get_post_reactions

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 the tool 'Returns cleaned data in TOON format,' which adds some context about output behavior. However, it doesn't disclose critical traits like whether this is a read-only operation, potential rate limits, authentication needs, or what 'cleaned data' entails (e.g., data transformation or filtering). For a tool with no annotations, this leaves significant gaps in understanding its 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 extremely concise with just one sentence, front-loaded with the core purpose and no wasted words. Every part earns its place by stating the action, resource, and output format efficiently, making it easy to parse quickly.

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 (4 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and output format but lacks details on usage guidelines, behavioral traits, and parameter interactions. Without an output schema, it doesn't explain return values beyond 'cleaned data in TOON format,' leaving ambiguity. This makes it functional but incomplete for effective 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 input schema has 100% description coverage, so all parameters are documented in the schema. The description adds no additional meaning beyond the schema, such as explaining the 'TOON format' for the 'save_dir' parameter or detailing how 'max_items' interacts with pagination. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 ('Get') and resource ('reactions on a LinkedIn post'), specifying what the tool does. It distinguishes itself from siblings like 'get_post' (which likely gets post content) and 'get_post_comments' (which gets comments rather than reactions). However, it doesn't explicitly differentiate from 'get_profile_reactions', which might be similar but for profiles instead of posts.

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. For example, it doesn't mention when to choose this over 'get_post' (which might include reactions) or 'get_profile_reactions' (for reactions on profiles rather than posts). The description lacks context about prerequisites or exclusions, such as needing a valid LinkedIn URL or authentication requirements.

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