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recall

Read-only

Retrieve relevant memories by combining vector, FTS5, and keyword search with optional filters for agent, channel, source, and project. Includes exhaustive deep recall and exclusion of known contents.

Instructions

Recall relevant memories using multi-strategy search (vector + FTS5 + keyword).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNoDeep recall — disable time and completion decay for exhaustive search
limitNoMax memories to return
queryYesSearch query (empty returns recent memories)
channelNoFilter memories by channel (e.g. 'chat', 'discord'). Default: '' (all channels).
agent_idYesAgent identifier
source_idNov2.4.20 per-user source filter. Empty (default) = no filter. Non-empty = prefix match against json_extract(source, '$.id'), e.g. 'discord:12345' to restrict to one Discord user, or 'discord:' to scope to all Discord-sourced memories. Episodes are skipped when set (no per-user source tagging).
project_idNov2.4.17 γ filter. Omit → no filter (all projects). '' → global pool only. 'X' → 'X' bucket ∪ global pool. Threaded through cascade / RRF / vector / FTS / keyword paths.
exclude_contentsNoNormalized content strings to exclude from results (starts-with match). Used to prevent duplication with conversation context already known to the caller.
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safe read nature is covered. The description adds behavioral context by mentioning the multi-strategy search (vector + FTS5 + keyword), which is beyond annotations. No contradictions.

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 a single, information-dense sentence with no fluff. It is front-loaded and efficiently conveys the core functionality.

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?

The tool has no output schema, and the description does not explain the return format or pagination. While parameters are well-documented, the missing return details make it less complete. Annotations cover read-only behavior, so overall adequate but with gaps.

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 the description adds little beyond what the schema provides. The description does not elaborate on parameter behavior; the schema already does that well. Baseline of 3 is appropriate.

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 tool recalls relevant memories using multi-strategy search (vector, FTS5, keyword), specifying the verb and resource. However, it does not explicitly differentiate from sibling tools like recall_with_context or list_memories, which could help the agent choose.

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 guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or context for preferring this over siblings like recall_with_context.

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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