ast-editor

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains what the tool does (appends to arrays in various formats) and provides examples, but it lacks details on potential side effects (e.g., file modification behavior, error handling, or permissions required). The description adds value by clarifying format-specific targeting but doesn't fully cover behavioral traits like mutation implications or response format.

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 well-structured and front-loaded, starting with a clear purpose statement. Each sentence adds value: format support, targeting rules, usage guidelines, and examples. There is no redundant or wasted text, and the information is organized efficiently for quick comprehension by an AI agent.

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 (mutation tool with 3 parameters, 0% schema coverage, no annotations, but with an output schema), the description is mostly complete. It covers purpose, usage, parameter semantics with examples, and distinguishes from siblings. The output schema likely handles return values, so the description doesn't need to explain those. However, it lacks details on behavioral aspects like error conditions or file system effects, which could be important for a mutation 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 0%, so the description must compensate for undocumented parameters. It adds significant meaning beyond the schema by explaining the semantics of 'target' (dotted path for JSON/YAML/TOML, variable name for Python) and 'value' (literal value to append), with examples for TOML and Python. However, it doesn't explicitly cover 'file_path', leaving one parameter partially unexplained, though context implies it's the file to modify.

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: 'Append a literal value to an array/list.' It specifies the exact action (append), the target (array/list), and distinguishes it from sibling tools by explicitly contrasting with 'add_key' for key-value pairs. The description also enumerates supported formats (JSON, YAML, TOML, Python), making the scope specific and well-defined.

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 guidance on when to use and when not to use this tool: 'Use this when: You want to add an item to a list (dependencies, keywords, include paths, fixtures, etc.). Don't use this when: You're adding a key-value pair -> use `add_key`.' It names a specific alternative tool (`add_key`) and gives context for appropriate use cases, which is comprehensive for guiding an AI agent.

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