Dd Unblock Pr logo

Dd Unblock Pr

OrganizationPopular
DataDog
dd-unblock-pr

Load when investigating a failing PR CI pipeline or checking PR health. Attributes each CI failure as flaky, infra, or regression, proposes a targeted action, and reports code coverage.

Overview

PublisherDataDog
Repositorypup
Skill namedd-unblock-pr
Stars
1K
Forks
127
Bundled files
Instructions only
LicenseApache-2.0
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 DataDog on GitHub. Read the source before you install it.

Installation

Install the Dd Unblock Pr 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/DataDog/pup/tree/main/skills/dd-unblock-pr
  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/DataDog/pup.git /tmp/pup
mkdir -p .claude/skills
cp -r /tmp/pup/skills/dd-unblock-pr .claude/skills/dd-unblock-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dd Unblock Pr 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 Dd Unblock Pr 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 Dd Unblock Pr 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.

Unblock PR

One-line summary: Investigate a failing PR CI pipeline — attribute each failure as flaky, infra, or regression and propose a targeted action.

Requires: dd-pup skill (pup CLI installed and authenticated), dd-triage-flaky-test skill (for flaky failure deep investigation).


Input

ParameterDescription
PR branchThe branch under investigation (e.g. my-feature-branch)
RepositoryLowercase, no-schema URL (e.g. github.com/org/repo). Derive from git remote get-url origin if not provided.

Workflow

STEP 0 — Parse Input

Derive repository ID and default branch from git if not provided:

bash
# Repository ID: fully lowercase, no-schema URL (the API rejects mixed-case)
git remote get-url origin
# Strip protocol and trailing .git, then lowercase the result
# e.g. https://github.com/DataDog/my-repo.git → github.com/datadog/my-repo

# Default branch
git symbolic-ref refs/remotes/origin/HEAD
# Strip refs/remotes/origin/ prefix — fall back to main if unset

STEP 1 — Get PR CI Summary (run both in parallel)

Pipeline failures (job level):

bash
pup cicd events search \
  --query "@ci.status:error @git.branch:<branch> @git.repository.id_v2:\"<repo>\"" \
  --level job \
  --from 24h \
  --limit 50

Test failures:

bash
pup cicd tests search \
  --query "@test.status:fail @git.branch:<branch> @git.repository.id_v2:\"<repo>\"" \
  --from 24h \
  --limit 50

Run both queries in parallel. Collect all distinct @test.service values from test event results. If more than one distinct service is found, note each separately in the triage brief — do not collapse them into a single service filter. If pipeline results contain only infrastructure job types (build, lint, deploy) with no test-runner output, discard test search results and skip to STEP 3.

STEP 1.5 — Fetch Code Coverage (run in parallel with STEP 1)

This step runs unconditionally — coverage context is valuable whether CI is red or green.

The --repo value must be fully lowercase (the API rejects mixed-case). Normalize before calling:

bash
repo_lower=$(echo "<repo>" | tr '[:upper:]' '[:lower:]')
pup code-coverage branch-summary \
  --repo "$repo_lower" \
  --branch "<branch>"

If the command returns no data or exits with an error, report "No data available" for Coverage in the PR Health section.

Note: Code quality and security violation counts are not available in pup — those lines always show "No data available".

STEP 2 — Blame Guard per Failing Job

First check whether @error_classification.domain / @error_classification.type are present on job events from STEP 1 — if populated, use them as primary classification signals.

For each failing job where classification is still needed, run both checks in parallel:

Default branch check — was this job already failing before this PR?

bash
pup cicd events aggregate \
  --query "@ci.status:error @ci.job.name:\"<job>\" @git.branch:<default-branch> @git.repository.id_v2:\"<repo>\"" \
  --compute count \
  --from 24h

Blast radius check — is this job failing on other branches too?

bash
pup cicd events aggregate \
  --query "@ci.status:error @ci.job.name:\"<job>\" @git.repository.id_v2:\"<repo>\"" \
  --compute count \
  --group-by "@git.branch" \
  --from 24h

Performance fallback: if the blast radius query is slow or times out, skip it and rely on the default branch check alone.

STEP 3 — Classify Each Failure

Priority order:

  1. If @error_classification.domain / @error_classification.type present → use as primary signal
  2. If test failure AND test appears in flaky tests with flaky_test_state:active:
    bash
    pup cicd flaky-tests search \
      --query "flaky_test_state:active @test.name:\"<test-name>\" @git.repository.id_v2:\"<repo>\""
    → flaky
  3. Use blame guard results:
Failing on default branch?Failing on ≥3 other branches?Classification
YesYesinfra (pre-existing, widespread)
YesNoinfra (pre-existing on default branch)
NoNoregression (introduced by this PR)
NoYesflaky (intermittent, cross-branch)
Insufficient data—unknown

STEP 4 — Produce Triage Brief

One entry per failing job:

PR CI Triage Brief
==================
Branch:   <branch>
Repo:     <repo>

Job: <job-name>
  Classification:  <flaky | infra | regression | unknown>
  Evidence:        <1 key data point — error message, pipeline count, or test result>
  Confidence:      <high | medium | low>
  Recommended:     <action>

[repeat for each failing job]

Overall: <N> failures — <e.g. "1 regression, 1 flaky, 1 infra">

PR Health
=========
Coverage:   <X>% on <branch> | No data available
Quality:    No data available
Security:   No data available

All three lines always appear.

STEP 5 — Propose Actions

regression → Prompt user to investigate their code changes. No write action available.

flaky → Load dd-triage-flaky-test skill for deep investigation. That skill will:

  • Attempt an agent-native fix using flaky_category + stack trace
  • Propose quarantine via pup test-optimization flaky-tests update if a quick fix isn't possible

infra → Before proposing a retry, assess whether the failure is transient:

  • Check @error_classification.type and error message for signals like timeout, runner unavailable, network error, quota exceeded — these indicate transient failures where a retry is likely to help
  • If the error is deterministic (build misconfiguration, missing secret, explicit test assertion failure), a retry is unlikely to help — note this and suggest investigating the root cause
  • If the failure is pre-existing on the default branch, inform the user — a retry will likely fail again; await the upstream fix instead

If transient and GitHub Actions: extract the run ID from @ci.pipeline.url (e.g. https://github.com/org/repo/actions/runs/<run_id>):

bash
gh run rerun <run_id> --failed

For other providers, share @ci.pipeline.url and direct to the provider UI for retry.

unknown → Suggest checking raw job logs via the CI provider UI or @ci.pipeline.url from the pipeline event.

Frequently asked questions

What does the Dd Unblock Pr AI skill do?

Load when investigating a failing PR CI pipeline or checking PR health. Attributes each CI failure as flaky, infra, or regression, proposes a targeted action, and reports code coverage.

Why use Dd Unblock Pr on TypingMind?

Because you install it once and use it with any model. Dd Unblock Pr 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 Dd Unblock Pr in TypingMind?

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

Which AI models can use Dd Unblock Pr?

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 Dd Unblock Pr?

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

Is the Dd Unblock Pr AI skill free?

Yes. It is published on GitHub by DataDog under the Apache-2.0 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇