Triage Flaky Test

One-line summary: Investigate a specific flaky test — get history, failure pattern, and category, then recommend fix, quarantine, or escalate.

Requires: Datadog MCP tools, or the dd-pup skill with pup installed and authenticated.

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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 get_datadog_flaky_tests 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 with JSON output (pup --output json ...) and parse the response.
• Repository IDs passed to pup must be fully lowercase (the API rejects mixed-case).
• Sort values starting with - require = syntax: --sort="-last_flaked" (not --sort "-last_flaked").
• If pup returns a 401/403, tell the user to run pup auth refresh or pup auth login.

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Input

Parameter	Description
Test name	Fully qualified test name (e.g. TestMyFunc or com.example.MyTest)
Repository	Lowercase, no-schema URL (e.g. github.com/org/repo). Derive from git remote get-url origin if not provided.

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Workflow

STEP 0 — Parse Input

Derive repository ID from git if not provided:

git remote get-url origin
# Strip protocol and trailing .git, normalize SSH git@host:org/repo to host/org/repo, then lowercase
# e.g. https://github.com/DataDog/my-repo.git → github.com/datadog/my-repo

Validation fallback: If STEP 1 returns no results, confirm the correct repository by searching without a repo filter:

Tool: search_datadog_test_events
query: @test.name:"<test-name>"
from: now-30d
test_level: test

Extract @git.repository.id_v2 from results and retry STEP 1 with the confirmed value.

STEP 1 — Get Flaky Test Details

Preferred — use fingerprint_fqn if known (fingerprint_fqn is a valid CI Visibility search facet):

Tool: get_datadog_flaky_tests
query: fingerprint_fqn:<fqn>
sort_field: last_flaked
sort_order: desc

Fallback — use name + suite + repo:

Tool: get_datadog_flaky_tests
query: @test.name:"<test-name>" @test.suite:"<suite>" @git.repository.id_v2:"<repo>"
sort_field: last_flaked
sort_order: desc

Omit @test.suite if unknown. If multiple suites or modules match, resolve the test identity from the failing event before continuing; add @test.module when needed to distinguish them. Do not filter by flaky_test_state — return the test regardless of state.

Note: the query filter facet is flaky_test_state; the returned response attribute is flaky_state — do not use flaky_state:active as a query filter.

Extract from results:

• fingerprint_fqn — unique test identifier; used as the id in STEP 5 write call. If absent, do not proceed to quarantine — see STEP 5.
• flaky_state — current state (active / quarantined / disabled / fixed)
• test_stats.failure_rate_pct — percentage of runs that fail
• flaky_category — root cause category
• codeowners — owning team
• pipeline_stats.total_lost_time_ms — total CI time lost in milliseconds
• attempt_to_fix_id — non-empty when a Bits Code fix has been generated
• web_url — datacenter-correct FTM link, when supplied by the backend

pup mode response mapping: Pup returns raw JSON:API records: read fields from data[].attributes and use the matching record’s data[].id as fingerprint_fqn if it is not repeated in attributes. The MCP enriches responses with fingerprint_fqn and web_url; pup may not return web_url. Keep the ID tied to the confirmed test’s module, suite, name, and repository. If no link is supplied, use the FTM UI on the configured Datadog site; do not assume a US1 hostname.

STEP 2 — Get Recent Failure History

Tool: search_datadog_test_events
query: @test.name:"<test-name>" @test.suite:"<suite>" @test.status:fail @git.repository.id_v2:"<repo>"
from: now-7d
test_level: test

Extract:

• Error messages and stack traces (@error.message, @error.stack)
• Failing branches (@git.branch) — branch-specific vs. widespread
• Frequency pattern — random timing or specific conditions
• Unique @ci.pipeline.id values for blast radius (STEP 3)

Reading stack traces: Read error chains from bottom to top. Chained errors hide the real cause — the innermost error at the bottom is the root cause, not the first line. If the identified root cause would cause near-100% failure but the actual flake rate is much lower, the root cause identification is wrong — look deeper.

STEP 2.5 — Determine Attribution

Decide whether this flake was introduced by the current working change (self-introduced) or is a pre-existing, inherited flake. This drives the fix-vs-quarantine steer in STEP 4/5 — you should not suppress a flake you just introduced.

Failure history takes precedence. If STEP 2 shows the test failing on the default branch, or failing across multiple unrelated branches (not just the current one), the flake pre-dates the current change — classify it pre-existing even if the current diff touches the test or nearby code, and even if the user claims ownership. Diff overlap or an author editing nearby code does not make an already-widespread flake self-introduced. Apply the signals below only when this pre-existing failure history is absent.

A flake is self-introduced when any signal holds (and the failure history above has not already classified it pre-existing):

1. Diff overlap (primary) — the current branch's changes touch the failing test's file, or a changed non-test file that plausibly feeds the failing code path. First confirm the local checkout is the repository under investigation: normalize git remote get-url origin (lowercase, strip scheme and trailing .git, and convert SSH remotes such as git@github.com:org/repo.git to github.com/org/repo) and check it equals the <repo> from STEP 0. If it does not match (or there is no git remote / no shell access), skip this signal entirely — diffing an unrelated local checkout would attribute the wrong repo's changes. Also confirm the checked-out branch/commit is the change under investigation; otherwise skip the local diff signal. Only when both match, derive the comparison base from the repository's default branch:

   git diff --name-only $(git merge-base origin/<default-branch> HEAD)...HEAD
   

   Derive <default-branch> from git symbolic-ref refs/remotes/origin/HEAD (strip the refs/remotes/origin/ prefix); fall back to main if unset. Then judge overlap using the stack trace and error evidence already gathered in STEP 2 — the test file appearing in the diff is a direct match; a changed source file named in the stack trace is an indirect match.
2. Branch-locality (secondary) — the failing branches from STEP 2 (@git.branch) are limited to the current branch and the test is not failing on the default branch. A truncated result page is not evidence of branch-locality: check the default branch and other branches for this test before relying on this signal; if that history is unavailable, treat branch-locality as inconclusive.
3. Stated ownership — the user says they just added, wrote, touched, or introduced the test (or the code it exercises) in their current change / PR / branch / commit. Take this at face value as a self-introduced signal on its own; it does not require corroboration from signals 1–2, and it applies even when the local diff cannot be inspected (no shell / git access) or branch history is inconclusive. Only discount it if the gathered data flatly contradicts it (e.g. the test has been failing on the default branch for weeks).

Record attribution as one of:

• pre-existing — the test fails on the default branch or across multiple unrelated branches (this takes precedence over the signals above).
• self-introduced — no pre-existing failure history, and any signal above holds.
• undetermined — no pre-existing failure history and none of the signals is available: the diff cannot be inspected, branch-locality is inconclusive, and the user has not stated ownership. Fall back to the default fix/quarantine behavior in STEP 4/5.

STEP 3 — Check Blast Radius

Primary method: Extract unique @ci.pipeline.id values from STEP 2 results and count distinct pipelines impacted.

Fallback (if > 10 unique pipeline IDs): Use the pipeline IDs already collected from STEP 2 and aggregate by name for supporting impact context — keeping the query scoped to pipelines that actually ran this test:

Tool: aggregate_datadog_ci_pipeline_events
query: @ci.status:error @ci.pipeline.id:(<id1> OR <id2> OR ...) @git.repository.id_v2:"<repo>"
ci_level: pipeline
aggregation: count
group_by: ["@ci.pipeline.name"]
from: now-7d

Use at most the first 20 unique IDs in the fallback query. Keep the distinct-ID count from STEP 2 as the primary count; grouped event counts are supporting evidence and must not be inflated by duplicate events. If STEP 2 was truncated, label the count as a lower bound.

Report blast radius as: number of unique pipelines impacted and whether failures are branch-specific or widespread.

Note: Blast radius is an approximation. A pipeline failure is not necessarily caused by this specific flaky test — the test may have failed in the same pipeline run that already had other unrelated failures. Treat blast radius as a signal, not a definitive count of pipelines blocked by this test.

STEP 4 — Attempt Fix

Infrastructure guard — check this before either branch below, including when attempt_to_fix_id is present. Using the evidence gathered in STEP 2, determine whether the root cause is a fault in the CI/build environment or tooling itself (an unavailable daemon, a testcontainer that never starts, a missing/mis-architected binary, a network dependency down in CI). This is narrower than "not the test's own code" — a genuine bug in production code or a shared test helper is a code fault, not infrastructure, even though it also lives outside the test itself; guard 4 already routes that to a fix at the correct layer, and this guard must not override it. An existing Bits Code fix does not clear this guard: its presence means a fix was generated, not that the observed failure is a code issue.

If the root cause is infrastructure, jump to STEP 5.B when producing the recommendation — never fix, regardless of category or failure rate. Otherwise, use the normal path, STEP 5.A.

For an infrastructure root cause, you may still surface the Bits Code link or a suggested infra remediation, but only via the AI Fix / Infra Fix lines in the STEP 5 brief — never as the Recommendation.

If attempt_to_fix_id is present (Bits Code fix available):

An AI-generated fix already exists for this test. Surface it using web_url from STEP 1. If that link is unavailable, tell the user to open Flaky Test Management on their configured Datadog site and locate the confirmed test; do not invent a URL or discard the available fix. Use the link below only when it was returned:

AI Fix Available: [View fix in Flaky Test Management](<web_url>)

A Bits Code fix has been generated for this test. Open the link above to view and apply
the proposed diff. If you'd prefer an inline agent-native fix attempt instead, say so.

After applying the fix, include the test key in your commit message so Datadog validates the fix:
  git commit -m "fix: <description>

  DD_<attempt_to_fix_id>"

Substitute <attempt_to_fix_id> with the value extracted in STEP 1.

If the infrastructure guard above did not trigger, skip the agent-native fix attempt and proceed to STEP 5.A with recommendation: fix and confidence: medium. If the guard did trigger, still show the "AI Fix Available" block above as informational context, but use STEP 5.B instead — never fix, regardless of the Bits Code fix's presence.

If attempt_to_fix_id is absent (V1 agent-native):

Use flaky_category from STEP 1 and the stack trace and error message from STEP 2 to propose a targeted fix.

Load references/fix-patterns.md for the full category-to-fix mapping.

Before proposing any code change, verify all of the following. If ANY fails → emit NO code changes and apply the attribution-aware fallback in the Decision block below (do NOT assume quarantine — for a self-introduced flake the fallback is escalate):

1. The failure is a code problem, not a CI infrastructure problem (Docker daemon down, testcontainer startup failure, network unavailable in CI — these cannot be fixed in test code).
2. The root cause is the innermost error in the chain, not a surface symptom. If the identified root cause would cause near-100% failures but the actual flake rate is much lower, the root cause identification is wrong.
3. The fix eliminates the root cause, not just reduces probability. Blind timing hacks (sleeps, or widening timeouts when the root cause is not a too-tight deadline) and relaxed assertions (exact → at_least) are invalid even if they lower the flake rate.
4. The fix targets the correct layer: test issues in test/helper code, production bugs in production code. Never patch one test callsite when the root cause is in shared code — update all callsites.

Guard 1 is the infrastructure guard from the top of STEP 4, not a "fix the infra instead" branch. When it fails, do not propose the infra remediation (rebuilding a binary, retagging a runner, restarting a service) as recommendation: fix — that remediation is not a pre-flight check failure to route around, it IS the guard-1 failure. Use STEP 5.B, not STEP 5.A — STEP 5.A's low-failure-rate/known-category rule can still select fix, which is specifically excluded once guard 1 has failed.

Decision:

• If category is known AND pre-flight passes AND error message confirms the root cause → apply the fix pattern from references/fix-patterns.md and propose specific code changes
• If category is unknown → the root cause cannot be confirmed from available signal; emit NO code changes and go to STEP 5.A
• If any pre-flight check fails → emit NO code changes and go to STEP 5.A (guards 2-4) or STEP 5.B (guard 1 — an infrastructure root cause)

Attribution overrides the no-fix fallback (from STEP 2.5):

• When attribution is self-introduced, fix is the strongly preferred outcome — you should not suppress a flake introduced by the current change. Still respect the pre-flight guards above: a self-introduced flake only gets a code change if the guards pass. If a safe fix cannot be made (category unknown or a guard fails), go to STEP 5 with recommendation: escalate to the author (the current change owns it; this applies whether or not guard 1 was the guard that failed). Do not default to quarantine for a self-introduced flake; quarantine is only a last resort if the user explicitly insists (see the warning in STEP 5).
• When attribution is pre-existing or undetermined, use STEP 5.A's thresholds: unknown categories may escalate, while failed code-fix guards may require quarantine — except when guard 1 (the infrastructure guard) failed, in which case use STEP 5.B instead. If undetermined, the Attribution: line in the STEP 5 brief must still read undetermined so the user can see the self-introduced check was inconclusive — do not present the quarantine as if attribution were confidently pre-existing.

After proposing the code change, provide commit message guidance:

To link the fix to Datadog's validation system, include the test key in your commit message:
  git commit -m "fix: <description>

  DD_<attempt_to_fix_id or fingerprint_fqn>"

Substitute the test key with attempt_to_fix_id from STEP 1 when non-empty, otherwise fall back to the confirmed fingerprint_fqn from STEP 1. If neither is available, omit the validation tag rather than inventing one.

STEP 5 — Recommend Action and Produce Triage Brief

Produce a triage brief in this exact format:

Flaky Test Triage Brief
=======================
Test:           <fully qualified test name>
Service:        <@test.service>
Category:       <flaky_category>
Failure Rate:   <test_stats.failure_rate_pct>%
Duration Lost:  <pipeline_stats.total_lost_time_ms ms>
Codeowners:     <codeowners>
Blast Radius:   <N> pipelines (<branch-specific | widespread>; approximate)
Attribution:    <self-introduced | pre-existing | undetermined>

Evidence:
  <1-2 key error message lines from STEP 2 results>
Infra Fix:      <non-blocking infra/build remediation if guard 1 failed on a CI-infra root cause, e.g. "rebuild the test binary for the runner architecture" | N/A>
AI Fix:         <web_url or FTM lookup instructions if attempt_to_fix_id present | N/A>

Recommendation: <fix | quarantine | escalate>
Confidence:     <high | medium | low>
Action:         <specific next step>

STEP 5.A — Decision thresholds (default path). Use this unless the STEP 4 infrastructure guard failed — in that case use STEP 5.B instead.

• Attribution self-introduced takes priority over every rule below and in STEP 5.B — follow the STEP 4 routing: prefer fix; if no safe fix can be made, escalate to the author. Do not recommend quarantine for a self-introduced flake; fall back to quarantine only if the user explicitly insists after seeing the warning below.
• If a Bits Code fix is available and the infrastructure guard passed, use the STEP 4 handoff: fix, confidence medium, without claiming the proposed diff is validated.
• test_stats.failure_rate_pct > 10 OR blast radius > 5 pipelines → quarantine (suppress failures while fix is prepared)
• test_stats.failure_rate_pct ≤ 10 AND category is known AND fix is clear → fix (propose code change from STEP 4)
• test_stats.failure_rate_pct ≤ 10 AND category is unknown → escalate to codeowners with triage brief context
• If the category is known but guards 2–4 prevent a safe fix, follow STEP 4’s no-fix fallback: quarantine for pre-existing / undetermined. Missing statistics are not zero; report the missing evidence and escalate when no preceding rule applies.

STEP 5.B — Infrastructure guard routing. Use this instead of STEP 5.A when the STEP 4 infrastructure guard failed. fix is never a valid outcome here, regardless of category or failure rate.

• self-introduced attribution → escalate to the author (per the priority rule in STEP 5.A).
• Otherwise → quarantine if test_stats.failure_rate_pct > 10 OR blast radius > 5 pipelines, else escalate to codeowners.

If recommending quarantine, present and require explicit user approval before writing:

If the user explicitly insists on quarantining a self-introduced flake (against the fix/escalate recommendation above), prepend this warning before the approval block:

⚠️ This flake appears to be introduced by your current change (<attribution reason — e.g. your branch adds/edits <file>, it fails only on <branch>, or you stated you just added it>).
Quarantining suppresses a failure you just introduced and lets a known-bad test merge.
Recommended: fix it instead.

Proposed action: quarantine "<test-name>"
  id (fingerprint_fqn): <fingerprint_fqn from STEP 1>
  Effect: test still runs but failures are suppressed (CI will not be blocked)
  Reversible: yes — set new_state: active to restore

Approve? (yes/no)

If fingerprint_fqn was not returned in STEP 1 (test not yet in FTM or query returned no results): do not attempt the write. Surface an error and ask the user to open the Flaky Test Management UI directly to quarantine manually.

Only after explicit approval and a confirmed fingerprint_fqn:

MCP mode:

Tool: update_datadog_flaky_test_states
test_ids: ["<fingerprint_fqn>"]
new_state: quarantined

pup mode:

cat > /tmp/flaky-update.json <<'EOF'
{
  "data": {
    "type": "UpdateFlakyTestsRequest",
    "attributes": {
      "tests": [{"id": "<fingerprint_fqn>", "new_state": "quarantined"}]
    }
  }
}
EOF
pup test-optimization flaky-tests update --file /tmp/flaky-update.json

To undo: repeat with new_state: active / "new_state": "active".

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Tool Reference

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

MCP Tool	pup Command
get_datadog_flaky_tests (by fingerprint_fqn)	pup cicd flaky-tests search --query "fingerprint_fqn:<fqn>" --sort="-last_flaked" --limit 5
get_datadog_flaky_tests (by name + suite + repo)	pup cicd flaky-tests search --query "@test.name:\"...\" @test.suite:\"...\" @git.repository.id_v2:\"...\"" --sort="-last_flaked" --limit 10
search_datadog_test_events (validation fallback)	pup cicd tests search --query "test_level:test @test.name:\"<test-name>\"" --from 30d --limit 5
search_datadog_test_events (failure history)	pup cicd tests search --query "test_level:test @test.name:\"...\" @test.suite:\"...\" @test.status:fail @git.repository.id_v2:\"...\"" --from 7d --limit 20
aggregate_datadog_ci_pipeline_events (blast radius)	pup cicd events aggregate --query "ci_level:pipeline @ci.status:error @ci.pipeline.id:(...) @git.repository.id_v2:\"...\"" --compute count --group-by "@ci.pipeline.name" --from 7d
update_datadog_flaky_test_states	Write body to /tmp/flaky-update.json, then pup test-optimization flaky-tests update --file /tmp/flaky-update.json

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References

• Fix patterns: category-specific fixes and forbidden workarounds; apply the attribution and infrastructure routing in STEP 4/5.