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submit_chunk

Store content chunks with provenance tracking, recording the AI model, task type, and source URLs for each submission.

Instructions

Store content with provenance tracking.

Args: project: Project name (e.g. "theology") node_id: Node identifier (e.g. "cath-person-001") node_type: Node type (e.g. "Person", "Council", "Document") field: Field name (e.g. "biography", "description") content: The actual content produced_by: Model that produced it (e.g. "haiku-4.5", "sonnet-4.6", "opus-4.6") task_type: Type of task (e.g. "biography_synthesis") sources: URLs used as sources

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYes
node_idYes
node_typeYes
fieldYes
contentYes
produced_byYes
task_typeYes
sourcesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description adds context like 'provenance tracking' and parameter examples, but doesn't disclose side effects (e.g., idempotency, overwrite behavior) or required permissions.

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?

Purpose is front-loaded. The Args list is necessary due to no schema descriptions, making it longer but still structured. Could be slightly more concise by grouping examples.

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?

Covers core functionality and parameter meanings, but lacks info on return values (output schema exists but not described) and behavioral details like create-vs-update or error handling.

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

Parameters5/5

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

Schema description coverage is 0%, but the description lists all 8 parameters with context and examples (e.g., 'Project name (e.g. "theology")'), fully compensating for the missing schema docs.

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?

Clear verb 'Store' and resource 'content with provenance tracking'. Sibling tools like 'export_chunks' and 'get_review_queue' have different purposes, so this is easily distinguished.

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 like 'export_chunks' or 'mark_reviewed'. The description only states what it does, not when it's appropriate.

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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