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Glama

anamnesis_search

Find specific stored memories by keyword, tag, or project filter. Use it when you know exact terms to retrieve past decisions, patterns, or solutions.

Instructions

Keyword and tag search across memories. Faster than recall when you know specific terms to search for. Supports filtering by tags and project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
limitNo
queryNo
projectNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions filtering capabilities, which is useful, but doesn't describe whether this is a read-only operation, how results are ordered, pagination behavior, or any rate limits. For a search tool, basic behavioral traits are missing.

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?

Three succinct sentences with no filler. The purpose is front-loaded, the efficiency comparison follows, and filtering details close. Efficient and well-structured.

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?

An output schema exists, so returning values needn't be described. However, with 4 parameters at 0% schema coverage, the description only partially documents the interface. For a search tool with no annotations, more behavioral context (e.g., result ordering, empty query handling) would improve completeness.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'filtering by tags and project' but doesn't explain the 'limit' parameter, the 'query' behavior (e.g., whether empty query returns all), or how tags are combined (AND/OR). Only 2 of 4 parameters get any semantic detail.

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?

States a specific verb+resource ('Keyword and tag search across memories') and distinguishes from the sibling recall tool by noting it's 'Faster than recall when you know specific terms to search for.' This gives a clear functional boundary, though it could be more explicit about the exact difference from 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 a clear when-to-use condition ('when you know specific terms to search for') that contrasts with recall. It doesn't state when not to use it, but the comparative framing gives good context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.