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zzhang82

Agent Memory Bridge

by zzhang82
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

feedback

Log retrieval result quality for a recalled memory, marking it helpful, misleading, or outdated to refine future recall.

Instructions

Record structured retrieval feedback for one recalled memory result.

Evidence is append-only/shadow-only. Provenance is caller-declared and not authenticated. This tool does not mutate memory records, recall results, or ranking behavior.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoOptional compact reason. Required for `misleading` and `outdated` outcomes.
outcomeNoDeclared retrieval outcome. Required for votes and corrections; optional for retractions.
memory_idYesExact recalled memory id being evaluated.
namespaceYesNamespace used by the recall receipt, such as `project:<workspace>` or `global`.
provenanceNoOptional declared provenance fields such as source_app, source_client, source_model, client_session_id, client_workspace, client_transport, or actor.
result_rankYesOne-based rank of the memory in the recalled result list.
feedback_typeNoAppend-only feedback event type. Defaults to a root vote.vote
recall_receiptYesSigned recall receipt token returned by a durable memory text `recall` response.
supersedes_feedback_idNoCurrent feedback head id. Required for corrections and retractions; omitted for root votes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Changed8 schema fields changedv0.26.1
    • addedInput schema / properties / feedback_type
      Added value: +{
+  "default": "vote",
+  "description": "Append-only feedback event type. Defaults to a root vote.",
+  "enum": [
+    "vote",
+    "correction",
+    "retraction"
+  ],
+  "title": "Feedback Type",
+  "type": "string"
+}
    • addedInput schema / properties / outcome / anyOf
      Added value: +[
+  {
+    "enum": [
+      "helpful",
+      "misleading",
+      "outdated",
+      "not_applicable",
+      "not_used"
+    ],
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / outcome / default
      Added value: +null
    • changedInput schema / properties / outcome / description
      Previous value: -"Declared retrieval outcome for the recalled memory."New value: +"Declared retrieval outcome. Required for votes and corrections; optional for retractions."
    • removedInput schema / properties / outcome / enum
      Removed value: -[
-  "helpful",
-  "misleading",
-  "outdated",
-  "not_applicable",
-  "not_used"
-]
    • removedInput schema / properties / outcome / type
      Removed value: -"string"
    • addedInput schema / properties / supersedes_feedback_id
      Added value: +{
+  "anyOf": [
+    {
+      "exclusiveMinimum": 0,
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Current feedback head id. Required for corrections and retractions; omitted for root votes.",
+  "title": "Supersedes Feedback Id"
+}
    • changedInput schema / required
      Previous value: -[
-  "namespace",
-  "recall_receipt",
-  "memory_id",
-  "result_rank",
-  "outcome"
-]New value: +[
+  "namespace",
+  "recall_receipt",
+  "memory_id",
+  "result_rank"
+]
  2. Addedv0.25.1

TDQS

A4.2/5.0
Behavior5/5

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

The description explicitly discloses key behavioral traits: 'Evidence is append-only/shadow-only. Provenance is caller-declared and not authenticated. This tool does not mutate memory records, recall results, or ranking behavior.' This is comprehensive given no annotations.

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 three concise sentences, front-loaded with the purpose. Every sentence adds value without repetition or fluff.

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 the tool has 9 parameters, an output schema, and no annotations, the description covers key behavioral aspects (append-only, provenance trust). It lacks details on error handling or response format, but output schema likely covers return values. Minor gaps noted.

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 100% and each parameter has a description. The description adds no per-parameter details, but provides overarching behavioral context. Baseline of 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 clearly states the tool's verb and resource: 'Record structured retrieval feedback for one recalled memory result.' This distinguishes it from siblings like recall (which retrieves) and store (which stores memories).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage after a recall, but does not explicitly state when to use or when to avoid. There is no mention of alternatives or conditions, leaving room for ambiguity.

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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