Cleotic

Suggest prompts

suggest_prompts

Read-onlyIdempotent

Suggest prompts for a segment about a topic. Ranked by AI search demand only when the demand provider has data; monthly_ai_searches null or 0 means none was found. Saves nothing and returns no IDs: add the ones you want with save_prompt (text, tags, category, intent_type). Cost: one AI model call from the model budget.

Input Schema

TableJSON Schema

Name	Required	Description
`brand`	Yes	Brand or study: its ID from list_brands, or its name (exact or a unique prefix).
`count`	No	How many to suggest. Defaults to 8.
`topic`	Yes	What the prompts should be about.
`segment`	Yes	Segment ID or name.

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes
`generated_at`	Yes	RFC 3339 time the response was made.
`schema_version`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 1, 2026

changedOutput schema / properties / data / properties / cost / properties / readiness_scans / description

Previous value: -"Site readiness scans used from the plan's monthly allowance."New value: +"Full site readiness scans started; counted for the month, with no monthly allowance."

changedOutput schema / properties / data / properties / suggestions / description

Previous value: -"Highest AI search demand first."New value: +"Highest AI search demand first when demand data exists; otherwise the model's order."

Changed6 schema fields changedOct 1, 2026

addedInput schema / additionalProperties
```
Added value: +false
```
addedInput schema / properties / brand / minLength
```
Added value: +1
```

changedInput schema / properties / count / description

Previous value: -"How many to suggest."New value: +"How many to suggest. Defaults to 8."

addedInput schema / properties / segment / minLength
```
Added value: +1
```
addedInput schema / properties / topic / minLength
```
Added value: +1
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "data": {
+      "additionalProperties": false,
+      "properties": {
+        "brand": {
+          "additionalProperties": false,
+          "properties": {
+            "id": {
+              "type": "string"
+            },
+            "name": {
+              "type": "string"
+            },
+            "url": {
+              "description": "The brand's website, or empty when none is set.",
+              "type": "string"
+            }
+          },
+          "required": [
+            "id",
+            "name",
+            "url"
+          ],
+          "type": "object"
+        },
+        "cost": {
+          "additionalProperties": false,
+          "properties": {
+            "content_generations": {
+              "description": "Content Studio generations used from the plan's allowance.",
+              "type": "integer"
+            },
+            "model_budget": {
+              "description": "Whether the call spends the organisation's AI model budget.",
+              "type": "boolean"
+            },
+            "note": {
+              "type": "string"
+            },
+            "prompt_capacity": {
+              "description": "Active prompts added against the plan's prompt limit.",
+              "type": "integer"
+            },
+            "queued_model_runs": {
+              "description": "Answer collections queued; each uses model budget.",
+              "type": "integer"
+            },
+            "readiness_checks": {
+              "description": "Readiness re-checks used from the plan's monthly allowance.",
+              "type": "integer"
+            },
+            "readiness_scans": {
+              "description": "Site readiness scans used from the plan's monthly allowance.",
+              "type": "integer"
+            }
+          },
+          "required": [
+            "model_budget",
+            "content_generations",
+            "readiness_scans",
+            "readiness_checks",
+            "prompt_capacity",
+            "queued_model_runs",
+            "note"
+          ],
+          "type": "object"
+        },
+        "segment": {
+          "additionalProperties": false,
+          "properties": {
+            "id": {
+              "type": "string"
+            },
+            "name": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "id",
+            "name"
+          ],
+          "type": "object"
+        },
+        "suggestions": {
+          "description": "Highest AI search demand first.",
+          "items": {
+            "additionalProperties": false,
+            "properties": {
+              "category": {
+                "type": "string"
+              },
+              "intent_type": {
+                "type": "string"
+              },
+              "monthly_ai_searches": {
+                "description": "null when no search demand was found.",
+                "type": [
+                  "null",
+                  "integer"
+                ]
+              },
+              "tags": {
+                "items": {
+                  "type": "string"
+                },
+                "type": "array"
+              },
+              "text": {
+                "description": "Pass to save_prompt to track it.",
+                "type": "string"
+              }
+            },
+            "required": [
+              "text",
+              "tags",
+              "category",
+              "intent_type",
+              "monthly_ai_searches"
+            ],
+            "type": "object"
+          },
+          "type": "array"
+        }
+      },
+      "required": [
+        "brand",
+        "segment",
+        "suggestions",
+        "cost"
+      ],
+      "type": "object"
+    },
+    "generated_at": {
+      "description": "RFC 3339 time the response was made.",
+      "type": "string"
+    },
+    "schema_version": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "schema_version",
+    "generated_at",
+    "data"
+  ],
+  "type": "object"
+}

AddedSep 30, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Goes well beyond the annotations: it discloses ranking behavior (ranked by AI search demand only when the provider has data), how to interpret null/0 values, that nothing is persisted and no IDs are returned, and the cost (one AI model call). That's rich context an agent cannot get from the structured fields.

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?

Three dense, front-loaded sentences with no filler; the persistence caveat and cost are packed efficiently. Slightly information-dense but every sentence earns its place.

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

Completeness4/5

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

With an output schema present, return values need not be spelled out, yet the description still clarifies the null/0 semantics of monthly_ai_searches and the cost/handoff behavior. Complete enough for correct invocation.

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?

Schema description coverage is 100%, so brand/segment/topic/count are already documented in the schema. The description adds no parameter-level syntax or defaults beyond that, so the baseline 3 applies.

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?

States a specific verb and resource ('Suggest prompts') plus scope ('for a segment about a topic'), which cleanly distinguishes it from list_prompts and save_prompt without opening any schema.

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

Usage Guidelines4/5

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

It routes the agent explicitly: 'Saves nothing and returns no IDs: add the ones you want with save_prompt.' This names the follow-up tool and its params. It doesn't contrast against list_prompts, so it stops short of a full when/when-not matrix, but the actionable handoff is 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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