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claude-session-continuity-mcp

memory_search

Search stored memories by keywords or semantic similarity to retrieve relevant context from previous Claude sessions. Filter results by type, project, tags, or importance to find specific information.

Instructions

Search stored memories using FTS5 full-text search or semantic/embedding similarity. Default mode returns compact index entries (id, type, truncated content) to save tokens — set detail=true for full content. Supports filtering by type, project, tags, and minimum importance. Read-only. Use memory_get to fetch full content for specific IDs found in search results. Use memory_related to explore graph connections from a known memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query
typeNoFilter by memory type (default: "all")
projectNoFilter by project (optional)
tagsNoFilter by tags — matches if any tag is present (optional)
semanticNoUse embedding-based semantic search instead of keyword FTS5 (default: false)
minImportanceNoMinimum importance threshold 1-10 (default: 1)
limitNoMax results to return (default: 10)
detailNoReturn full content per memory (default: false — returns compact index only)
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's read-only, returns compact index entries by default to save tokens, supports two search modes (FTS5 and semantic), and allows filtering. However, it doesn't mention rate limits, authentication needs, or error conditions, which keeps it from a perfect score.

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 efficiently structured in three sentences that each serve distinct purposes: stating the core functionality, explaining the default behavior and key parameter, and providing usage guidelines with sibling tools. There's no wasted language, and the most important information (what the tool does) is front-loaded.

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 search tool with 8 parameters, 100% schema coverage, and no output schema, the description provides good contextual completeness. It explains the tool's purpose, different search modes, default behavior, and relationships to sibling tools. The main gap is the lack of output format details (beyond mentioning compact vs full content), which would be helpful given no output schema exists.

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 8 parameters thoroughly. The description adds some context about the default mode (compact index entries) and the detail parameter's purpose, but doesn't provide significant additional semantic meaning beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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 with specific verbs ('search stored memories') and methods ('using FTS5 full-text search or semantic/embedding similarity'), and distinguishes it from siblings by mentioning memory_get and memory_related as alternatives for different operations. It explicitly identifies what resource it operates on (memories).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool vs alternatives: 'Use memory_get to fetch full content for specific IDs found in search results' and 'Use memory_related to explore graph connections from a known memory.' It also specifies the default behavior (compact index entries) and when to override it (set detail=true).

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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