turingmind_classify_failure

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

With no annotations, the description carries the burden. It declares the tool is 'deterministic' and lists the outputs per classification. It does not cover error cases or idempotency, but the core behavior is transparent.

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 extremely concise, front-loading the core purpose and using a clear bullet-like format. Every sentence adds value without redundancy.

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 tool's complexity (4 params, enum, no output schema), the description covers the classifications and their actions well. It assumes domain knowledge of SpecNode but otherwise is sufficiently complete for correct tool invocation.

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 50% (descriptions for evidence and failure_trace). The description adds meaning for 'classification' by explaining the enum values, but node_id and evidence lack additional context beyond what is in the schema.

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 classifies a SpecNode failure deterministically, listing the four exact classifications and their meanings. This distinguishes it from sibling tools like 'detect_conflicts' or 'analyze_diff'.

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 explicit when-not instructions ('Do NOT guess') and defines each classification's action (escalate to Architect/Tester/Builder Mode, block node). However, it does not compare directly to other sibling tools for alternative use cases.

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