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NEXO Brain

by wazionapps
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Python
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nexo_learning_update

Modify a learning record by specifying the ID and any fields to update. Only the provided fields are changed, leaving others intact.

Instructions

Update a learning entry. Only non-empty fields are changed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesLearning ID number.
titleNoNew title (optional).
statusNoNew status such as active/superseded (optional).
contentNoNew content (optional).
categoryNoNew category (optional).
priorityNocritical, high, medium, low (optional).
reasoningNoNew reasoning/context (optional).
applies_toNoNew applies_to target(s) (optional).
preventionNoNew prevention rule (optional).
review_daysNoNew review interval in days (optional).
supersedes_idNoExisting learning ID this updated canonical rule replaces (optional).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv7.37.4
  2. Removedv7.23.8
  3. Addedv7.20.23
  4. Removedv7.20.14
  5. Addedv7.17.4
  6. Removedv7.17.1
  7. Changed12 schema fields changedv7.13.7
    • addedInput schema / properties / applies_to
      Added value: +{
+  "default": "",
+  "description": "New applies_to target(s) (optional).",
+  "type": "string"
+}
    • addedInput schema / properties / category / description
      Added value: +"New category (optional)."
    • addedInput schema / properties / content / description
      Added value: +"New content (optional)."
    • addedInput schema / properties / id / description
      Added value: +"Learning ID number."
    • addedInput schema / properties / prevention
      Added value: +{
+  "default": "",
+  "description": "New prevention rule (optional).",
+  "type": "string"
+}
    • addedInput schema / properties / priority
      Added value: +{
+  "default": "",
+  "description": "critical, high, medium, low (optional).",
+  "type": "string"
+}
    • addedInput schema / properties / reasoning
      Added value: +{
+  "default": "",
+  "description": "New reasoning/context (optional).",
+  "type": "string"
+}
    • addedInput schema / properties / review_days
      Added value: +{
+  "default": 0,
+  "description": "New review interval in days (optional).",
+  "type": "integer"
+}
    • addedInput schema / properties / status
      Added value: +{
+  "default": "",
+  "description": "New status such as active/superseded (optional).",
+  "type": "string"
+}
    • addedInput schema / properties / supersedes_id
      Added value: +{
+  "default": 0,
+  "description": "Existing learning ID this updated canonical rule replaces (optional).",
+  "type": "integer"
+}
    • addedInput schema / properties / title / description
      Added value: +"New title (optional)."
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "type": "object",
-  "x-fastmcp-wrap-result": true
-}New value: +null
  8. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the key trait 'Only non-empty fields are changed' (partial update semantics), but omits important details such as error behavior on invalid id, return value, side effects, and permission requirements.

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 a single, front-loaded sentence that efficiently conveys the core purpose and a critical behavioral rule. No wasted words.

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

Completeness2/5

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

For a tool with 11 parameters, no output schema, and no annotations, the description is too minimal. It lacks usage context, result format, error handling, and any guidance on how the 'only non-empty fields' behavior interacts with defaults. The agent would need additional information to use it confidently.

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?

The input schema has 100% description coverage for all 11 parameters, so the baseline is 3. The description does not add any further meaning to the parameters beyond what the schema already provides.

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?

The description 'Update a learning entry' provides a clear verb-resource pair, and the added detail 'Only non-empty fields are changed' distinguishes it from a full replacement update. However, it does not contrast it explicitly with sibling tools like nexo_learning_add or nexo_learning_delete, leaving some ambiguity.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus alternatives (e.g., nexo_learning_add for creation, nexo_learning_delete for removal). The agent is not told prerequisites, when not to use it, or how it fits in a workflow.

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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