Skip to content
Datadog Triage Flaky Test

Datadog Triage Flaky TestSkill

Added to Onei
1 views
v1.0.0
MIT
Repository Docs

Summary

Official Datadog skill for investigating one flaky test — pulls its history and failure pattern, categorises the root cause and recommends fixing, quarantining or escalating.

Features

  • Pulls per-test flake history, failure pattern and blast radius
  • Categorises the flake's root cause rather than labelling it 'flaky'
  • Recommends fix, quarantine or escalate with the evidence attached
  • Auto-detects Datadog MCP server or pup CLI with a translation appendix
  • Documents the lowercase-repo-ID and --sort="-field" quoting traps
  • Designed as the deep-dive path from the unblock-pr skill

Install This Skill

Add this skill to your favorite AI agent in a few steps.

Any AI agent

This skill is plain instructions — it works with any assistant that accepts custom instructions or system prompts.

  1. Copy the skill content with the button below.
  2. Paste it into your agent's instruction file or system prompt (for example AGENTS.md, .cursorrules, or a custom instructions field).
  3. Ask the agent to apply the skill whenever the task matches.

Skill Content

Markdown Content

Copy this content and use it with your preferred AI agent

---
name: triage-flaky-test
description: Load when investigating a specific flaky test. Gets history, failure pattern, and category, then recommends fix, quarantine, or escalate.
metadata:
  version: "1.0.0"
  author: datadog-labs
  repository: https://github.com/datadog-labs/agent-skills
  tags: datadog,ci,cicd,flaky,flaky-tests,test-optimization
  alwaysApply: "false"
---

# Triage Flaky Test

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

Requires: `dd-pup` skill (pup CLI installed and authenticated).

---

## 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. pup always outputs JSON — parse directly.
- 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`.

---

## 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. |

---

## Workflow

### STEP 0 — Parse Input

Derive repository ID from git if not provided:
```bash
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
```

**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. 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

### 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)

### STEP 3 — Check Blast Radius

Count distinct pipelines impacted using pipeline IDs from STEP 2:

```
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 the first 10 pipeline IDs from STEP 2 (cap at 10; if more are available, run a second batch and merge results by summing counts per `@ci.pipeline.name` across batches). Report blast radius as: total number of unique pipelines impacted and whether failures are branch-specific or widespread.

Note: a pipeline failure is not necessarily caused solely by this flaky test — treat blast radius as a signal, not a definitive count.

### STEP 4 — Recommend Fix or Quarantine

Use `flaky_category` from STEP 1 and error messages from STEP 2.

**Root cause first:**
- Read the full error trace from bottom to top — chained errors hide the real cause; the innermost error is the root cause, not the first line.
- Identify the exact source of nondeterminism (race, ordering, stale state, timing).
- If the root cause is a CI infrastructure problem (runner unavailable, Docker daemon failure, network outage) → do NOT propose a code fix; classify as `infra` and recommend retry instead.
- If root cause is uncertain and cannot be confirmed from the stack trace → skip fix, go to quarantine.

**Fix at the correct layer:**
- Test issue → fix in test or test helper only.
- Production bug exposed by the test → fix in production code.
- Shared helper used by multiple tests → fix the helper AND update all call sites.

**Forbidden — do not propose these:**
- Timing hacks: increasing timeouts, adding sleeps, widening time windows, adding retries.
- Masking: relaxing assertions (e.g., exact match → at least 1), dropping validations.
- Partial fixes: touching one call site when multiple share the root cause.

**Fix patterns by category:**

| Category | Approach |
|---|---|
| `timeout` | Identify the slow operation and make it synchronous or deterministic — do NOT simply raise the timeout constant |
| `concurrency` | Add deterministic synchronization (barriers, channels, locks); remove shared mutable state between tests |
| `network` | Mock or stub network calls at the boundary; if the test requires a real connection, isolate it with a test server |
| `time` | Inject a controllable clock; replace wall-clock assertions with relative or event-driven checks |
| `order_dependency` | Isolate test state with setup/teardown; eliminate dependencies on execution order or global state |
| `environment_dependency` | Mock env variables and external config; use test-local fixtures, not shared directories or singletons |
| `resource_leak` | Ensure every resource opened in a test is closed in teardown; use cleanup hooks that run even on failure |
| `randomness` | Fix the random seed for the test run; use deterministic inputs instead of random generation |
| `asynchronous_wait` | Replace fixed sleeps with condition polling or event/signal-driven waits with a hard timeout |
| `io` | Use temp files/dirs cleaned up in teardown; mock or stub filesystem interactions |
| `unknown` | Skip fix attempt → go to quarantine |

**Before proposing code changes, verify all of the following — if any fails, skip fix and recommend quarantine:**
- The root cause is the innermost error in the trace, not a surface-level symptom.
- The failure is a code problem, not a CI infrastructure problem.
- The fix eliminates the root cause (not just reduces flake probability).
- The fix is at the correct layer (test vs. production vs. shared helper).
- All call sites of any shared code are updated.
- No timing hacks or relaxed assertions introduced.

**Decision:**
- If category is `unknown` OR verification above fails → skip fix, recommend quarantine
- If category is known AND root cause is confirmed AND fix is valid → propose specific code change

### STEP 5 — Produce Triage Brief and Act

```
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 — other failures in the same pipeline runs may not be related]

Evidence:
  <1-2 key error message lines from STEP 2>

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

**Decision thresholds:**
- `failure_rate_pct > 10` OR blast radius > 5 pipelines → **quarantine**
- `failure_rate_pct ≤ 10` AND known category AND clear fix → **fix**
- `failure_rate_pct ≤ 10` AND category `unknown` → **escalate** to codeowners with triage brief

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

```
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:**
```bash
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"`.

---

## 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.name:\"<test-name>\"" --from 30d --limit 5` |
| `search_datadog_test_events` (failure history) | `pup cicd tests search --query "@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.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` |

Description

"That test is just flaky" is where most investigations stop. This official Datadog skill is built to go one step further on a single named test: pull its failure history, establish the pattern and blast radius, put the flake into a root-cause category, and then make a call — fix it, quarantine it, or escalate it to the owning team.

What it does

Given a fully qualified test name, it queries Datadog Test Optimization for how often and when the test has flaked, what changed around those runs, and how much of the suite the flake is holding up. The output is a recommendation with the evidence attached, which is what makes the quarantine decision defensible rather than a shrug.

Two backends, detected automatically

Like the rest of Datadog's software-delivery skills, it checks for an explicit --backend pup flag, then for the MCP server's get_datadog_flaky_tests tool, then for a working pup binary, and uses whichever it finds throughout. A Tool Reference appendix maps every MCP call to its pup equivalent. With neither available it stops and tells you to connect the MCP server or brew install datadog-labs/pack/pup.

The details that bite

Repository IDs must be passed to pup fully lowercase — the API rejects mixed case. Sort values that begin with a hyphen need = syntax, so --sort="-last_flaked" rather than --sort "-last_flaked", a shell-quoting trap that otherwise produces a confusing argument error. A 401 or 403 means the pup token expired and needs pup auth refresh.

Fits with

Requires the dd-pup skill for the CLI, and is the deep-dive that unblock-pr calls into once it has classified a failure as flaky. For teams with CI Visibility and Test Optimization already reporting, it turns flake triage from a judgement call into a documented one. MIT licensed.

Related Skills

New

Railway's official agent skill: create projects, provision databases and buckets, deploy, manage variables and domains, and read build failures back — from the CLI, API or MCP server.

2 views

Diagnoses wrong gradients in differentiable NVIDIA Warp programs by measuring first — comparing autodiff against finite differences on a shrunk reproduction before proposing any fix.

6 views
New

Google's official skill for the gws CLI — drive Gmail, Drive, Calendar, Sheets, Docs, Chat and Admin APIs from an agent, with Model Armor screening.

6 views 1 copies
New

Netlify's official skill for zero-config managed Postgres — querying from Functions, Drizzle setup, migrations and per-preview database branches.

4 views
Browse all skills →