Pro ChatGPT GPTs Dify LangGraph

Data Insight Narrator

Turns raw metrics and query results into decision-ready narratives: findings, so-what, confidence and recommended actions.

0 downloads 0 views Updated Sep 30, 2026 v1.2.0

Overview

Data Insight Narrator is the bridge between a spreadsheet of numbers and a room of decision-makers. Feed it query results, dashboards exports or summary metrics and it produces an executive-ready narrative: what changed, why it matters, how confident we are, and what to do next.

It separates observation from interpretation, quantifies impact in business terms, flags anomalies and seasonality instead of over-explaining noise, and explicitly lists what the data does NOT show.

The output format works for weekly business reviews, product analytics digests and investor updates alike.

System prompt

Preview redacted

The instruction block that defines the agent's role, rules and output format.

system-prompt.txt

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User prompt template

Fill in the variables and send it to run the skill: {{variables}}

user-template.txt

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Variables

Name	Required	Description	Example
{{metrics}}	Yes	Raw numbers, CSV/JSON results or dashboard summary.	—
{{dataset_desc}}	Yes	What the data covers and how it was collected.	Postgres events table, signup-to-activation funnel, last 90 days
{{time_window}}	Optional	The reporting period and comparison baseline.	Sep 1–30 vs Aug, UTC
{{audience}}	Optional	Who reads the narrative.	exec team at a seed-stage SaaS

Full skill configuration

Redacted preview

The standard .aiskill file in JSON and YAML.

data-insight-narrator.aiskill (JSON)

{
  "format": "aiskill/v1",
  "skill": {
    "name": "Data Insight Narrator",
    "slug": "data-insight-narrator",
    "version": "1.2.0",
    "description": "Turns raw metrics and query results into decision-ready narratives: findings, so-what, confidence and recommended actions.",
    "category": "Data",
    "tags": [
      "analytics",
      "reporting",
      "storytelling",
      "business-intelligence"
    ],
    "platforms": [
      "chatgpt",
      "dify",
      "langgraph"
    ],
    "tested_environment": "GPT-5, Claude Sonnet 4.5; CSV/JSON exports up to ~5k rows summarized",
    "license": "CC-BY-4.0"
  },
  "prompts": {
    "system": "████████████████████████████████████████████████████████████████████████████████████████████████",
    "user_template": "████████████████████████████████████████████████████████████████████████████████████████████████"
  },
  "variables": [
    {
      "name": "metrics",
      "description": "Raw numbers, CSV/JSON results or dashboard summary.",
      "required": true
    },
    {
      "name": "dataset_desc",
      "description": "What the data covers and how it was collected.",
      "required": true,
      "example": "Postgres events table, signup-to-activation funnel, last 90 days"
    },
    {
      "name": "time_window",
      "description": "The reporting period and comparison baseline.",
      "required": false,
      "example": "Sep 1–30 vs Aug, UTC"
    },
    {
      "name": "audience",
      "description": "Who reads the narrative.",
      "required": false,
      "example": "exec team at a seed-stage SaaS"
    }
  ],
  "install": {
    "steps": [
      {
        "title": "Copy the system prompt",
        "detail": "Copy the narrator system prompt from the skill page."
      },
      {
        "title": "Create a reporting agent",
        "detail": "Paste it into a custom GPT or Dify/LangGraph reporting agent."
      },
      {
        "title": "Paste your numbers",
        "detail": "Provide the metrics, dataset context and time window per report."
      },
      {
        "title": "Distribute",
        "detail": "Drop the Headline + Recommended actions into your weekly review doc."
      }
    ]
  },
  "usage": {
    "steps": [
      "Export the metrics you want narrated, including a comparison baseline.",
      "Fill in dataset context so confidence ratings are meaningful.",
      "Review hypothesis labels and verify any HIGH-impact claim before acting.",
      "Track the Watch list metrics in your next reporting cycle."
    ]
  },
  "metadata": {
    "author": "SkillVault",
    "source": "https://skillvault.top/skills/data-insight-narrator",
    "exported_at": "2026-11-03T07:43:38.894Z"
  }
}

data-insight-narrator.aiskill (YAML)

format: aiskill/v1
skill:
  name: Data Insight Narrator
  slug: data-insight-narrator
  version: 1.2.0
  description: >-
    Turns raw metrics and query results into decision-ready narratives: findings, so-what,
    confidence and recommended actions.
  category: Data
  tags:
    - analytics
    - reporting
    - storytelling
    - business-intelligence
  platforms:
    - chatgpt
    - dify
    - langgraph
  tested_environment: GPT-5, Claude Sonnet 4.5; CSV/JSON exports up to ~5k rows summarized
  license: CC-BY-4.0
prompts:
  system: ████████████████████████████████████████████████████████████████████████████████████████████████
  user_template: ████████████████████████████████████████████████████████████████████████████████████████████████
variables:
  - name: metrics
    description: Raw numbers, CSV/JSON results or dashboard summary.
    required: true
  - name: dataset_desc
    description: What the data covers and how it was collected.
    required: true
    example: Postgres events table, signup-to-activation funnel, last 90 days
  - name: time_window
    description: The reporting period and comparison baseline.
    required: false
    example: Sep 1–30 vs Aug, UTC
  - name: audience
    description: Who reads the narrative.
    required: false
    example: exec team at a seed-stage SaaS
install:
  steps:
    - title: Copy the system prompt
      detail: Copy the narrator system prompt from the skill page.
    - title: Create a reporting agent
      detail: Paste it into a custom GPT or Dify/LangGraph reporting agent.
    - title: Paste your numbers
      detail: Provide the metrics, dataset context and time window per report.
    - title: Distribute
      detail: Drop the Headline + Recommended actions into your weekly review doc.
usage:
  steps:
    - Export the metrics you want narrated, including a comparison baseline.
    - Fill in dataset context so confidence ratings are meaningful.
    - Review hypothesis labels and verify any HIGH-impact claim before acting.
    - Track the Watch list metrics in your next reporting cycle.
metadata:
  author: SkillVault
  source: https://skillvault.top/skills/data-insight-narrator
  exported_at: "2026-11-03T07:43:38.894Z"

Installation guide

1

Copy the system prompt

Copy the narrator system prompt from the skill page.
2

Create a reporting agent

Paste it into a custom GPT or Dify/LangGraph reporting agent.
3

Paste your numbers

Provide the metrics, dataset context and time window per report.
4

Distribute

Drop the Headline + Recommended actions into your weekly review doc.

How to use

Export the metrics you want narrated, including a comparison baseline.
Fill in dataset context so confidence ratings are meaningful.
Review hypothesis labels and verify any HIGH-impact claim before acting.
Track the Watch list metrics in your next reporting cycle.

Platform compatibility

ChatGPT GPTs

OpenAI

Paste the system prompt into the GPT "Instructions" field and keep the user template as your starter message.

Official docs

Dify

LangGenius

Create a new Agent/App, paste the system prompt as the system prompt, and register template variables as input fields.

Official docs

LangGraph

LangChain

Load the JSON config into your graph state: use prompts.system for the system message and prompts.user_template as a runnable template.

Official docs

Preview gallery

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