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10CG

nexusm-mcp-server

by 10CG

nexus.memory_feedback

Submit feedback on retrieved memories to improve future retrieval quality. Rate relevance 1-5 and mark each memory as useful or not.

Instructions

Submit per-memory feedback on a previous nexus.context_retrieve call. Pass retrieve_id from earlier output. Rating 1-5, plus per-memory useful flag with optional reason. v5 feedback loop drives quality_score reranking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYesMCP server **internal** audit/logging field, **not forwarded** to backend FeedbackRequest body. Backend derives user_id from retrieve_log (route is PUT /v1/feedback/{retrieve_id}). This field is only used for MCP server-side structlog + metric label.
retrieve_idYesFrom earlier nexus.context_retrieve output. MCP server uses this value as PUT URL path parameter.
ratingYes
item_feedbackNoPer-memory useful flag with optional reason. Maps to backend FeedbackRequest.item_feedback[].
expected_missingNoFree-text on what relevant memories were missing from retrieval. (PII-filtered before storage by backend)
contextNoFree-form context for feedback (e.g., {client: 'claude-code', session_id: '...'}).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
feedback_idYes
retrieve_idYes
statusYesSubmission status (currently always 'accepted', enum reserved for future expansion)
created_atYes
Behavior3/5

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

With no annotations, description carries burden. It discloses that user_id is internal and not forwarded, and that feedback drives quality_score reranking. Missing side effects, idempotency, or rate limits.

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, front-loaded with action, no fluff. Efficiently conveys core purpose and usage.

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?

Covers key aspects: purpose, input requirements, per-memory feedback, and feedback loop impact. Lacks explanation of output schema, but that is acceptable since an output schema exists.

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 coverage is high (83%); description adds marginal value by explaining user_id's internal nature and item_feedback's structure, but largely repeats schema descriptions.

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?

Description clearly states this tool submits per-memory feedback on a previous nexus.context_retrieve call, specifying key parameters (retrieve_id, rating, useful flag). It distinguishes from siblings (retrieve, create, search) by focusing on feedback.

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 instructs to pass retrieve_id from earlier output, implying usage after retrieval. Does not list exclusions or alternatives, but context is clear given sibling tools.

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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