Gpc train

Skill yasserstudio/gpc-skills/gpc-train

Agent skills for the GPC CLI. 19 skills that teach Claude Code how to use GPC for Google Play workflows: releases, metadata, vitals, monetization, CI/CD.

Install

npx -y skills add yasserstudio/gpc-skills --skill gpc-train

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Use when setting up or managing automated staged rollout pipelines with GPC. Trigger when the user mentions gpc train, release train, staged rollout automation, rollout pipeline, release gates, automatic rollout progression, auto-halt on regression, rollout stages — even if they don't explicitly say 'train.' Also trigger when someone wants to automatically progress a release from internal → alpha → production with time gates, or set up crash/ANR gates that pause a rollout.

SKILL.md

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GPC Release Train

When to use

Use this skill when the task involves:

Setting up a config-driven staged rollout pipeline
Automatically progressing a release through tracks (internal → alpha → production) with time gates
Gating progression on crash rate and ANR rate thresholds
Pausing, resuming, or aborting an in-flight release train
Checking the current stage and gate health of a running train

Inputs required

Package name (or configured default in .gpcrc.json)
Release train config: stages with tracks, rollout percentages, and time delays
Gate thresholds: max crash rate and max ANR rate
Whether to pause, resume, or abort the train

Procedure

1) Configure the release train

Add a release-train block to .gpcrc.json in the project root:

{
  "release-train": {
    "stages": [
      { "track": "internal",   "rollout": 100 },
      { "track": "alpha",      "rollout": 100, "after": "2d" },
      { "track": "production", "rollout": 10,  "after": "7d" },
      { "track": "production", "rollout": 100, "after": "14d" }
    ],
    "gates": { "crashes": { "max": 1.5 }, "anr": { "max": 0.5 } }
  }
}

Config keys:

Key	Type	Description
`stages[].track`	string	Target track: `internal`, `alpha`, `beta`, `production`
`stages[].rollout`	number	Rollout percentage for this stage (1–100)
`stages[].after`	string	Minimum time to wait before this stage (e.g., `2d`, `12h`, `30m`). Omit for immediate.
`gates.crashes.max`	number	Maximum crash rate percentage before pausing progression
`gates.anr.max`	number	Maximum ANR rate percentage before pausing progression

Read:

references/rollout-pipeline.md

2) Start the train

gpc train start

This reads .gpcrc.json, creates a state file at ~/.cache/gpc/train-<packageName>.json, and begins executing the first stage immediately. Subsequent stages are executed when the after time has elapsed and gates pass.

# Resume a paused train
gpc train start --resume

3) Check train status

gpc train status

Output:

Release Train · com.example.app
  Stage 2 / 4   alpha @ 100%   in progress
  Last progressed: 2026-03-17 11:00 (2 days ago)
  Next stage: production @ 10%   eligible in 5 days

  Gates (last check: 10 minutes ago)
    crashes   0.82%   ✓  (max 1.5%)
    anr       0.19%   ✓  (max 0.5%)

# Resume if paused due to a gate failure
gpc train status --resume

4) Monitor gate health

Before each stage transition, gpc train automatically checks the configured gates:

If all gates pass, the stage progresses (subject to the after time having elapsed).
If any gate fails, progression is paused and a warning is shown.
The user must fix the regression and re-run gpc train start --resume or gpc train status --resume.

Gate checks call the same vitals API as gpc vitals crashes and gpc vitals anr. Data lag of 6–48 hours applies to new releases — avoid configuring gates on the very first stage.

5) Pause a running train

gpc train pause

Pauses automatic progression. Does not halt or change the active rollout on any track. Run gpc train start --resume to continue.

6) Abort the train

gpc train abort

Aborts the train and halts all active rollouts on tracks managed by this train. State file is cleared. Use when a critical regression is found and the release must be stopped immediately.

Verification

gpc train status shows the correct current stage and gate health values
gpc status confirms rollout percentages on each track match the active stage in the train config
Gate values (crashes, ANR) are below configured max thresholds
State file at ~/.cache/gpc/train-<packageName>.json reflects the current stage index and last progression timestamp

Failure modes / debugging

Symptom	Likely Cause	Fix
Gate check fails	Crash/ANR rate above configured `max`	Fix the regression in a new release, then `gpc train start --resume`
`Train already running`	Previous train was not completed or aborted	`gpc train status` to check state; `gpc train abort` if needed
Stage progression skipped	`after` time has not elapsed	`gpc train status` shows time remaining until next eligible stage
Train aborted unexpectedly	Gate threshold breached automatically	Check `gpc vitals crashes` and `gpc vitals anr`, fix regression, then restart
State file missing	Cache directory cleared or different machine	Re-run `gpc train start` — it will re-read `.gpcrc.json` and restart from stage 1