Neotic

cognitive_execute_task

One-call orchestration: identify → gate → guide → solve → verify → report.

Parameters:
- task: Dict containing:
  - task_structure (or loose definition: name, entities, constraints, etc.)
  - raw (optional): Domain-specific execution payload. If omitted, returns
    status='guidance_only' with 'recommended_action'='supply_raw' and
    an 'expected_raw_formats' object detailing valid schemas.
    Supported problem types for task.raw:
    * scheduling: {"workers": [{"id": "w1", "eligible_shifts": ["s1"], "max_shifts": 1}],
                   "shifts": [{"id": "s1", "required_workers": 1}]}
    * allocation: {"consumers": [{"id": "c1", "demands": {"r1": 1}}],
                   "resources": [{"id": "r1", "capacity": 2}]}
    * graph: {"nodes": ["A", "B"], "edges": [["A", "B"]]}
    * graph_coloring: {"nodes": ["A", "B"], "edges": [["A", "B"]], "colors": ["red", "blue"]}
    * shortest_path: {"nodes": ["A", "B"], "edges": [["A", "B"]], "weights": {"A->B": 1.0}, "start": "A", "target": "B"}
    * math: {"math": {"question": "...", "quantities": {...}, "equations": [...], "target_variable": "x", "ground_truth": 42.0}}
    * code: {"code": {"code": "def solution()...", "tests": ["assert ..."]}}
    * pddl: {"pddl": {"plan": [...], "init": {...}, "goal": {...}}}

Returns a single envelope with status (completed / guidance_only /
blocked_until_clarified / no_applicable_guidance / refused_infeasible /
failed), solution, score, assumptions, failure reasons, and expected_raw_formats.

Input Schema

TableJSON Schema

Name	Required	Default
`goal`	No
`task`	No
`environment`	No
`model_family`	No	generic

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 / additionalProperties
```
Removed value: -true
```
- addedInput schema / properties / task / anyOf
```
Added value: +[
+  {
+    "additionalProperties": true,
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]
```
- addedInput schema / properties / task / default
```
Added value: +null
```
- removedInput schema / properties / task / type
```
Removed value: -"object"
```
- removedInput schema / required
```
Removed value: -[
-  "task"
-]
```
AddedSep 19, 2026

TDQS

B3.4/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden and does a good job: it discloses the orchestration flow, the guidance-only fallback, the possible status values, and the return envelope. It does not discuss side effects, permissions, or resource consumption, but this appears to be a read-only/stateless orchestrator, so the disclosure is reasonably complete.

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 long but front-loaded with the orchestration pipeline and uses clear bulleted sections. The raw-format examples are verbose yet practically valuable for invoking the tool correctly; minor trimming of redundant phrasing would improve conciseness.

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?

For a complex tool with an output schema, the description covers statuses, raw formats, and response envelope well. Still, it leaves the semantics of goal, environment, and model_family unexplained, and it treats task as central while the schema marks it optional, creating ambiguity about what a minimal valid invocation looks like.

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?

The description thoroughly documents the task parameter and provides detailed examples for eight raw problem types. However, goal, environment, and model_family receive no explanation beyond their names in the JSON schema, and with 0% schema coverage, the description fails to compensate for most parameters.

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 clearly identifies the tool as a one-call orchestrator that handles an end-to-end pipeline (identify → gate → guide → solve → verify → report). It is distinct from narrower sibling tools like cognitive_identify_task or cognitive_get_guidance, though it does not explicitly name those alternatives.

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: supply task_structure and raw to execute, or omit raw to receive guidance_only with expected_raw_formats. It gives supported problem types but never explicitly says when not to use this tool or when to choose a sibling, which matters given the large sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Neotic tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?