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delimit_intel_snapshot_ingest

Stores research snapshots with optional provenance metadata for traceable knowledge management.

Instructions

Store a research snapshot with provenance metadata in the local intel store.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesSnapshot data (any JSON-serializable dict).
provenanceNoOptional provenance metadata (source, author, etc.).

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 must fully convey behavioral traits. It states 'Store' (mutation/persist) but does not disclose whether it overwrites existing data, any required permissions, side effects, or error handling. The description lacks detail on what 'local intel store' entails or if the operation is reversible.

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?

The description is a single concise sentence. It contains no extraneous information and is front-loaded with the key action and purpose. Every word is justified.

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?

The tool has a simple interface (2 parameters, output schema available) but the description omits what the tool returns (despite output schema existing) and provides no context on prerequisites or side effects. It is minimally adequate for a straightforward operation but leaves gaps in understanding the full context.

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 coverage is 100% with descriptions for both parameters. The description adds minimal semantics beyond the schema: it mentions 'provenance metadata' but the schema already describes provenance similarly. With high schema coverage, the baseline is 3, and the description does not significantly enhance parameter understanding.

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 action ('Store') and the resource ('a research snapshot with provenance metadata in the local intel store'). It distinguishes this tool from sibling intel tools like `delimit_intel_query` (querying) and `delimit_intel_dataset_register` (registering datasets), focusing on storing a snapshot with provenance.

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 does not provide explicit guidance on when to use this tool versus alternatives among siblings. There is no mention of when to use `delimit_intel_dataset_register` or other intel tools, nor any exclusion criteria or prerequisites. Usage is only implied through the description.

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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