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kaminocorp
by kaminocorp

query

Search an agent's memory, knowledge, and identity to find relevant information using natural language queries. Results are ranked by semantic similarity.

Instructions

Search an Anima's brain across memories, knowledge, and identity. Returns relevant results ranked by semantic similarity to your query. Use this for general questions about what the Anima knows or remembers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language query to search the Anima's brain
anima_idNoAnima ID (optional, uses default if not set)
sourcesNoWhich layers to search (default: all)
max_tokensNoToken budget for results (default: 2000)
limitNoMax number of results (default: 20)
exclude_idsNoIDs to exclude (for multi-turn dedup)
Behavior4/5

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

Discloses that it returns results ranked by semantic similarity. No annotations provided, so description carries burden; it adequately conveys read-only behavior through the term 'search' but lacks details on limitations or edge cases.

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?

Two sentences with no wasted words. Front-loaded with purpose and output behavior immediately.

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?

No output schema, but description mentions 'returns relevant results ranked by semantic similarity,' which gives a general idea. Could be more specific about return format, but sufficient for a search tool with many parameters.

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%, so each parameter is already described. The tool description does not add significant meaning beyond what the schema provides, meeting baseline expectations.

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?

Clearly states it searches across memories, knowledge, and identity, returning results ranked by semantic similarity. Distinguishes from siblings like search_knowledge and search_memories by being a general cross-layer query.

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

Usage Guidelines4/5

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

Explicitly says 'Use this for general questions about what the Anima knows or remembers,' providing clear context. Does not explicitly mention when not to use or alternatives, but sibling tools imply specialization.

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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