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memory

Manage individual memories: get, list, search, update importance, archive, hydrate, feedback, chain head, history.

Instructions

Manage individual memories — get, list, search, update importance, archive, hydrate, relevance feedback, fetch a chain-shaped namespace's head, or query revision history.

ACTIONS:

  • "get": Retrieve a single memory by rid.

  • "list": Browse memories with filters.

  • "search": Keyword substring search.

  • "update_importance": Change a memory's importance score.

  • "archive": Move to cold storage.

  • "hydrate": Restore archived memory.

  • "feedback": v0.10 — relevance feedback on a recalled memory (needs rid + feedback="relevant"|"irrelevant"). Call after USING a recalled memory; it tunes future retrieval. (Moved here from recall, which is now read-only.)

  • "chain_head": The CURRENT value of a chain-shaped namespace (narrative / decision / config chains). Use this — not recall — for "what is the current/latest X": similarity search favors the most-similar revision, chain_head returns the newest.

  • "history": v0.8.0 — revision history for a single rid (needs rid).

Args: See action docs above. New args: namespace: Required for chain_head — the chain-shaped namespace. rid: Required for history/feedback — the record acted on. feedback: For feedback — "relevant" or "irrelevant". feedback_query: For feedback — the query that surfaced the memory. feedback_score / feedback_rank: For feedback — retrieval context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ridNo
limitNo
actionYes
domainNo
offsetNo
sort_byNocreated_at
feedbackNo
namespaceNo
importanceNo
memory_typeNo
feedback_rankNo
text_containsNo
feedback_queryNo
feedback_scoreNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Adds behavioral context beyond annotations, such as that feedback tunes future retrieval, chain_head returns the newest revision, and feedback was moved from recall. Annotations (readOnlyHint false) are consistent with mutation actions described.

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?

Structured with a main sentence and bullet list of actions; front-loaded with purpose. Some redundancy (e.g., repeating 'action' in each bullet) and length, but organized.

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 the tool's complexity (14 parameters, many actions) and that output schema exists, the description covers actions well but lacks full parameter documentation. Missing descriptions for common parameters like limit, offset, memory_type, etc. reduces completeness.

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?

With 0% schema description coverage, the description partially compensates by documenting key parameters for specific actions (namespace for chain_head, rid for history/feedback, feedback-related fields) but omits descriptions for many other parameters (limit, offset, sort_by, domain, etc.).

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 explicitly states the tool manages individual memories and lists multiple specific actions (get, list, search, etc.), clearly distinguishing it from sibling tools like recall (e.g., notes feedback moved from recall, and chain_head vs recall).

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 usage guidance for key actions: feedback should be called after using a recalled memory; chain_head should be used instead of recall for current/latest values. Lacks comprehensive when-not-to-use notes for other actions.

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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