Skills extract-kpi-data
Extract campaign or business KPIs from report documents — metrics, values, periods, and targets.
install
source · Clone the upstream repo
git clone https://github.com/iterationlayer/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/iterationlayer/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/extract-kpi-data" ~/.claude/skills/iterationlayer-skills-extract-kpi-data && rm -rf "$T"
manifest:
skills/extract-kpi-data/SKILL.mdsource content
Extract KPI Data
Marketing agencies, analytics teams, and finance departments use this recipe to extract performance metrics from campaign summaries or quarterly reports — pulling out KPIs like impressions, conversions, spend, and ROAS for dashboards and automated reporting.
APIs Used
Document Extraction (1 credit per page)
Prerequisites
You need an Iteration Layer API key. Get one at platform.iterationlayer.com — free trial credits included, no credit card required.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
Implementation
curl -X POST https://api.iterationlayer.com/document-extraction/v1/extract \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "files": [ { "type": "url", "name": "campaign-summary-q1.pdf", "url": "https://example.com/reports/campaign-summary-q1-2026.pdf" } ], "schema": { "fields": [ { "name": "client_name", "type": "TEXT", "description": "Client or company name" }, { "name": "report_period", "type": "TEXT", "description": "Reporting period, e.g. Q1 2026" }, { "name": "total_impressions", "type": "INTEGER", "description": "Total ad impressions" }, { "name": "total_clicks", "type": "INTEGER", "description": "Total ad clicks" }, { "name": "click_through_rate", "type": "DECIMAL", "description": "Click-through rate as a percentage" }, { "name": "total_conversions", "type": "INTEGER", "description": "Total conversions or leads generated" }, { "name": "cost_per_conversion", "type": "CURRENCY_AMOUNT", "description": "Average cost per conversion" }, { "name": "total_spend", "type": "CURRENCY_AMOUNT", "description": "Total advertising spend" }, { "name": "return_on_ad_spend", "type": "DECIMAL", "description": "Return on ad spend ratio" } ] } }'
import { IterationLayer } from "iterationlayer"; const client = new IterationLayer({ apiKey: "YOUR_API_KEY" }); const result = await client.extract({ files: [ { type: "url", name: "campaign-summary-q1.pdf", url: "https://example.com/reports/campaign-summary-q1-2026.pdf", }, ], schema: { fields: [ { name: "client_name", type: "TEXT", description: "Client or company name" }, { name: "report_period", type: "TEXT", description: "Reporting period, e.g. Q1 2026" }, { name: "total_impressions", type: "INTEGER", description: "Total ad impressions" }, { name: "total_clicks", type: "INTEGER", description: "Total ad clicks" }, { name: "click_through_rate", type: "DECIMAL", description: "Click-through rate as a percentage" }, { name: "total_conversions", type: "INTEGER", description: "Total conversions or leads generated" }, { name: "cost_per_conversion", type: "CURRENCY_AMOUNT", description: "Average cost per conversion" }, { name: "total_spend", type: "CURRENCY_AMOUNT", description: "Total advertising spend" }, { name: "return_on_ad_spend", type: "DECIMAL", description: "Return on ad spend ratio" }, ], }, });
from iterationlayer import IterationLayer client = IterationLayer(api_key="YOUR_API_KEY") result = client.extract( files=[ { "type": "url", "name": "campaign-summary-q1.pdf", "url": "https://example.com/reports/campaign-summary-q1-2026.pdf", } ], schema={ "fields": [ {"name": "client_name", "type": "TEXT", "description": "Client or company name"}, {"name": "report_period", "type": "TEXT", "description": "Reporting period, e.g. Q1 2026"}, {"name": "total_impressions", "type": "INTEGER", "description": "Total ad impressions"}, {"name": "total_clicks", "type": "INTEGER", "description": "Total ad clicks"}, {"name": "click_through_rate", "type": "DECIMAL", "description": "Click-through rate as a percentage"}, {"name": "total_conversions", "type": "INTEGER", "description": "Total conversions or leads generated"}, {"name": "cost_per_conversion", "type": "CURRENCY_AMOUNT", "description": "Average cost per conversion"}, {"name": "total_spend", "type": "CURRENCY_AMOUNT", "description": "Total advertising spend"}, {"name": "return_on_ad_spend", "type": "DECIMAL", "description": "Return on ad spend ratio"}, ] }, )
package main import il "github.com/iterationlayer/sdk-go" func main() { client := il.NewClient("YOUR_API_KEY") result, err := client.Extract(il.ExtractRequest{ Files: []il.FileInput{ il.NewFileFromURL("campaign-summary-q1.pdf", "https://example.com/reports/campaign-summary-q1-2026.pdf"), }, Schema: il.ExtractionSchema{ "client_name": il.NewTextFieldConfig("client_name", "Client or company name"), "report_period": il.NewTextFieldConfig("report_period", "Reporting period, e.g. Q1 2026"), "total_impressions": il.NewIntegerFieldConfig("total_impressions", "Total ad impressions"), "total_clicks": il.NewIntegerFieldConfig("total_clicks", "Total ad clicks"), "click_through_rate": il.NewDecimalFieldConfig("click_through_rate", "Click-through rate as a percentage"), "total_conversions": il.NewIntegerFieldConfig("total_conversions", "Total conversions or leads generated"), "cost_per_conversion": il.NewCurrencyAmountFieldConfig("cost_per_conversion", "Average cost per conversion"), "total_spend": il.NewCurrencyAmountFieldConfig("total_spend", "Total advertising spend"), "return_on_ad_spend": il.NewDecimalFieldConfig("return_on_ad_spend", "Return on ad spend ratio"), }, }) if err != nil { panic(err) } _ = result }
{ "name": "Extract KPI data in Iteration Layer", "nodes": [ { "parameters": { "content": "## Extract KPI Data\n\nMarketing agencies, analytics teams, and finance departments use this recipe to extract performance metrics from campaign summaries or quarterly reports — pulling out KPIs like impressions, conversions, spend, and ROAS for dashboards and automated reporting.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes before importing. Self-hosted n8n only.", "height": 280, "width": 500, "color": 2 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [200, 40], "id": "e2f3a4b5-c6d7-8901-efab-678901234501", "name": "Overview" }, { "parameters": { "content": "### Step 1: Extract KPI Data\nResource: **Document Extraction**\n\nConfigure the Document Extraction parameters below, then connect your credentials.", "height": 160, "width": 300, "color": 6 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [475, 100], "id": "e2f3a4b5-c6d7-8901-efab-678901234502", "name": "Step 1 Note" }, { "parameters": {}, "type": "n8n-nodes-base.manualTrigger", "typeVersion": 1, "position": [250, 300], "id": "e2f3a4b5-c6d7-8901-efab-678901234503", "name": "Manual Trigger" }, { "parameters": { "resource": "documentExtraction", "schemaInputMode": "rawJson", "schemaJson": "{\"fields\":[{\"name\":\"client_name\",\"type\":\"TEXT\",\"description\":\"Client or company name\"},{\"name\":\"report_period\",\"type\":\"TEXT\",\"description\":\"Reporting period\"},{\"name\":\"total_impressions\",\"type\":\"INTEGER\",\"description\":\"Total ad impressions\"},{\"name\":\"total_clicks\",\"type\":\"INTEGER\",\"description\":\"Total ad clicks\"},{\"name\":\"click_through_rate\",\"type\":\"DECIMAL\",\"description\":\"Click-through rate as a percentage\"},{\"name\":\"total_conversions\",\"type\":\"INTEGER\",\"description\":\"Total conversions or leads generated\"},{\"name\":\"cost_per_conversion\",\"type\":\"CURRENCY_AMOUNT\",\"description\":\"Average cost per conversion\"},{\"name\":\"total_spend\",\"type\":\"CURRENCY_AMOUNT\",\"description\":\"Total advertising spend\"},{\"name\":\"return_on_ad_spend\",\"type\":\"DECIMAL\",\"description\":\"Return on ad spend ratio\"}]}", "files": { "fileValues": [ { "fileInputMode": "url", "fileName": "campaign-summary-q1.pdf", "fileUrl": "https://example.com/reports/campaign-summary-q1-2026.pdf" } ] } }, "type": "n8n-nodes-iterationlayer.iterationLayer", "typeVersion": 1, "position": [500, 300], "id": "e2f3a4b5-c6d7-8901-efab-678901234504", "name": "Extract KPI Data", "credentials": { "iterationLayerApi": { "id": "1", "name": "Iteration Layer API" } } } ], "connections": { "Manual Trigger": { "main": [ [ { "node": "Extract KPI Data", "type": "main", "index": 0 } ] ] } }, "settings": { "executionOrder": "v1" } }
Extract KPI data from the file at [file URL]. Use the extract_document tool with these fields: - client_name (TEXT): Client or company name - report_period (TEXT): Reporting period, e.g. Q1 2026 - total_impressions (INTEGER): Total ad impressions - total_clicks (INTEGER): Total ad clicks - click_through_rate (DECIMAL): Click-through rate as a percentage - total_conversions (INTEGER): Total conversions or leads generated - cost_per_conversion (CURRENCY_AMOUNT): Average cost per conversion - total_spend (CURRENCY_AMOUNT): Total advertising spend - return_on_ad_spend (DECIMAL): Return on ad spend ratio
Response
{ "success": true, "data": { "client_name": { "value": "Greenfield Organics", "confidence": 0.99, "citations": ["Client: Greenfield Organics"] }, "report_period": { "value": "Q1 2026", "confidence": 0.99, "citations": ["Reporting Period: Q1 2026 (January — March)"] }, "total_impressions": { "value": 1245800, "confidence": 0.98, "citations": ["Total Impressions: 1,245,800"] }, "total_clicks": { "value": 37420, "confidence": 0.98, "citations": ["Total Clicks: 37,420"] }, "click_through_rate": { "value": 3.0, "confidence": 0.97, "citations": ["CTR: 3.00%"] }, "total_conversions": { "value": 1870, "confidence": 0.98, "citations": ["Total Conversions: 1,870"] }, "cost_per_conversion": { "value": { "amount": "12.45", "currency": "USD" }, "confidence": 0.97, "citations": ["Cost per Conversion: $12.45"] }, "total_spend": { "value": { "amount": "23281.50", "currency": "USD" }, "confidence": 0.98, "citations": ["Total Spend: $23,281.50"] }, "return_on_ad_spend": { "value": 4.2, "confidence": 0.96, "citations": ["ROAS: 4.2x"] } } }