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Octonove

crbro-memory

by Octonove
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Local

Recall

crbro_recall
Read-onlyIdempotent

Search full-text memory of earlier sessions to find facts and decisions the user already shared, before asking again or saving new data. Returns best-matching neuron with confidence label.

Instructions

Read-only search of everything saved in earlier sessions — the full text of facts, decisions, patterns, preferences, errors, debts and maps, not just topic names; to read one neuron by id or name use crbro_inspect view=neuron. One result per neuron: its best matching chunk with matched_kind and matched_added, a confidence label (weak = little of the question covered; verify first), plus also_matched. Retired facts and entries never surface. Call it before asking the user what they may already have told you, and before crbro_learn. If nothing matches, retry with 2-4 phrasings in queries or fewer, distinctive words. has_map:true: read the system map with crbro_map before touching that system.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax neurons returned (default 10).
queryYesWhat to look for, e.g. "Firebase authentication setup". Fewer, distinctive terms beat full sentences.
domainNoOnly neurons in this domain (exact match, e.g. "proyectos-web").
queriesNoAlternative phrasings of the same question, searched together with query and fused by rank. Use synonyms, the other language and the concrete product name; 2-4 is plenty.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintYes
queryYes
resultsYes
total_resultsYes

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / queries
      Added value: +{
+  "description": "Alternative phrasings of the same question, searched together with query and fused by rank. Use synonyms, the other language and the concrete product name; 2-4 is plenty.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  2. Changed4 schema fields changedv1.14.0
    • changedInput schema / properties / domain / description
      Previous value: -"Filter by domain"New value: +"Only neurons in this domain (exact match, e.g. \"proyectos-web\")."
    • changedInput schema / properties / limit / description
      Previous value: -"Max results (default 10)"New value: +"Max neurons returned (default 10)."
    • changedInput schema / properties / query / description
      Previous value: -"What to search for (e.g., \"Firebase authentication setup\")"New value: +"What to look for, e.g. \"Firebase authentication setup\". Fewer, distinctive terms beat full sentences."
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "hint": {
+      "type": "string"
+    },
+    "query": {
+      "type": "string"
+    },
+    "results": {
+      "items": {
+        "additionalProperties": {},
+        "properties": {
+          "also_matched": {
+            "items": {
+              "additionalProperties": false,
+              "properties": {
+                "added": {
+                  "type": "string"
+                },
+                "kind": {
+                  "type": "string"
+                },
+                "text": {
+                  "type": "string"
+                }
+              },
+              "required": [
+                "text",
+                "kind",
+                "added"
+              ],
+              "type": "object"
+            },
+            "type": "array"
+          },
+          "confidence": {
+            "enum": [
+              "strong",
+              "weak"
+            ],
+            "type": "string"
+          },
+          "domain": {
+            "type": "string"
+          },
+          "has_map": {
+            "type": "boolean"
+          },
+          "heat": {
+            "type": "number"
+          },
+          "matched_added": {
+            "type": "string"
+          },
+          "matched_kind": {
+            "type": "string"
+          },
+          "matched_terms": {
+            "type": "number"
+          },
+          "matching_content": {
+            "type": "string"
+          },
+          "name": {
+            "type": "string"
+          },
+          "neuron_id": {
+            "type": "string"
+          },
+          "query_terms": {
+            "type": "number"
+          },
+          "relevance_score": {
+            "type": "number"
+          }
+        },
+        "required": [
+          "neuron_id",
+          "name",
+          "domain",
+          "relevance_score",
+          "matching_content",
+          "heat"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total_results": {
+      "type": "number"
+    }
+  },
+  "required": [
+    "query",
+    "total_results",
+    "results",
+    "hint"
+  ],
+  "type": "object"
+}
  3. First observedv1.4.0

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint, the description adds meaningful behavioral detail: one result per neuron, best matching chunk with matched_kind/matched_added, confidence label semantics, the 'retired facts never surface' rule, and what 'weak' confidence implies. These are not captured by annotations alone and significantly improve agent expectations.

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 dense but every sentence adds value: core scope, result format, confidence interpretation, exclusion behavior, usage timing, retry strategy, and conditional map guidance. It is front-loaded with the key purpose and then organizes supporting detail in a logical flow without redundancy.

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?

Given four parameters, an output schema, and a large sibling family, the description is complete: it explains the return format, confidence label, exclusion behavior, when to call versus crbro_inspect/crbro_map/crbro_learn, and how to handle no matches. Nothing an agent needs to invoke it correctly is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds valuable semantic guidance beyond the schema, such as 'fewer, distinctive terms beat full sentences' and using synonyms, the other language, or the concrete product name for queries. This meaningfully improves parameter usage.

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 a specific verb ('search') and resource ('everything saved in earlier sessions'), and explicitly contrasts with crbro_inspect view=neuron, distinguishing this tool's scope from the inspect sibling. The detail that it searches full text of facts/decisions/patterns rather than topic names adds precision.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance: call it before asking the user what they may already have told you, and before crbro_learn. It also provides actionable retry guidance for empty results and instructs to use crbro_map when has_map:true, making alternatives clear.

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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