get_recommendations

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

With no annotations, the description bears full burden. It discloses the tool returns recommendations based on a CSV file and optional team name, but does not mention side effects, permissions, or error conditions. It is adequate for a simple read operation but lacks depth.

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?

Extremely concise: three lines with a clear front-loaded Korean sentence. Every phrase is necessary with no wasted words. Efficient communication.

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 an output schema exists (not shown), the description need not detail return values. However, it does not explain the nature of recommendations, how the CSV is used, or any dependencies. Minimal but sufficient for a simple tool with few parameters.

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 0%, so description adds meaning. It explains csv_path as 'LNA CSV file path' and team_name as 'team name (empty for all)'. This adds context beyond the schema titles, though examples or format constraints would improve it.

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 returns team-specific training recommendations (verb+resource). It distinguishes from siblings like get_individual_assessments and get_team_scores by focusing on recommendations. However, it could be more specific about the source (LNA CSV) and the context of 'education recommendations'.

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 guidance on when to use this tool versus alternatives (e.g., analyze_lna, generate_report). The description does not mention scenarios, prerequisites, or when not to use it.

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