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capture_idea

Store and organize an idea with automatic tag extraction and cross-pollination connections to related content from your research library.

Instructions

Store an idea in the SQLite ideas table.

Auto-extracts tags from content. Links to domains/projects if keywords match.
Unless `auto_cross_pollinate=False`, automatically surfaces up to 5 cross-
pollination matches from library / meetings / news / older ideas in the same
response — so the user sees connections without a second tool call.

Args:
    content: The idea text.
    source: Where the idea came from (default "manual").
    image_path: Optional path to an associated image.
    auto_cross_pollinate: When True (default), include connection matches in the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
sourceNomanual
image_pathNo
auto_cross_pollinateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Given no annotations, the description effectively discloses key behaviors: auto-extraction of tags, linking to domains/projects, and optional cross-pollination matching in responses. It does not mention destructive actions, authorization needs, or rate limits, but covers the main transparent traits.

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?

The description is well-structured with a clear main purpose, bullet points for key behaviors, and an 'Args' section. It is slightly verbose in repeating parameter defaults that could be inferred, but overall efficient and front-loaded.

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?

The description covers the tool's primary action, side effects, and optional behavior. Given the presence of an output schema, return values need not be explained. It lacks mention of error handling or usage sequences, but is fairly complete for its complexity.

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?

With 0% schema description coverage, the description compensates fully by explaining each parameter's purpose and default behavior in the 'Args' section. This adds significant meaning beyond the schema's basic titles and types.

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

Purpose4/5

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

The description clearly states the verb 'store an idea' and the resource 'SQLite ideas table', with added features like tag extraction and cross-pollination. However, it does not differentiate from sibling tools such as 'capture_observation' or 'ingest_ideas_document', which have similar purposes.

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 provides no explicit guidance on when to use this tool versus alternatives. It mentions the auto_cross_pollinate parameter but does not specify conditions for setting it to False or compare with other tools.

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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