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CarryMem

CarryMem

by lulin70
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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recall_from_knowledge

Full-text search across your knowledge base. Returns notes with title, content preview, tags, and wiki-links.

Instructions

Search knowledge base (e.g., Obsidian vault) using full-text search. Returns matching notes with title, content preview, tags, and wiki-links. Requires knowledge adapter.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "recall_from_knowledge"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of results (default 20)
queryYesSearch query for full-text search
filtersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It explains the return structure (title, preview, tags, links) but does not disclose side effects, authorization needs, rate limits, or error behavior. It adds some behavioral context but not comprehensively.

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, efficient and front-loaded. First sentence states the core action, second states output. No redundant words.

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?

The description covers the tool's purpose and return structure despite lacking an output schema. Missing details on filter logic and adapter requirements, but for a search tool with few parameters the description is mostly complete.

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 67%, so the baseline is 3. The description adds context that the search is full-text and returns specific fields, but it does not elaborate on parameter behavior (e.g., how filters combine, default vs. explicit limit). It provides moderate added 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?

The description clearly states the tool searches a knowledge base using full-text search and lists what it returns (title, content preview, tags, wiki-links). It distinguishes from sibling tools like 'recall_memories' or 'recall_all' by specifying the 'knowledge base' and 'full-text search' verbs.

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 mentions a prerequisite ('Requires knowledge adapter') but provides no guidance on when to use this tool versus alternatives like 'recall_memories' or 'recall_all'. There is no explicit 'when to use' or 'when not to use' 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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