'scan_dependencies'. It mentions a return value but doesn't specify contexts such as after dependency changes or before documentation lookups, leaving usage unclear.

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 of behavioral disclosure. It mentions scanning dependencies and returning JSON, but fails to detail critical aspects like error handling (e.g., if pyproject.toml is missing), performance implications, or any side effects. This leaves significant gaps for an agent to understand the tool's behavior.

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 appropriately sized and front-loaded, with the core purpose stated first followed by structured sections for args and returns. There's minimal waste, though the 'Args:' and 'Returns:' labels could be slightly more integrated into the flow.

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 moderate complexity (scanning dependencies), no annotations, and an output schema present (which handles return values), the description is partially complete. It covers the basic operation and parameters but lacks details on errors, dependencies on external files, or integration with sibling tools, leaving room for improvement.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'project_path' defaults to the current directory and specifies the file type ('pyproject.toml'), which clarifies beyond the schema's generic 'Project Path' title. However, it doesn't cover parameter constraints or format details, keeping the score at 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 clearly states the action ('Scan project dependencies') and the resource ('from pyproject.toml'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_package_docs' or 'refresh_cache', which prevents a perfect score.

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 guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, such as whether the project must have a pyproject.toml file, or comparisons to siblings like 'get_package_docs' for documentation retrieval.

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