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. This came from an engineering director who calculated velocity manually in a spreadsheet because the built-in charts did not account for story point inflation. The reporter normalizes velocity metrics across teams and sprints.

Last updated March 17, 2026

Engineering leaders spend 4-6 hours per week manually compiling velocity reports from Jira or Linear. The reports are backward-looking and arrive too late to affect the current sprint. Automated velocity reporting delivers actionable insights — cycle time trends, throughput changes, bottleneck identification — before the retrospective.

triggerSchedule01FetcherLinear GraphQL02Assembler5 VHD Metrics03AnalystVHS Scoring04FormatterReport + DigestNotionVelocity ReportSlackVHS Digest

Four Agents. Weekly Velocity Report. Dual-Audience Insights.

The Fetcher

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.

The Assembler

Step 2 — The Assembler

Code-only

What does The Assembler actually decide? 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).

The Analyst

Step 3 — The Analyst

Classification

This step exists because raw data alone is not enough. 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.

The Formatter

Step 4 — The Formatter

Creative

Without this step, upstream analysis sits idle. 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.A non-idempotent re-run turned a 32-node workflow into 44 nodes. Every build script now removes existing nodes before adding fresh ones.

That's the full pipeline. Here's what it intentionally does NOT do — and why those boundaries exist.

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

With those boundaries clear, here's everything that ships when you purchase.

The Complete Customer Success Bundle

7 files.

CHANGELOG.md — Version history
README.md — Setup and configuration guide
docs/TDD.md — Technical Design Document
linear_engineering_velocity_reporter_v1_0_0.json — n8n workflow (main pipeline)
system_prompts/analyst_system_prompt.md — Analyst system prompt
system_prompts/formatter_system_prompt.md — Formatter system prompt
workflow/levr_scheduler_v1_0_0.json — Scheduler workflow

The technical specifications below are ITP-measured, not estimated.

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 Velocity Health Score (VHS) scores).

Tested on n8n v2.7.5, March 2026

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.

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?

How does this compare to the Jira Engineering Velocity Reporter?+

Same analysis framework adapted for Linear's data model. Linear uses estimates and cycles instead of Jira's story points and sprints. Both produce identical output format for engineering leadership.

Read the full guide →

Related Blueprints

Linear Sprint Risk Analyzer

AI-powered weekly sprint risk analysis that scores velocity deviation, blocked chains, scope creep, and concentration risk from your Linear data — delivered as a Notion brief and Slack digest every Monday.

$199

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.

$199

Feature Request Extractor

Every feature request in Slack becomes a structured Linear issue. Automatically.

$199