get_activity

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that 'minimal=true' reduces context usage by stripping social metrics and metadata, which adds some behavioral context. However, it doesn't cover other critical aspects like rate limits, authentication needs, error handling, or what 'detailed information' includes (e.g., data format, pagination). For a read operation with no annotation coverage, this is insufficient.

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 highly concise and front-loaded: it states the core purpose in the first sentence and adds a practical tip in the second. Every sentence earns its place by providing essential information without redundancy, making it efficient and easy to parse.

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 output schema, no annotations), the description is partially complete. It covers the basic purpose and a key parameter tip, but lacks details on behavioral traits (e.g., auth, errors) and output format, which are important for a read tool. It's adequate as a minimum viable description but has clear gaps in 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?

Schema description coverage is 100%, so the schema already documents all parameters (id, include_all_efforts, minimal) with clear descriptions. The description adds minimal value by briefly mentioning 'minimal=true to reduce context usage,' which reinforces but doesn't significantly expand beyond the schema. This meets the baseline score when schema coverage is high.

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: 'Get detailed information about a specific activity by ID.' It specifies the verb ('Get'), resource ('activity'), and key constraint ('by ID'), making it easy to understand. However, it doesn't explicitly differentiate from siblings like 'get_activities' (which likely lists multiple activities) or 'get_activity_streams' (which might return different data types), so it doesn't reach the highest 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 some implied usage guidance by mentioning 'minimal=true to reduce context usage,' suggesting this parameter is useful for efficiency. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'get_activities' for lists or 'get_activity_streams' for specific data types) or any prerequisites, such as needing a valid activity ID. This leaves gaps in decision-making context.

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