recommend_from_library

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

The description adds useful behavioral details by stating 'Returns ranked matches with tag overlap scores' and providing an example of tag derivation. However, with no annotations available, it does not disclose other behavioral aspects such as authentication, rate limits, or error handling, leaving some transparency 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 concise, front-loaded with the primary purpose, and contains no unnecessary words. The four sentences each add value: purpose, use case, LLM guidance with example, and output behavior.

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?

The description provides essential information: purpose, usage guidance, a derivation example, and output format. However, it lacks explanation for three of the four input parameters and does not detail how the ranking score is computed, making it incomplete for a tool with no annotations or output schema.

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%, and the description only implicitly references the 'tags' parameter via 'specified tags/mood'. It does not explain the meaning of 'limit', 'steam_id', or 'unplayed_only', leaving these parameters underspecified.

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 function: 'Find games in the user's library that match specified tags/mood.' This is a specific verb+resource statement that distinguishes it from siblings like get_library, which simply lists, and search_games, which searches external content.

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 clear context by stating 'Ideal for backlog recommendations' and gives concrete guidance for the LLM on how to derive tags from user mood. It does not explicitly outline when not to use the tool or name alternatives, but the use case is well implied.

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