MCPInstall

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 and quality/security status.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/datadog-labs/agent-skills --skill unblock-pr
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads unblock-pr automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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), triage-flaky-test skill (for flaky failure deep investigation).


Backend

Detection — At the start of every invocation, before taking any action, determine which backend to use:

  1. If the user passed --backend pup anywhere → use pup mode immediately. Skip steps 2–4.
  2. Check whether search_datadog_ci_pipeline_events appears in your available tools.
  3. If present → use MCP mode throughout. Call tools exactly as named in this skill's workflow sections.
  4. If absent → check whether pup is executable: run pup --version via Bash. If the command exits successfully (exit code 0), pup is available.
  5. If pup responds → use pup mode throughout. Translate every tool call using the Tool Reference appendix at the bottom of this file.
  6. If neither is available → stop and tell the user:

    "Neither the Datadog MCP server nor the pup CLI is available. Connect the MCP server or install pup (brew install datadog-labs/pack/pup)."

pup invocation rules:

  • Invoke via Bash. pup always outputs JSON — parse directly.
  • Repository IDs passed to pup must be fully lowercase (the API rejects mixed-case): github.com/datadog/my-repo, not github.com/DataDog/my-repo.
  • If pup returns a 401/403, tell the user to run pup auth refresh or pup auth login.

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:

# 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 in parallel)

Pipeline failures:

Tool: search_datadog_ci_pipeline_events
query: @ci.status:error @git.branch:<branch> @git.repository.id_v2:"<repo>"
ci_level: job
from: now-24h

Test failures (only if pipeline results include test-runner jobs):

Tool: search_datadog_test_events
query: @test.status:fail @git.branch:<branch> @git.repository.id_v2:"<repo>"
from: now-24h
test_level: test

Run both 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 results and skip to STEP 3.

STEP 1.5 — Fetch PR Health (run in parallel with STEP 1)

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

Code coverage (both modes):

Tool: get_datadog_code_coverage_branch_summary
repository_id: <repo>
branch: <branch>

PR number resolution (MCP mode only — skip if PR number already provided as input):

Tool: get_prs_by_head_branch
repo_url: https://<repo>
head_branch: <branch>

Use the first open PR returned. If no open PR is found, skip the quality/security fetch and report "No data available" for Quality and Security.

Code quality and security (MCP mode only — only if PR number is available):

Tool: search_pr_insights
repo_url: https://<repo>
pr_number: <pr_number>

Extract only code_quality and code_security from products_status. Ignore failed_tests, flaky_tests, and failed_jobs — CI data comes from STEP 1–3.

pup mode note: PR number resolution and search_pr_insights are not available in pup. Quality and Security always show "No data available" in pup mode.

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?

Tool: aggregate_datadog_ci_pipeline_events
query: @ci.status:error @ci.job.name:"<job>" @git.branch:<default-branch> @git.repository.id_v2:"<repo>"
ci_level: job
aggregation: count
from: now-24h

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

Tool: aggregate_datadog_ci_pipeline_events
query: @ci.status:error @ci.job.name:"<job>" @git.repository.id_v2:"<repo>"
ci_level: job
aggregation: count
group_by: ["@git.branch"]
from: now-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 in get_datadog_flaky_tests with flaky_test_state:active → 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:    <N violations (X high, Y medium)> | No violations | No data available
Security:   <N violations> | No violations | No data available

All three lines always appear. Use "No data available" when a tool returned no data or is unavailable (pup mode for Quality/Security).

STEP 5 — Propose Actions

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

flaky → Load triage-flaky-test skill for deep investigation. Invoke it once per distinct failing test name classified as flaky, passing the test name (from @test.name in STEP 1 results) and the derived repository as inputs. That skill will:

  • Attempt an agent-native fix using flaky_category + stack trace
  • Propose quarantine via update_datadog_flaky_test_states 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 — 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 — 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:

MCP mode — GitHub Actions: use retry_datadog_ci_job. From the failing job event, collect:

  • @ci.provider.name → ci_provider ("github")
  • @git.repository.id_v2 → repository_id
  • @ci.job.id → job_id
  • event id field → event_uuid (optional)

For pipeline_id: use @ci.pipeline.id directly if it matches ^\d+-[1-9]\d*$ (e.g. 26027867390-1). If it is a bare numeric run ID, combine it with @github.run_attempt from the same event: "{@ci.pipeline.id}-{@github.run_attempt}". Fallback: parse @ci.pipeline.url — extract {run_id} and {attempt} from runs/{run_id}/attempts/{attempt}.

After retry returns, confirm via search_datadog_ci_pipeline_events (query: @ci.job.name:"<job>" @git.branch:<branch>, from: now-5m) that a new run appears.

Fallback / pup mode — GitHub Actions: extract the run ID from @ci.pipeline.url:

gh run rerun <run_id> --failed

GitLab / other providers (both modes): share @ci.pipeline.url and direct to the provider UI.

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


Tool Reference

This appendix applies only in pup mode. In MCP mode, use the tool names in the workflow sections directly.

MCP Toolpup Command
search_datadog_ci_pipeline_events (ci_level: job)pup cicd events search --query "..." --level job --from 24h --limit 50
aggregate_datadog_ci_pipeline_events (count, group_by branch)pup cicd events aggregate --query "..." --compute count --group-by "@git.branch" --from 24h
aggregate_datadog_ci_pipeline_events (count, no group_by)pup cicd events aggregate --query "..." --compute count --from 24h
search_datadog_test_eventspup cicd tests search --query "..." --from 24h --limit 50
get_datadog_flaky_testspup cicd flaky-tests search --query "flaky_test_state:active ..."
update_datadog_flaky_test_statesWrite body to /tmp/flaky-update.json, then pup test-optimization flaky-tests update --file /tmp/flaky-update.json
get_datadog_code_coverage_branch_summaryrepo_lower=$(echo "<repo>" | tr '[:upper:]' '[:lower:]') && pup code-coverage branch-summary --repo "$repo_lower" --branch "<branch>"
get_prs_by_head_branchNot available in pup — skip; report "No data available" for Quality/Security
search_pr_insightsNot available in pup — skip; report "No data available" for Quality/Security
retry_datadog_ci_jobNot available in pup — use gh run rerun <run_id> --failed instead

FAQ

What does the unblock-pr 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 and quality/security status.

How do I install unblock-pr?

Run npx skills add https://github.com/datadog-labs/agent-skills --skill unblock-pr in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/unblock-pr/ (personal) or .claude/skills/unblock-pr/ (project).

Which AI agents can use unblock-pr?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is unblock-pr safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains unblock-pr?

It is published by datadog-labs in datadog-labs/agent-skills. It has 254 recorded installs.

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