generate-tokens-from-pattern

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 discloses key behavioral traits: automatic tokenization, intelligent name generation, optional prefix support, support for token options (skip, channel, fragment), and generation of ANTLR4 string literal patterns. It also lists return values (list of tokens, per-rule status, modified grammar, summary). It does not explicitly warn about potential file mutation via write_to_file, but that is disclosed in the schema. The description provides substantial behavioral detail beyond the schema.

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 structured with clear sections (When to use, Examples, Features, Returns) and uses bold headers. While it is relatively long (~200 words), every section contributes useful information. The examples are concrete and aid comprehension. It is not overly verbose, but could be slightly trimmed without losing value.

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?

The tool has 9 parameters and no output schema, so the description must cover return values and behavior. It does so by listing output categories and providing examples. It also covers most relevant scenarios (tokenization, prefixing, token options). It does not fully explain the interplay between from_file and write_to_file, but that is available in the parameter descriptions. Overall, it is quite complete for a complex tool.

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 baseline is 3. The description adds value beyond the schema through concrete examples illustrating how to use input_pattern, tokenize, and prefix. The features section also explains the tokenization behavior that parameters like tokenize control. This enhances understanding of parameter semantics without duplicating schema text.

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 opens with a clear verb+resource: 'Generate lexer tokens automatically from natural language input patterns.' The examples further clarify the exact functionality, and this is distinct from sibling tools like 'preview-tokens' (which likely previews tokens) or 'add-tokens-with-template' (which uses templates). The purpose is unambiguous and well-differentiated.

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 'When to use' section lists specific scenarios (quick token generation, converting configuration snippets, generating tokens from command examples, prototyping grammars). This provides clear context for when the tool is appropriate. It does not explicitly mention alternatives or exclusions relative to sibling tools, which would push it to a 5, but the guidance is sufficient for selecting it in common cases.

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