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davidgut1982

lore-mcp

by davidgut1982
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

log_retrieval_feedback

Annotate prior search results with feedback score, notes, or requery flag to improve retrieval quality.

Instructions

Score or annotate a prior kb_search result by its query_id (retrieval telemetry, issue #5). Supply user_feedback_score, required_requery, notes, or any combination; an omitted field is left unchanged (cannot be reset to null). No effect unless LORE_HARD_NEGATIVE_MINING=true on a PostgreSQL backend.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_idYes
user_feedback_scoreNo
notesNo
required_requeryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed17 schema fields changedv0.8.5
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / notes / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / notes / default
      Added value: +null
    • removedInput schema / properties / notes / description
      Removed value: -"Free-text note about the retrieval (truncated at 4000 chars). Optional; omit to leave unchanged."
    • removedInput schema / properties / notes / type
      Removed value: -"string"
    • removedInput schema / properties / query_id / description
      Removed value: -"query_id returned by a prior kb_search call."
    • addedInput schema / properties / required_requery / anyOf
      Added value: +[
+  {
+    "type": "boolean"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / required_requery / default
      Added value: +null
    • removedInput schema / properties / required_requery / description
      Removed value: -"True if the user had to refine/repeat their query because the results were insufficient. Optional; omit to leave unchanged."
    • removedInput schema / properties / required_requery / type
      Removed value: -"boolean"
    • addedInput schema / properties / user_feedback_score / anyOf
      Added value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / user_feedback_score / default
      Added value: +null
    • removedInput schema / properties / user_feedback_score / description
      Removed value: -"Integer relevance/quality score for the retrieval (1-5). Optional; omit to leave unchanged."
    • removedInput schema / properties / user_feedback_score / maximum
      Removed value: -5
    • removedInput schema / properties / user_feedback_score / minimum
      Removed value: -1
    • removedInput schema / properties / user_feedback_score / type
      Removed value: -"integer"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "type": "object",
+  "x-fastmcp-wrap-result": true
+}
  2. Changed4 schema fields changedv0.8.2
    • addedInput schema / properties / required_requery
      Added value: +{
+  "description": "True if the user had to refine/repeat their query because the results were insufficient. Optional; omit to leave unchanged.",
+  "type": "boolean"
+}
    • changedInput schema / properties / user_feedback_score / description
      Previous value: -"Integer relevance/quality score for the retrieval. Optional; omit to leave unchanged."New value: +"Integer relevance/quality score for the retrieval (1-5). Optional; omit to leave unchanged."
    • addedInput schema / properties / user_feedback_score / maximum
      Added value: +5
    • addedInput schema / properties / user_feedback_score / minimum
      Added value: +1
  3. First observedv0.7.0

TDQS

A3.6/5.0
Behavior3/5

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

Discloses that omitted fields cannot be reset to null and the environment dependency. However, no annotations exist, so the description must fully cover behavioral traits. It lacks details on side effects, idempotency, and return value (though output schema may cover return).

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 purpose. Every sentence adds value: purpose, field behavior, environment requirement. No wasted words.

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?

Given an output schema exists (presumably documenting return values), the description covers purpose, field semantics, update behavior, and environment requirement. Missing broader context like typical usage workflow or interpretation of scores, but mostly complete for a feedback logging tool.

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

Parameters2/5

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

Schema description coverage is 0%, so description must add meaning. It lists the three optional fields but does not explain valid values, ranges, or formats for user_feedback_score or required_requery. The query_id format is not specified. Only minimal semantic help.

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?

Clearly states the tool scores/annotates a prior kb_search result by query_id. Mentions retrieval telemetry context, distinguishing it from sibling tools like get_retrieval_telemetry which only retrieve data. Slight jargon ('issue #5') reduces clarity slightly.

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?

Explains what can be supplied (feedback score, requery, notes) and that omitted fields are left unchanged. Also warns that the tool has no effect unless LORE_HARD_NEGATIVE_MINING=true on PostgreSQL backend. Does not explicitly state when not to use it or mention alternatives.

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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