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keymem

by donggyun112
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TypeScript
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read_key

List memory handles stored under a key, ranked by relevance to your query. Retrieve metadata and validity scores to choose which memory to read next.

Instructions

List the memories stored under one key (concept), ranked. Returns the canonical key, its aliases, and hub metadata plus ranked memory IDs, metadata, and validity — never memory content. Always pass the original focused query and active namespace when known: handles are then ranked by content relevance, which is essential for hubs. Each memory's score is content_relevance × link_weight × depth_factor × freshness_factor when query is passed (link_weight × depth_factor × freshness_factor otherwise); content_relevance is a cosine, comparable to recall's key relevance — both only meaningful within this one key's ranking. Call read_memory(memory_id, via_key_id=key_id, namespace) on the selected handle to inspect the fact and reinforce the path; reading does not confirm that its content is current. Use limit/offset to page without flooding context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
key_idYes
offsetNo
namespaceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.29.0
  2. Removedv0.17.1
  3. First observedv0.14.8

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden. It discloses the return payload (canonical key, aliases, hub metadata, ranked IDs, metadata, validity), explicitly states it never returns memory content, explains the scoring formula and its semantics, and warns that reading does not confirm current content. This is unusually thorough.

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 dense but well-organized: it opens with purpose and return summary, then usage guidance, then scoring formula, then a pointer to the next step, then pagination. Every sentence adds value, though the scoring formula section could be trimmed without losing critical meaning. The structure front-loads the key facts.

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

Completeness5/5

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

For a tool with no output schema and five parameters, the description covers the return shape, ranking logic, caveats about content freshness, and pagination. It also provides cross-tool guidance (read_memory) that completes the workflow. No critical operational detail appears missing.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must explain all parameters. It covers key_id implicitly (the key), query and namespace (with their effect on ranking), and limit/offset for pagination. It also clarifies how query changes the scoring, which is essential for correct invocation.

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 clearly states the verb ('List'), the resource ('memories stored under one key'), and the ranking behavior. It distinguishes itself from siblings by explicitly noting it never returns memory content and pointing to read_memory for that purpose, and it contrasts with recall's key relevance.

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?

The description advises always passing the original focused query and active namespace, explains why (essential for hubs), and explicitly directs the agent to call read_memory on a selected handle. It implies when to use this tool (to list and rank) versus read_memory (to inspect content) but does not explicitly enumerate exclusions or alternative conditions beyond that.

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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