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

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

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.

Changed1 schema field changedOct 13, 2026

changedOutput schema / properties / data / properties / cost / properties / content_generations / description

Previous value: -"Content Studio generations used from the plan's allowance."New value: +"Content Studio pages or outreach drafts used from the plan's allowance."

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

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world). The description adds genuinely new behavioral context beyond them: the one-model-call cost, the fact that ranking depends on the demand provider having data, and the null/0 sentinel meaning for monthly_ai_searches.

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?

Three sentences, front-loaded with the purpose and each carrying distinct information (ranking caveat, no-save behavior, cost). No filler or repeated schema content.

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

Completeness5/5

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

An output schema exists, so return structure needn't be repeated, and annotations carry the safety profile. The description fills the remaining gaps an agent needs: cost, the meaning of a null/0 demand figure, and the absence of persisted IDs.

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 and count are already documented, establishing a baseline of 3. The description doesn't add syntax or format detail for any input parameter; its illustrative parameter list (text, tags, category, intent_type) actually belongs to the sibling save_prompt, not this tool.

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 for a segment about a topic') and immediately carves out scope by noting it 'saves nothing and returns no IDs,' which distinguishes it from save_prompt and list_prompts without the agent 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?

Gives clear workflow context: this is a suggestion-generation step whose output is consumed via save_prompt (text, tags, category, intent_type). It routes the agent forward, but never states when to prefer this over list_prompts or what conditions make it worth the model-call cost.

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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