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octave_validate

Validate OCTAVE content against a specified schema, identify constraint violations, and return canonical form with optional automatic repairs.

Instructions

Schema check + repair suggestions for OCTAVE content. Validates content against schema, returns canonical form with optional repairs. Focus on I3 (Mirror Constraint) and I5 (Schema Sovereignty).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fixNoIf True, apply repairs to canonical output. If False (default), suggest repairs only.
schemaYesSchema name to validate against (e.g., 'META', 'SESSION_LOG')
compactNoIf True, return warning/error counts instead of full lists. Saves tokens.
contentNoOCTAVE content to validate (mutually exclusive with file_path)
profileNoValidation strictness profile: STRICT (full compliance, reject unknown), STANDARD (default), LENIENT (warnings not errors, auto-repairs), ULTRA (minimal validation).
diff_onlyNoIf True, return diff instead of canonical content. Saves tokens when validating.
file_pathNoPath to OCTAVE file to validate (mutually exclusive with content)
grammar_hintNoIf True and validation returns INVALID, include compiled GBNF grammar in response to guide correction.
debug_grammarNoIf True, include compiled regex/grammar in output for debugging constraint evaluation.
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses validation and optional repairs, focus on specific constraints, but does not detail side effects, permissions, or whether modifications are persisted. Some behavioral context is present via parameters like fix and profile.

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?

Three sentences concisely convey purpose, behavior, and focus areas without unnecessary detail. 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?

Given 9 parameters and no output schema, the description effectively summarizes tool behavior (validation, repair, canonical form) and key features (diff, grammar hints). It covers the main use cases but could elaborate on return value structure and error handling.

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

Parameters4/5

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 by linking parameters to purpose (e.g., 'fix' for repairs, 'profile' for strictness) and highlighting focus on I3/I5 constraints, providing meaningful context beyond schema definitions.

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?

The description clearly states the tool performs schema checking and repair suggestions for OCTAVE content, specifies it validates against schema and returns canonical form, and identifies focus on I3 and I5 constraints. This distinguishes it from siblings like compile_grammar and eject.

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?

No guidance on when to use this tool vs alternatives. The description does not mention prerequisites, scenarios, or when not to use it. Siblings are not referenced for differentiation.

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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