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madgodinc

mgi-mind

Official

mind_search

Search long-term AI memories semantically and filter by author, source, date range, or libraries to retrieve relevant facts and summaries.

Instructions

Semantic search across memories, with optional metadata filters (author, source, date window, multiple libraries).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNoRetrieval tier: 1=facts, 2=summaries, 3=full
limitNoMax results
queryYesSearch query
authorNoFilter to memories written by this agent
rerankNoOverride the reranker for THIS query: true forces it on, false gives the raw hybrid (dense+sparse) order. Omit to use the configured default.
sourceNoFilter by ingest source tag (e.g. a session id or URL)
libraryNoFilter to one library
librariesNoFilter to ANY of these libraries (OR). Use instead of 'library' for cross-library search.
rerank_top_kNoOverride how many candidates the reranker re-orders for this query.
created_sinceNoOnly memories created at/after this instant, INCLUSIVE (RFC3339 timestamp or YYYY-MM-DD date)
created_beforeNoOnly memories created before this instant, EXCLUSIVE (RFC3339 timestamp or YYYY-MM-DD date)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 behavioral burden, and it discloses almost nothing beyond the search mode. It says nothing about result ordering (the reranker behavior that is central to this tool), pagination, result format, or cost/latency characteristics of a semantic search over a tiered store.

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?

A single front-loaded sentence with zero filler, naming the core operation first and the optional modifiers second. It is efficient, though arguably too terse given the tool's 11 parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter retrieval tool with no annotations and no output schema, one sentence is not enough. Nothing explains how tier, rerank, rerank_top_k, or the library vs libraries distinction should be chosen, and with dozens of sibling tools the agent has no routing context.

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 11 parameters in detail. The description only restates the filter categories (author, source, date window, multiple libraries) and adds no syntax, defaults, or interaction rules 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Semantic search across memories") plus the filter categories it supports, so the agent knows the retrieval mode. However, it never distinguishes itself from close siblings like mind_recall, mind_recall_all, mind_fact_query, or mind_should_search, so the agent must infer which one applies.

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?

There is no when-to-use guidance and no alternatives named. With ~40 sibling memory tools including several other recall/search entry points, the description gives the agent no basis for choosing mind_search over mind_recall or mind_should_search.

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