---
title: "Have an agent investigate every new issue before a person does"
description: "Post a diagnosis with evidence, assumptions and reproduction results on each new issue."
url: https://starsling.dev/ci-playbooks/techniques/triage-investigation
canonicalUrl: https://starsling.dev/ci-playbooks/techniques/triage-investigation
---

# Have an agent investigate every new issue before a person does

Post a diagnosis with evidence, assumptions and reproduction results on each new issue.

## How to choose an approach

This technique currently has one documented company example. Validate its prerequisites, tradeoffs and original CI environment against your repository before adapting it.

- **[Mastra](https://starsling.dev/ci-playbooks/mastra#triage-investigation)**: Use it when Many new issues are too vague to reproduce or come from setup mistakes, and each takes a person's time to sort. Check before adopting: Review the investigation's assumptions before planning starts, since an incorrect assumption upstream carries into every later stage. Adapted for GitHub Actions; compare the original system with yours.

## Apply this technique

````text
Evaluate and apply this CI technique to my repository: Have an agent investigate every new issue before a person does.

Post a diagnosis with evidence, assumptions and reproduction results on each new issue.

Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/triage-investigation.md

Inspect this repository’s CI workflows, build and test commands, dependencies, and recent run timings. Identify where this technique applies and explain the expected benefit using this repository’s evidence.
Measure a baseline from recent comparable runs: elapsed time, queue time, runner minutes and failures where available. If data is unavailable, say what cannot be measured.
Compare relevant company approaches, checking prerequisites, platform differences and tradeoffs. Rank applicable options by evidence, fit and measurable opportunity; do not present company results as predictions for this repo.
Recommend the smallest safe change, show what checks and fallback paths remain, and ASK ME WHICH CHANGE TO APPROVE BEFORE EDITING ANY FILES.
Only after approval, work on a new feature branch, make one reversible change, and open a reviewable pull request. Never merge or push to a default or protected branch.
Keep required checks, test coverage, deployment and release behavior intact. Validate the change and compare equivalent runs where possible; report limitations and what should be monitored after merge.
````

## How Mastra used this technique

Read what Mastra changed and follow the original sources.

### Mastra: Have an agent investigate every new issue before a person does

**Translated to GitHub Actions**

- What Mastra built: Mastra Factory produces an investigation for each new issue: a diagnosis, supporting evidence, assumptions and reproduction results.
- Your GitHub Actions version: An agent that investigates every new issue and posts a diagnosis, evidence, assumptions and reproduction results before a person looks.

Mastra's earlier intake bot supplied labels and a welcome comment. Factory produces an investigation the next person can use: a diagnosis, supporting evidence, assumptions and reproduction results. Its A2A investigation documented six failing reproduction assertions and identified the server integration as the owner. Mastra credits observational memory, which compresses file contents, searches and test output into a line-by-line log of the important items.

Evidence: Company-reported result or observation

its A2A investigation documented six failing reproduction assertions and identified the server integration as the owner ([Source](https://mastra.ai/blog/announcing-mastra-factory-beta))

Use it when: Many new issues are too vague to reproduce or come from setup mistakes, and each takes a person's time to sort.

Before applying it: Review the investigation's assumptions before planning starts, since an incorrect assumption upstream carries into every later stage.

GitHub Actions adaptation: Compare the source system with your own workflow before applying this translation.

[Read more in the Mastra playbook](https://starsling.dev/ci-playbooks/mastra#triage-investigation)

[Primary source](https://mastra.ai/blog/announcing-mastra-factory-beta)

## CI optimization is continuous work.

Apply this technique yourself, or use StarSling Runners for faster GitHub Actions and optional agent-driven optimization PRs, which teams on eligible paid plans can turn on.

[Get self-improving CI](https://starsling.dev/products/runners)

## Company Playbooks

### [Anthropic](https://starsling.dev/ci-playbooks/anthropic)

Run only affected tests

### [DoorDash](https://starsling.dev/ci-playbooks/doordash)

Run build and test in parallel, sharded across CI agents

### [Linear](https://starsling.dev/ci-playbooks/linear)

Benchmark the same job on faster hardware

### [Mastra](https://starsling.dev/ci-playbooks/mastra)

StarSling runners for the slowest test workflow

### [OpenAI](https://starsling.dev/ci-playbooks/openai)

Rank CI fixes by the minutes they save

### [Ramp](https://starsling.dev/ci-playbooks/ramp)

Move a CPU-bound test suite to a faster CPU

### [Shopify](https://starsling.dev/ci-playbooks/shopify)

Let an agent iterate against one CI metric

### [Spotify](https://starsling.dev/ci-playbooks/spotify)

Build arm64 on native arm64 runners

### [Stripe](https://starsling.dev/ci-playbooks/stripe)

Run only the tests a change can reach

### [Uber](https://starsling.dev/ci-playbooks/uber)

Build the merge-queue speculations most likely to be needed