normalize_tokens

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

With no annotations, the description should fully disclose behavior, but it only states the core action. It does not mention side effects, read-only nature, error handling, or what happens to unknown tokens. The transformation process is opaque.

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 (one sentence), but under-specification outweighs brevity. While it is well-structured, it sacrifices essential detail for shortness.

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 lack of annotations, output schema, and parameter descriptions, the description is far from complete. It does not cover the mode parameter, token expectations, or return value format, making it insufficient for reliable 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 description coverage is 0%, and the tool description does not explain the parameters. 'mode' (full vs compact) and 'tokens' (expected format) are left undefined, leaving the agent without necessary context to construct valid inputs.

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: normalizing glyphs and domain terms into canonical IDs. It uses a specific verb and resource, and it distinguishes from siblings like lookup_glyph and lookup_term which are lookups rather than normalization.

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?

No guidance is provided on when to use this tool versus alternatives (e.g., lookup_glyph). There is no mention of prerequisites or context that would help an agent decide between normalization and other operations.

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