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delimit_data_validate

Validate data files for JSON parsing, CSV structure, and SQLite integrity to ensure data quality and reliability.

Instructions

Validate data files: JSON parse, CSV structure, SQLite integrity check.

Args: target: Directory or file path containing data files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNo.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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 mentions validation actions but doesn't disclose behavioral traits such as whether it's read-only or destructive, permission requirements, rate limits, or output format. The description is minimal and lacks critical operational context for a validation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, with the core purpose stated first and parameter details following. Both sentences earn their place by defining the tool's function and its single parameter. There's no unnecessary fluff, though it could be slightly more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (validation across multiple file types), no annotations, and an output schema present, the description is incomplete. It lacks details on validation criteria, error handling, or output structure. The output schema might cover return values, but the description doesn't provide enough context for effective use without relying heavily on structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description includes an 'Args' section that explains the 'target' parameter as 'Directory or file path containing data files,' adding meaning beyond the schema's basic type and default. However, with 0% schema description coverage and only one parameter, this provides some value but doesn't fully compensate for the lack of schema details (e.g., path format constraints).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Validate data files: JSON parse, CSV structure, SQLite integrity check.' It specifies the verb (validate) and resources (data files) with concrete validation types. However, it doesn't explicitly differentiate from sibling tools like 'delimit_docs_validate' or 'delimit_design_validate_responsive', which might also involve validation but for different domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., during data migration or backup), or exclusions. Given the many sibling tools, this lack of differentiation leaves the agent guessing about appropriate use cases.

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

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