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"
-]
```
AddedSep 19, 2026

TDQS

A3.5/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses the privacy/retention constraint ('without storing raw private content'), indicates that it may return matching existing structures, and explicitly describes the invalid-input error contract instead of an exception.

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 compact, front-loaded with the core purpose, and uses clear Args/Returns sections. Every sentence contributes information, with no filler.

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 description covers return shape and error handling, and an output schema exists, but it lacks usage context and enough detail about how the three optional objects should be assembled. An agent could invoke the tool, but may not know when to invoke it or what minimal input is required.

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 schema gives only generic nullable object types with no descriptions (0% coverage), so the description's one-line glosses provide the sole semantic meaning for each parameter. However, the glosses are high-level and do not explain the expected shape or composition of the objects, leaving important gaps.

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 opening sentence specifies a concrete action ('Create or resolve an abstract task structure') and a resource, and adds a meaningful constraint about not storing raw private content. It does not explicitly contrast with siblings like parse_task or resolve_intent, so it misses full differentiation.

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 gives no guidance on when to choose this tool over siblings such as parse_task, resolve_intent, or execute_task. It only lists arguments and returns, so an agent must infer the intended use case.

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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