Clarifyprompt-MCP

memory_search

Semantically search the memory store to retrieve facts, pack chunks, and past optimizations ranked by similarity. Debug curator decisions by seeing what ClarifyPrompt would retrieve for a given prompt.

Instructions

Semantic search over the persistent memory store. Returns facts, pack chunks, and past optimizations ranked by vector similarity to the query. Useful for inspecting what ClarifyPrompt would retrieve for a given prompt, and for debugging curator decisions.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "memory_search"
  }
}

Input Schema

Name	Required	Description
`query`	Yes	The search query — usually the user's intent or a paraphrase of a future prompt.
`kinds`	No	Which memory kinds to search. Default: facts + pack chunks.
`limit`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.6.8Jun 2, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations provided, so description carries the full burden. It discloses the search mechanism (vector similarity) and return types, but does not indicate whether the operation is read-only or any side effects, leaving ambiguity about safety.

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?

Two sentences, no fluff, front-loaded with the core purpose and followed by use case examples. Every sentence earns its place.

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, but description explains what is returned. Could be improved by mentioning result structure or pagination, but overall covers need-to-know aspects for a search tool.

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?

Two of three parameters have schema descriptions (67% coverage). Description does not add extra meaning beyond schema; it restates the purpose of the tool overall without detailing parameter usage. Baseline 3 is appropriate.

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?

The description states 'Semantic search over the persistent memory store' with specific resource ('memory store') and action ('search'), and lists what is returned. It distinguishes from siblings like memory_list_facts which are likely non-semantic.

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?

Explicitly says 'Useful for inspecting what ClarifyPrompt would retrieve for a given prompt, and for debugging curator decisions,' clarifying the context. No explicit exclusions or alternative comparisons, but context is clear.

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