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billy12151

memory-arbiter-mcp

by billy12151

memory

Remember, find, read, update, and judge entries to store and retrieve structured memory across AI coding tools, with built-in conflict arbitration. Use help to learn accepted fields.

Instructions

Daily memory operations: remember, find, read, update, judge, status, help.

Call memory(action="help") to discover accepted fields, judge requirements, value enums, update modes, and action_required paths before relying on a result that requests attention.

find is an index page: results carry metadata + content_chars + a bounded outline (offsets usable directly as read span starts), not full content — pass include_content=true for full text. Score compares only within the page; if the top page misses, reword the query or add tags_filter instead of deep paging. The size block meters the returned page (tokens_estimate + display_hint).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
actionNohelp

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the burden, and it adds real behavioral detail for find: index-page semantics, include_content=true for full text, page-scoped scoring, and a size block. However, it does not disclose side effects, permissions, or outcome implications for remember, update, judge, or status, so behavioral coverage is incomplete across the tool's surface.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the action list and uses three compact paragraphs, each with a distinct job: overview, help-first advice, and find semantics. There is no filler or repetition; every sentence adds information.

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?

The description fully details only the find action and points to help for the rest; remember, read, update, judge, and status semantics are left undisclosed. Sibling tool boundaries are not addressed, so an agent still needs extra discovery before confidently using all operations.

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 coverage is 0%, so the description must compensate. It lists the accepted action values, mentions action='help', and names concrete data fields such as include_content and tags_filter. The full data object shape is left to the help action, but this partial enumeration is meaningful.

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 opens with 'Daily memory operations' and enumerates the supported verbs (remember, find, read, update, judge, status, help), making the dispatch role clear. It does not fully explain what each operation does, and 'memory operations' is somewhat generic, but it is enough to distinguish this tool from the memory_review/govern/repair siblings.

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?

It gives explicit guidance to call action='help' before relying on results, and advises rewording the query or adding tags_filter instead of deep paging. It does not name sibling tools or state when memory_review/govern/repair should be chosen instead, so exclusions/alternatives are missing.

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

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