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ellmos-ai

ellmos-homebase-mcp

Official

hb_mem_store

Store facts, lessons, or working memory entries with confidence and agent provenance in persistent local memory for LLM orchestration.

Instructions

Store a fact, lesson, or working memory entry

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe content to store
agent_idNoAgent identifier for shared-memory provenance
categoryYesMemory category
confidenceNoConfidence score (0-1)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0-alpha.29

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, yet it says nothing about persistence semantics, deduplication, whether entries are append-only or overwritable, or what provenance/agent_id actually does. 'Store' implies a mutation but no safety, auth, or reversibility context is given.

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 no filler or redundancy. It is efficient, though the terseness is partly what leaves the behavioral and usage gaps unfilled.

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 a write tool with four parameters, zero annotations, and no output schema, the description does not cover enough ground. It never addresses what happens on store, whether duplicates are handled, or what the caller gets back.

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 are already documented in the schema, establishing the baseline of 3. The description only re-lists the category values that the schema's enum already covers, adding no new meaning.

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 ('Store') and the resource is clearly scoped by the enumeration of what may be stored ('fact, lesson, or working memory entry'). The verb alone distinguishes it from read-oriented siblings like hb_mem_query and hb_mem_context, though it never names those siblings explicitly to confirm the boundary.

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 guidance on when to store versus query, merge, consolidate, or route memory, and no preconditions. An agent must infer the write-vs-read split purely from the verb.

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