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

No annotations are provided, so the description carries the full burden. It does disclose important behavior: it extracts structural invariants and registers an initial candidate strategy immediately. Still, it does not explain what 'registers' entails (persistence, overwrites, reversibility) or potential failure modes.

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 and front-loaded with the core purpose, followed by a single sentence of useful elaboration. It avoids filler and does not repeat schema fields, though the phrase 'few-shot learning' is somewhat redundant with the tool name.

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 0% schema coverage, no annotations, nested objects, and 4 parameters including 2 required ones, an agent would need more detail to invoke the tool correctly. The output schema helps with return semantics, but the description does not specify what solution_trace must contain, what task_structure_id refers to, or the role of strategy_name.

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, but it never names task_structure_id, solution_trace, source_model, or strategy_name. The phrase '1-3 problem traces' hints at solution_trace but does not clarify its structure or how multiple traces are represented within that single object.

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 states a specific verb ('induce') and resource ('generalized procedural StrategyIR') with a clear source scope ('from 1-3 problem traces'). It also names the extracted artifacts, which distinguishes this few-shot learning tool from sibling strategy tools like propose_strategy and compose_strategies.

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 implies usage context: few-shot learning with 1-3 traces and no large training sets. However, it does not explicitly say when to prefer this over sibling tools such as cognitive.propose_strategy, cognitive.learn_from_mistake, or cognitive.compose_strategies, nor does it provide exclusion criteria.

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