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oneKn8
by oneKn8

recall

Retrieve semantically similar memories from persistent storage using natural language queries. Filter by project, tags, or minimum relevance score to find the most relevant past information.

Instructions

Search memories by semantic similarity.

Returns the most relevant stored memories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFilter results to memories with these tags.
queryYesNatural language search query.
projectNoLimit search to a specific project (None = search all).
n_resultsNoMaximum results to return (default: 10).
min_relevanceNoMinimum relevance score 0.0-1.0 to include.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are present, so the description must fully disclose behavioral traits. It only states that it returns memories, without mentioning side effects, authorization needs, or whether it's read-only. This is minimal disclosure.

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 consists of two concise, front-loaded sentences: the action and the result. Every word adds value, with zero waste.

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?

Given 5 parameters (1 required) and full schema coverage plus an output schema, the description is adequate but minimal. It does not explain the semantic similarity mechanism or provide context beyond the basic purpose, leaving some gaps for a complex search tool.

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 description coverage is 100%, so the schema already documents all five parameters. The description adds no additional meaning beyond the schema, resulting in the baseline score of 3.

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 tool searches memories by semantic similarity and returns relevant results, using specific verbs 'search' and 'returns'. It distinguishes from siblings (forget, list_memories, remember) as a retrieval operation.

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?

The description implies use for semantic search, and sibling tool names clarify alternatives (e.g., 'list_memories' for listing, 'remember' for storing). However, no explicit when-not-to-use or criteria for choosing between tools is provided.

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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