Skip to main content
Glama

search_memory

Search FSB's memory for relevant past experiences before automating a site, ranking results by keyword match and recency to reuse learned patterns.

Instructions

Search FSB's memory system for relevant past experiences. Returns memories ranked by relevance with keyword matching and recency scoring. Use to find what FSB learned from previous tasks on similar sites or domains. When to use: before automating a site to check if FSB has learned relevant patterns from past sessions. Related: get_memory_stats (check memory size), list_sessions (find specific sessions).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNNoMax results to return (default: 5)
typeNoFilter by memory type
queryYesNatural language search query
domainNoFilter by domain (e.g., "amazon.com")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the ranking mechanism (keyword matching plus recency scoring), but does not cover permissions, behavior on empty results, or result size limits — meaningful gaps for a tool with zero annotation coverage.

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?

Front-loaded with purpose, then return behavior, then usage, then related tools — a logical order with little waste. Slightly longer than strictly needed, but each sentence carries useful information.

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?

No output schema or annotations exist, so the description does the heavy lifting: it explains purpose, when-to-use, related tools, and the ranking logic. It is close to complete for a 4-param search tool, missing only edge-case behavior and result-format specifics.

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 all four parameters (query, topN, type, domain) are already documented in the schema. The description adds no syntax, format, or filtering detail beyond what the schema provides, so baseline 3 applies.

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?

States a specific verb and resource ('Search FSB's memory system') and specifies scope ('relevant past experiences', 'similar sites or domains'), with a return summary ('memories ranked by relevance with keyword matching and recency scoring'). It differentiates itself from siblings by naming get_memory_stats and list_sessions as related tools.

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?

Gives an explicit 'When to use' clause ('before automating a site to check if FSB has learned relevant patterns from past sessions') and points to related tools. It stops short of stating when NOT to use it or how it differs from a competing sibling, since the named related tools serve different purposes rather than being alternatives for the same task.

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