label_question

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

With no annotations, the description carries full burden. It describes that the tool updates the question's DNA labeling, lists parameters with constraints, and specifies the return format including error handling. It does not explicitly mention side effects or permissions, but overall provides good behavioral detail.

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 lengthy but well-structured with clear sections: purpose, prerequisite, parameter list, and return values. It front-loads the main purpose and uses a bullet-like format for parameters. Some information could be consolidated, but it remains clear and scannable.

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 (17 parameters, 2 required) and no annotations, the description covers all necessary aspects: prerequisites, detailed parameter meanings, return values, and error handling. It is fully sufficient for an agent to select and invoke the tool correctly.

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 does so thoroughly, explaining each parameter's role, constraints (e.g., difficult rubric, controlled vocabularies for hard_points and scenario), and how to fill them. This adds significant value beyond 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's purpose: to write DNA labeling (difficulty, knowledge anchor, solution skeleton, variant base material) for an already ingested question. It uses specific verbs and resources, and distinguishes itself from siblings like ingest_question by explicitly requiring prior ingestion.

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 explicitly states the prerequisite (question must be ingested via ingest_question) and suggests that Claude should read the question and KG context before calling the tool. It does not explicitly name alternatives or when not to use, but the context provides sufficient guidance.

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