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memory_search_tool

Find stored engineering knowledge by combining full-text search with tag and type filters, retrieving relevant decisions, invariants, and gotchas from persistent project memory.

Instructions

Hybrid tag + full-text search.

Args: query: Search query (full-text via Turso FTS5) types: Filter by memory types tags: Filter by tags include_stale: Whether to include potentially stale items limit: Maximum results (default 20) project: Optional project root path. Auto-detected from git root if omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
limitNo
queryYes
typesNo
projectNo
include_staleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden and does reasonably well: it discloses FTS5-based full-text search, filtering by types/tags, the include_stale option, and project auto-detection from git root. It does not explain ranking behavior or what 'stale' means precisely, but the main behavioral traits are present.

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 compact and front-loaded with a clear one-line summary followed by a parameter list. Each line has a purpose, with no fluff, though the word 'full-text' appears twice and the 'Args:' label is slightly mechanical.

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?

Given the output schema exists and the tool has moderate complexity, the description covers all invocation-relevant aspects: query, filters, limits, stale handling, and project scoping. It could be more complete about accepted type/tag values and hybrid ranking semantics, but it is sufficient for basic correct usage.

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

Parameters4/5

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, and it does: all six parameters get one-line explanations. The query parameter gains FTS5 context and project gains auto-detection detail, though 'types' and 'tags' remain somewhat generic without enumerating valid values.

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?

The description states a specific action ('search') with a resource ('memory') and a distinguishing mechanism: 'Hybrid tag + full-text search'. It is clear enough to differentiate from memory_get, memory_list, and memory_recent, though it does not explicitly mention those siblings.

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

Usage Guidelines3/5

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

Usage is implied by the word 'search' and the filter parameters, but there is no explicit guidance on when to prefer this tool over memory_list_tool or memory_recent_tool. No exclusions or alternative tool names are provided.

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