Linear Engineering Velocity Reporter
Weekly AI-generated engineering velocity report from your Linear data — measures throughput trends, identifies bottlenecks, tracks contribution distribution, monitors bug/feature ratio, and flags cycle time outliers.
Weekly AI-generated engineering velocity report from your Linear data — measures throughput trends, identifies bottlenecks, tracks contribution distribution, monitors bug/feature ratio, and flags cycle time outliers.
Four Agents. Weekly Velocity Report. Dual-Audience Insights.
Step 1 — The Fetcher
Code-only
Queries Linear GraphQL API for completed issues across the lookback window — assignees, estimates, labels, state transitions, and completion timestamps. Groups issues by week for trend analysis.
Step 2 — The Assembler
Code-only
Computes 5 Velocity Health Dimensions: throughput trend (week-over-week vs 4-week baseline), bottleneck identification (state accumulation analysis), contribution distribution (Gini coefficient), bug/feature ratio (label classification), and cycle time health (median, P90, outliers).
Step 3 — The Analyst
Classification
Scores each dimension 1-10 (VHS), classifies overall health (HEALTHY/CONCERNING/CRITICAL), produces dual-audience output: executive summary for eng leadership + engineering recommendations with specific actions. Flags throughput decline >20% as URGENT alert.
Step 4 — The Formatter
Creative
Generates a Notion weekly velocity report with dimension breakdowns, trend data, and recommendations, plus a Slack Block Kit digest for the eng-leadership channel with VHS scores, executive summary, and top 3 actions.
What It Does NOT Do
Does not create Linear issues — use Feature Request Extractor (#20) for Slack-to-Linear issue creation
Does not predict sprint risk — use Linear Sprint Risk Analyzer (#46) for forward-looking per-sprint risk analysis
Does not audit backlog health — use Linear Backlog Grooming Intelligence (#53) for staleness and priority distribution audits
Does not modify Linear data — this is a read-only analysis tool
Does not work with non-Linear project management tools — this is Linear-specific
Does not track individual developer performance — this is team-level velocity analysis
The Complete Customer Success Bundle
7 files.
Tested. Measured. Documented.
Weekly 5-dimension engineering velocity analysis with dual-audience reporting (exec summary + eng recommendations) and dual-channel delivery (Notion velocity report + Slack digest with VHS scores).
Linear Engineering Velocity Reporter v1.0.0──────────────────────────────────────────Nodes: 24 main + 3 scheduler (27 total)Agents: 4 (Fetcher, Assembler, Analyst, Formatter)LLM Calls: 2 per run (Analyst + Formatter)Model: Sonnet 4.6 (SINGLE-MODEL — no Opus)Trigger: Weekly Monday 8:00 UTC (configurable)Pattern: AGGREGATE (one Analyst call per weekly run)Tool A: Linear (httpHeaderAuth) — completed issues, cycle data, assignee stats via GraphQLTool B: Notion (httpHeaderAuth) — weekly engineering velocity reportTool C: Slack (httpHeaderAuth) — digest for eng-leadershipCost: ~$0.03-$0.10/run (weekly aggregate)ITP: 8/8 variations, 14/14 milestonesBQS: 12/12
What You'll Need
Platform
n8n 2.7.5+
Est. Monthly API Cost
~$0.03-0.10 per weekly run + Linear subscription.
Credentials Required
- ▪Anthropic API
- ▪Linear (httpHeaderAuth, Bearer prefix)
- ▪Notion (httpHeaderAuth Bearer)
- ▪Slack (Bot Token, httpHeaderAuth Bearer)
Services
- ▪Linear account with API access
- ▪Anthropic API key
- ▪Notion workspace
- ▪Slack workspace (Bot Token with chat:write)
Setup Track
Quick Start
~15 min
All credentials live, n8n running
Full Setup
1–2 hrs
Needs API config + tables
From Scratch
2–4 hrs
No n8n, no credentials
Linear Engineering Velocity Reporter v1.0.0
$199
one-time purchase
What you get:
- ✓24-node main workflow + 3-node scheduler
- ✓Weekly engineering velocity report from Linear completed issue data
- ✓5-dimension Velocity Health Score (VHS): throughput trend, bottleneck identification, contribution distribution, bug/feature ratio, cycle time health
- ✓VHS 1-10 per dimension with overall health classification (HEALTHY/CONCERNING/CRITICAL)
- ✓Dual-audience output: executive summary for leadership + engineering recommendations for the team
- ✓Throughput decline >20% triggers URGENT alert with root cause analysis
- ✓Per-week throughput trend with 4-week rolling baseline comparison
- ✓Contribution distribution via Gini coefficient — detects bus factor risk
- ✓Bug/feature ratio monitoring with label-based classification
- ✓Cycle time analysis with median, P90, and outlier detection (>3x median)
- ✓Notion velocity report with dimension breakdowns and trend charts
- ✓Slack Block Kit digest with VHS scores and top 3 recommendations
- ✓Configurable: team IDs, velocity metric (issues/points), baseline weeks, alert threshold
- ✓Full technical documentation + system prompts
Frequently Asked Questions
What are the 5 Velocity Health Dimensions?+
Throughput trend (completion rate vs 4-week baseline), bottleneck identification (states where issues accumulate), contribution distribution (Gini coefficient measuring work balance), bug/feature ratio (bug-labeled vs feature-labeled issues), and cycle time health (median created-to-completed time plus outlier detection). Each scored 1-10.
When does it trigger an alert?+
When throughput (issues or story points completed) declines more than 20% compared to the 4-week rolling average. The threshold is configurable via DECLINE_ALERT_THRESHOLD. The alert includes root cause analysis and recommended actions in the Slack digest.
How does it differ from Linear Sprint Risk Analyzer?+
LSRA (#46) analyzes the ACTIVE sprint cycle — predicting risk for the current sprint (forward-looking). This product measures historical velocity trends across multiple weeks — tracking team throughput, bottlenecks, and health over time (retrospective). LSRA is per-sprint, LEVR is the executive engineering report.
Can I track story points instead of issue count?+
Yes. Set velocity_metric to "points" in the scheduler Payload Builder. The system will use story point estimates instead of issue count for throughput calculations, baseline comparisons, and contribution distribution.
What is the Gini coefficient?+
A measure of inequality in work distribution. 0.0 means perfectly equal distribution across all contributors. 1.0 means a single person did everything. Above 0.45 signals bus factor risk — the team depends too heavily on one contributor. The Analyst scores this dimension and recommends distribution improvements.
Does it use web scraping?+
No. All data comes from the Linear GraphQL API. No web scraping, no page parsing.
Is there a refund policy?+
All sales are final after download. Review the Blueprint Dependency Matrix and prerequisites before purchase. Questions? Contact support@forgeworkflows.com before buying. Full terms at forgeworkflows.com/legal.
Related Blueprints
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Linear Backlog Grooming Intelligence v1.0.0
Weekly AI backlog grooming intelligence that scores staleness, orphaned issues, duplicate clusters, blocked chains, and estimate gaps across your Linear backlog.
Feature Request Extractor
Every feature request in Slack becomes a structured Linear issue. Automatically.