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Pr Monitoring

Community
lucasfcosta
pr-monitoring

Use after a pull request has been opened and the task is not finished until it lands. Triggers on "PR is open", "CI is running", "is it merged yet", a PR that is green but not merged, fresh CI that might still flip, or being tempted to report a task done at PR-open. GitHub / gh CLI based.

Overview

Publisherlucasfcosta
Repositorybackpressured
Skill namepr-monitoring
Stars
63
Forks
2
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by lucasfcosta on GitHub. Read the source before you install it.

Installation

Install the Pr Monitoring AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/lucasfcosta/backpressured/tree/main/skills/pr-monitoring
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/lucasfcosta/backpressured.git /tmp/backpressured
mkdir -p .claude/skills
cp -r /tmp/backpressured/skills/pr-monitoring .claude/skills/pr-monitoring
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pr Monitoring in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pr Monitoring on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pr Monitoring is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PR Monitoring

Overview

Open is not landed. Green is not merged. A PR you opened is unfinished work until it has actually merged with nothing outstanding — or you have named a blocker only a human can clear. You are the machine that keeps watching so a human doesn't have to babysit the PR; declaring "done" at PR-open (or at a freshly-green CI) is exactly the human-backpressure you exist to replace.

Two traps the base instinct misses even when it resists "open = done":

  1. A green check can flip red. Late-starting jobs and slow stages mean an initial all-green is not a final all-green.
  2. The watch ends at merge, not at first green. New commits, reviewer comments, and conflicts arrive after CI goes green.

When to Use

  • You (or the main agent) just opened a PR, or CI is running on one, and the goal is to get it merged.
  • Asked "is it merged / did it land / is CI done yet?" on a PR you own.
  • Tempted to report the task complete because the PR is open or CI just went green.

Not for: opening the PR itself; deciding whether to open one; code review of the diff (that is the reviewer skills). This is purely the watch-until-landed loop.

"Landed clean" — the sufficiency bar

Report done only when all hold; otherwise keep monitoring or name the blocker:

  • PR state is MERGED (not just approved, not just green).
  • Every required check is green — confirmed, not assumed (statusCheckRollup).
  • No unresolved review-bot or human comments.
  • No conflict (mergeStateStatus is not DIRTY) and the branch is not stale (BEHIND) — ideally CLEAN.

The monitoring loop

dot
digraph pr_monitor {
    "PR open" [shape=box];
    "Watch checks to completion" [shape=box];
    "All required checks green?" [shape=diamond];
    "Read failing logs, fix root cause, push" [shape=box];
    "Hold a green minute (≥60s continuously green)" [shape=box];
    "Anything flipped red / new check started?" [shape=diamond];
    "Comments or conflicts outstanding?" [shape=diamond];
    "Address them (push fix / resolve / reply)" [shape=box];
    "Merge if authorized" [shape=box];
    "Merged?" [shape=diamond];
    "STOP: name the human blocker" [shape=octagon];
    "Landed clean — report done" [shape=doublecircle];

    "PR open" -> "Watch checks to completion";
    "Watch checks to completion" -> "All required checks green?";
    "All required checks green?" -> "Read failing logs, fix root cause, push" [label="no"];
    "Read failing logs, fix root cause, push" -> "Watch checks to completion";
    "All required checks green?" -> "Hold a green minute (≥60s continuously green)" [label="yes"];
    "Hold a green minute (≥60s continuously green)" -> "Anything flipped red / new check started?";
    "Anything flipped red / new check started?" -> "Watch checks to completion" [label="yes — restart clock"];
    "Anything flipped red / new check started?" -> "Comments or conflicts outstanding?" [label="no"];
    "Comments or conflicts outstanding?" -> "Address them (push fix / resolve / reply)" [label="yes"];
    "Address them (push fix / resolve / reply)" -> "Watch checks to completion";
    "Comments or conflicts outstanding?" -> "Merge if authorized" [label="no"];
    "Merge if authorized" -> "Merged?";
    "Merged?" -> "STOP: name the human blocker" [label="no — needs approval/permission"];
    "Merged?" -> "Landed clean — report done" [label="yes"];
}

gh mechanics (quick reference)

NeedCommand
Watch checks (background, 1-min poll, 10-min cap)timeout 600 gh pr checks <pr> --watch --interval 60 &
Structured status in one shotgh pr view <pr> --json state,mergeStateStatus,reviewDecision,statusCheckRollup
Read only the failing job's logsgh run view <run-id> --log-failed
Read review-bot / human commentsgh pr view <pr> --comments
Merge when authorizedgh pr merge <pr> --squash (or repo's strategy)

Key mergeStateStatus values: CLEAN (mergeable), BLOCKED (needs approval/required check), BEHIND (must update branch), DIRTY (conflict), UNSTABLE (a non-required check failing).

Cadence & backgrounding (defaults)

Always monitor in the background — never block the session. The user must be able to keep prompting while the PR is watched, so run the watch as a background job (&, or your harness's background-task / re-invoking monitor) and check back on it. A foreground gh pr checks --watch that holds the terminal is wrong here — it freezes the user out.

  • Default window: 10 minutes of active polling per round (timeout 600).
  • Default poll interval: 1 minute (--interval 60) — not a tight loop, not once-and-walk-away.
  • When the 10-min window elapses without landing: report the current state (which checks are pending/red, review status, mergeability) and kick off another background round. Don't declare done and don't silently drop the watch — the task is still "land it"; the window only bounds each pass so you surface progress and stay responsive.
  • Defaults only: a BACKPRESSURE.md may override the window/interval, and an obviously fast/slow pipeline can adjust — but the background, non-blocking rule always holds.

Background ≠ abandoned — the loop is not over until merged.

Handling each outcome

  • A check fails: read --log-failed, fix the root cause, push. Do not re-run jobs hoping for a pass — a red check is unresolved work, and a flaky-looking failure on your own change is usually your change. (See [[general-code-review]] if the failure points at a logic/type defect.)
  • Late comments arrive: review bots (CodeRabbit, linters) and humans often comment 1–3 min after green. Address real findings; reply to or dismiss noise — don't merge over unresolved blocking comments.
  • BEHIND: update the branch from base, which re-triggers CI — back to watching.
  • Can't merge (BLOCKED, missing approval, no permission): that is a genuine human blocker. STOP and name it precisely ("CI green and mergeable; branch protection needs one human approval") — do not report success.

Common rationalizations

RationalizationReality
"PR is open, task done — I'll log off"Open ≠ landed. The watch has barely started.
"Local tests passed, CI will be the same"CI is a different environment; that's the point of CI. Confirm green on CI.
"All 7 checks are green, we're done"Green ≠ merged, and a 30-second-old green can still flip. Hold the green minute, then merge.
"A check went red, just re-run it"Re-run-until-green hides a real failure. Read the log, fix the cause.
"Green now, I can stop watching"Comments and conflicts land after green. Watch until merged.
"I'll report done and mention CI is still running"A status that depends on an unverified future is a false completion claim.
"I'll just --watch in the foreground until it's done"That blocks the session so the user can't prompt. Run it in the background, poll every minute (default 10-min window).

Red flags — STOP

  • About to report the task complete while the PR is open but not merged.
  • About to trust an all-green that has been green for less than a minute.
  • About to re-run a failing check instead of reading its log.
  • About to stop watching at first green instead of at merge.
  • Treating "can't merge, needs approval" as done instead of as a named blocker.
  • Blocking the session with a foreground watch instead of monitoring in the background.

Frequently asked questions

What does the Pr Monitoring AI skill do?

Use after a pull request has been opened and the task is not finished until it lands. Triggers on "PR is open", "CI is running", "is it merged yet", a PR that is green but not merged, fresh CI that might still flip, or being tempted to report a task done at PR-open. GitHub / gh CLI based.

Why use Pr Monitoring on TypingMind?

Because you install it once and use it with any model. Pr Monitoring is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pr Monitoring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lucasfcosta/backpressured/tree/main/skills/pr-monitoring. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pr Monitoring?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pr Monitoring?

As many as you like. As long as a model supports skills, you can use Pr Monitoring with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pr Monitoring AI skill free?

Yes. It is published on GitHub by lucasfcosta under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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