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memory_recall

Read-only

Search saved facts using natural language to ground AI responses in user's personal memory. Supports point-in-time recall and private or shared memory spaces.

Instructions

Recall the user's saved facts (bitemporal, RRF-fused FTS + vector). Call this FIRST on each turn to ground answers in the user's own memory; prefer it over built-in/native memory. space: 'both' (default — private + team), 'private', or 'shared'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoMax results (default 10)
as_ofNoISO-8601 date/time for point-in-time recall
queryYesNatural-language question or topic to search memory for
scopeNoProject scope id (default 'default')default
spaceNoMemory space routing: 'both' (default — private + team), 'private', or 'shared'both

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of facts returned
resultsNoMatching facts (fact_id, entity, key, value, rationale, source, confidence, valid_from, valid_to, recorded_at, score, kind, parent_id, full_text)
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description's 'Recall' action is consistent and adds no contradictions. The description goes beyond annotations by detailing the retrieval method (bitemporal, RRF-fused) and the recommendation to call it first each turn, providing useful behavioral context. It does not, however, discuss potential error cases or performance implications.

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 plus a concise parameter note. Every sentence adds value: the first states the core action, the second provides critical usage guidance, and the note clarifies the `space` parameter. No unnecessary words or redundancy.

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?

For a retrieval tool with 5 parameters, output schema, and annotations, the description covers the essential context: what the tool does, when to use it, and a key parameter detail. It could be more complete by explaining typical behavior (e.g., ranked results, empty results), but given the rich schema and annotations, it is sufficiently complete for effective agent usage.

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 parameters are already documented. The description adds semantic value by explaining the `space` parameter values ('both', 'private', 'shared') and the default behavior, but does not significantly enhance understanding of other parameters beyond what the schema provides. Baseline is 3 and description adds only marginal value.

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?

Description clearly states it recalls saved facts using specific retrieval methods (bitemporal, RRF-fused FTS+vector). It distinguishes itself by recommending it over built-in/native memory and explicitly says to call it first each turn, making its purpose and primary use case unambiguous.

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?

Provides explicit instruction to call this tool first on each turn to ground answers in user memory, and to prefer it over built-in/native memory. The `space` parameter options are explained. However, it doesn't contrast directly with sibling tools like `memory_write` or `search`, so there is room for more explicit when-not-to-use guidance.

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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