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Lyellr88

marm-mcp

marm_smart_recall

Search stored memories by semantic similarity or keyword match. Returns ranked results with relevance scores to find relevant context quickly.

Instructions

🧠 Recall memories by semantic similarity or keyword match.

Searches stored memories for the most relevant matches to query. Returns a ranked list of results with similarity scores.

Parameters:

  • query: natural language search term or phrase

  • session_name: limit search to a specific session (default searches active session)

  • limit: maximum number of results to return (default 5)

  • search_all: if True, search across all sessions instead of just the active one

  • include_logs: if True, include log entries alongside memory results

  • detail: controls how much content is returned per result 1 = summary only (~200 chars) 2 = extended context (~500 chars) 3 = full content

Returns: status, results list with id/content/score, results_count

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
session_nameNodefault
limitNo
search_allNo
include_logsNo
detailNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the return structure and that results are ranked by similarity. However, it does not explicitly state that the operation is read-only or disclose any potential side effects (e.g., no destructive actions are indicated). It could be more explicit about behavioral traits.

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?

The description is well-structured with a clear separation of purpose and parameter details. There is minor redundancy between the first two sentences, but overall it is concise and front-loaded with the main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, 1 required, output schema present), the description is comprehensive. It covers search behavior, parameter options, and return fields (status, results, results_count). No additional information is needed for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides detailed explanations for all 6 parameters, including defaults and behavior (e.g., detail levels). Since the input schema has 0% description coverage, the description fully compensates by adding meaningful semantics beyond type and default values.

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's purpose: recalling memories by semantic similarity or keyword match. It uses specific verbs ('Recall', 'Searches') and a resource ('memories'). It is easily distinguishable from sibling tools like marm_delete or marm_compact, which focus on different operations.

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 explains the tool retrieves relevant memories for a query, with clear parameter guidance (e.g., search_all, include_logs). It does not explicitly state when to avoid using this tool or provide alternatives, but the context makes it suitable for memory retrieval tasks.

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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