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run_batch_validation_tests

Validates multiple inputs against an llguidance grammar from a JSON test file, returning pass/fail statistics and details on failed tests.

Instructions

Run batch validation tests from a JSON file against an llguidance grammar. Test file should contain array of {input, should_parse, description?} objects. Returns high-level statistics (total, passed, failed, success_rate) and detailed information for failed tests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
grammarYesllguidance grammar string or path to grammar file (.lark, .grammar)
test_fileYesPath to JSON test file with format: [{"input": "test", "should_parse": true}] or {"tests": [...]}
Behavior3/5

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

Describes expected behavior (runs tests, returns statistics and fail details) but does not disclose potential side effects, error conditions, or performance implications. With no annotations, description carries full burden, yet remains basic.

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

Conciseness5/5

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

Two sentences, front-loaded with purpose, no extraneous information. Every sentence adds value.

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

Completeness4/5

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

Covers purpose, parameter basics, and return format. With no output schema, the description adequately explains what is returned. Lacks minor details like path resolution or error handling, but sufficient for a simple tool.

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?

Schema already covers both parameters with good descriptions. Description adds minimal new parameter information beyond restating test file format. Baseline 3 due to 100% schema coverage.

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

Purpose5/5

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

Clearly states the verb 'run', resource 'batch validation tests', and context 'from a JSON file against an llguidance grammar'. Distinguishes from siblings 'get_llguidance_documentation' and 'validate_grammar' by focusing on test execution.

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

Usage Guidelines4/5

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

Implies usage context (when you have a grammar and test file), but no explicit when-not or alternatives. Purpose is distinct enough from siblings that agent can infer correct use, lacking explicit guidance.

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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