Agent Farm

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

With no annotations provided, the description carries the full burden. It mentions that analysis is done 'in parallel' and 'results are synthesized', which adds some behavioral context. However, it lacks details on permissions, rate limits, error handling, or what the synthesis entails, leaving significant gaps for a tool that performs analysis.

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: the first sentence states the core purpose, followed by brief elaboration and a clear example. Every sentence adds value without redundancy, making it efficient and well-structured.

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 no annotations, no output schema, and 3 parameters with 0% schema coverage, the description is moderately complete. It covers the tool's purpose and parameters adequately but lacks details on behavioral traits, output format, and usage context. It's minimal viable but has clear gaps in transparency and guidelines.

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 explains each parameter: 'target' as 'What to analyze (file path, concept, code, etc.)', 'question' as 'The analysis question', and 'num_perspectives' as 'How many different angles (default 4)'. This adds meaningful semantics beyond the bare schema, though it could be more detailed (e.g., constraints on 'num_perspectives').

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: 'Analyze something from multiple perspectives in parallel' with 'results are synthesized'. It specifies the action (analyze) and resource (something), but doesn't explicitly differentiate from sibling tools like 'deep_analysis_swarm' or 'recon_swarm' that might also perform analysis, keeping it at 4 rather than 5.

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 'multiple perspectives in parallel' but doesn't specify contexts, exclusions, or compare to sibling tools like 'deep_analysis_swarm' or 'api_swarm'. The example shows usage but doesn't explain when this approach is preferred.

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