Neotic

cognitive.identify_task

Create or resolve an abstract task structure without storing raw private content (§24).

Args:
    task_structure: Structural representation (entities, constraints, variables, etc.).
    environment: Environmental context and characteristics.
    goal: Objective and optimization goals.

Returns:
    task_structure_id, structural_features, and matching existing structures.
    On invalid input returns {"error", "detail", "hint"} instead of raising,
    so the MCP client sees the cause instead of a generic execution error.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`goal`	No
`environment`	No
`task_structure`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedSep 20, 2026
- removedInput schema / properties / task_structure / additionalProperties
```
Removed value: -true
```
- addedInput schema / properties / task_structure / anyOf
```
Added value: +[
+  {
+    "additionalProperties": true,
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]
```
- addedInput schema / properties / task_structure / default
```
Added value: +null
```
- removedInput schema / properties / task_structure / type
```
Removed value: -"object"
```
- removedInput schema / required
```
Removed value: -[
-  "task_structure"
-]
```
First observedSep 19, 2026

TDQS

B3.4/5.0

Behavior5/5

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

No annotations are present, so the description carries the full burden. It explicitly discloses that raw private content is not stored, that invalid inputs return a structured {error, detail, hint} instead of raising, and that the tool may return matching existing structures rather than always creating new ones. These are meaningful behavioral details beyond a simple one-liner.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with a clear purpose sentence and then organized into Args/Returns sections without filler. It is appropriately sized, though the cryptic '§24' cross-reference is unexplained and could confuse an agent without policy context.

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

Completeness3/5

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

The return values and error behavior are covered, and an output schema exists, which helps. However, usage guidance versus sibling tools is absent and parameter semantics are thin. For an abstract tool with three optional open-object parameters, this is adequate but has clear gaps.

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 the description must compensate. It gives only brief glosses: task_structure includes examples, but environment and goal are largely restatements ('Environmental context', 'Objective and optimization goals'). It does not explain the open-object format, how they interact, or that all parameters are optional/nullable.

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 states a specific verb+resource: 'Create or resolve an abstract task structure.' It also adds a distinguishing scope note ('without storing raw private content') and names the return values. However, it does not explicitly differentiate the tool from siblings like cognitive.parse_task or cognitive.execute_task.

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?

No explicit when-to-use guidance or alternative tool references are provided. With a large sibling list containing similar task-related tools, an agent must infer when identify_task is the right choice. The privacy clause hints at one context but no exclusions or comparisons are given.

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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