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source.ingest

Ingest documents (md, txt, csv, pdf) into the raw sources layer to enable subsequent entity extraction, cross-referencing, and knowledge base index updates.

Instructions

Ingest one or more documents (md, txt, csv, pdf) into the raw sources layer. After ingesting, follow the workflow in .kiro/steering/kb-ingest.md to extract entities into the KB, create cross-references, and update the index and changelog.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesYes
project_idNo
project_rootNo
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal that ingestion is only the first step and that additional processing is required (KB extraction, cross-referencing, index/changelog updates), which is useful. However, it omits side effects such as overwrite behavior, permission requirements, reversibility, and document size limits, leaving gaps in transparency.

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 two sentences: the first states the core purpose concisely, and the second provides a direct reference to the follow-up workflow. It is front-loaded with the action verb and contains no redundant information.

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

Completeness2/5

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

Given no annotations and no output schema, the description should provide complete context. While it names the raw sources layer and the post-ingestion workflow, it fails to explain essential parameter semantics, project context (project_id/project_root), and any behavioral constraints. The workflow reference is helpful but cannot compensate for the missing operational details.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It mentions accepted document types (md, txt, csv, pdf), which loosely implies the 'files' parameter, but it does not explain any of the parameters (files, project_id, project_root) or how to provide content vs. file_path. This is insufficient for an agent to correctly map inputs.

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 uses a specific verb ('Ingest') and clearly identifies the resource ('documents ... into the raw sources layer'). It distinguishes itself from sibling tools like source.get/source.search, which are retrieval operations, and from kb.add, which targets the KB layer.

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

Usage Guidelines3/5

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

The description implies usage for adding raw documents and includes a post-ingestion workflow pointer, but it does not explicitly state when to use this tool versus alternatives (e.g., source.get for reading) or provide exclusions. The workflow reference gives some contextual guidance but not direct selection criteria.

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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