deep-thinker

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 actions like scoring and generating critiques but lacks details on permissions, side effects (e.g., whether evaluation modifies the graph), rate limits, or output format. For a tool with 4 parameters and no annotation coverage, this is a significant gap in transparency.

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 front-loaded with the core purpose in the first sentence and uses efficient language without redundancy. However, the second sentence ('Provides detailed analysis...') could be integrated more tightly, and it slightly repeats 'evaluate' from the first sentence, preventing a perfect score.

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 complexity (evaluating thinking processes with 4 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'graph health' entails, how scores are calculated, or what the output looks like (e.g., structured report vs. simple score). This leaves critical gaps for an agent to use the tool effectively.

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 4 parameters with clear descriptions. The description adds no additional meaning about parameters beyond implying evaluation of 'thinking process' and 'graph health', which aligns with the schema but doesn't enhance understanding of parameter usage or interactions.

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 with specific verbs ('score confidence', 'generate critiques', 'assess overall graph health') and identifies the resource ('thinking process'). It distinguishes from potential siblings like 'graph' (which might visualize) or 'think' (which might generate thoughts) by focusing on evaluation. However, it doesn't explicitly contrast with 'metacog' or 'prune', which could have overlapping evaluation aspects.

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 like 'metacog' (which might involve meta-cognition) or 'prune' (which might remove weak nodes). It implies usage for analyzing thinking processes but doesn't specify contexts, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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