agents-at-scale-ark: Agent for Claude Code

.claude/agents/ark-build-manager.md

ark-build-manager is an agent for Claude Code from mckinsey/agents-at-scale-ark. It costs 0 tokens per session (4,117 once invoked), scanned A, original, Apache-2.0.

A build-triage agent for Ark, a Kubernetes operator for managing AI workloads. It checks the project's continuous integration and delivery system, classifies failures, and directs each problem to the appropriate fix.

In plain words
What is it for?
Use it to investigate failed builds, broken tests, red CI checks, and other Ark build problems, then fix or route them.
Why use it?
It helps identify why builds or tests are failing and keeps unrelated automated workflows from being confused with the main build workflow. CI/CD means automated checks and delivery steps run when code changes.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; mentions CLAUDE.md; names the AskUserQuestion tool.

This is mckinsey/agents-at-scale-ark's own configuration. It tells Claude Code how to work on agents-at-scale-ark itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything agents-at-scale-ark configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is chainsaw test ./tests/<specific-test> --fail-fast.

Reuse

Borrowing it

Nothing to install: this file belongs to mckinsey/agents-at-scale-ark. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/mckinsey/agents-at-scale-ark/main/.claude/agents/ark-build-manager.md
Clone the repo
git clone --depth 1 https://github.com/mckinsey/agents-at-scale-ark

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ark-build-manager

README.md
[![agentmods](https://agentmods.dev/badge/agents/mckinsey/agents-at-scale-ark/ark-build-manager/github.svg)](https://agentmods.dev/agents/mckinsey/agents-at-scale-ark/ark-build-manager)
Your own site
<a href="https://agentmods.dev/agents/mckinsey/agents-at-scale-ark/ark-build-manager"><img src="https://agentmods.dev/badge/agents/mckinsey/agents-at-scale-ark/ark-build-manager/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ark-build-manager

Your own site · 80×15
<a href="https://agentmods.dev/agents/mckinsey/agents-at-scale-ark/ark-build-manager"><img src="https://agentmods.dev/badge/agents/mckinsey/agents-at-scale-ark/ark-build-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,117 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.04117
Opus 5 $0.00000 $0.02058
Sonnet 5 $0.00000 $0.00823
Haiku 4.5 $0.00000 $0.00412

Measured 7d ago against content hash 1ac37c1bb74a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ark-build-manager scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/ark-build-manager.md · 391 lines

How it starts

The opening of the file, as written. The whole thing — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a build and CI/CD specialist agent for the Ark platform. You triage build failures, categorize issues, and either fix them directly or delegate to the appropriate skill.

Your Mission

When the user asks about build issues, complete this workflow:

  1. Assess the current state of CI/CD across the repository
  2. Categorize each failure by type
  3. For each failure, either fix it directly or recommend the appropriate skill/workflow
  4. Report a clear summary with status and next steps

Step 1: Assess Current Build State

Always filter by workflow name. The repo has multiple workflows (CI/CD, Validate PR Title, SonarQube Scan). Only the CI/CD workflow runs builds and tests.

gh run list --repo mckinsey/agents-at-scale-ark --workflow "CI/CD" --limit 20 \
  --json databaseId,displayTitle,headBranch,conclusion,event,createdAt \
  --jq '.[] | "\(.databaseId)\t\(.conclusion)\t\(.headBranch)\t\(.displayTitle)"'

Focus on failures:

gh run list --repo mckinsey/agents-at-scale-ark --workflow "CI/CD" --status failure --limit 10 \
  --json databaseId,displayTitle,headBranch,conclusion,createdAt \
  --jq '.[] | "\(.databaseId)\t\(.headBranch)\t\(.displayTitle)\t\(.createdAt)"'

Check main branch health specifically:

gh run list --repo mckinsey/agents-at-scale-ark --workflow "CI/CD" --branch main --limit 5 \
  --json databaseId,displayTitle,conclusion,createdAt \
  --jq '.[] | "\(.databaseId)\t\(.conclusion)\t\(.displayTitle)"'

Step 2: Get Failure Details

For each failed run, identify which jobs failed:

gh run view <RUN_ID> --repo mckinsey/agents-at-scale-ark \
  --json jobs --jq '.jobs[] | select(.conclusion == "failure") | "\(.name)\t\(.conclusion)"'

Get the failure logs:

gh run view <RUN_ID> --repo mckinsey/agents-at-scale-ark --log-failed 2>&1 | tail -100

Step 3: Categorize Failures

Classify each failure into one of these categories and delegate accordingly:

Category: E2E Test Failures (Chainsaw)

Indicators: E2E Standard, chainsaw in job name, FAIL: chainsaw/ in logs Skill: Use chainsaw skill to debug and fix failing tests Common causes:

  • Timeout issues in LLM-dependent tests
  • CRD schema changes not reflected in test fixtures
  • Mock service configuration drift
  • Antipattern: kubectl wait --for=condition=... crashing with nil accessor error — use chainsaw assert with JMESPath instead (see chainsaw skill Antipatterns section) Antipattern check: When a chainsaw test fails with .status.conditions accessor error: <nil> is of the type <nil>, use the chainsaw skill to replace the kubectl wait command with a chainsaw assert block.

Read the full file on GitHub · 391 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 391 lines · 0 tokens per session scan A 1ac37c1bb74a

Subscribe to this mod's changes

ark-build-manager is an agent published in the GitHub repository mckinsey/agents-at-scale-ark (422 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 4,117 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other agents, from other repositories

cicd-automation-terraform-specialist

Expert Terraform/OpenTofu specialist mastering advanced IaC automation, state management, and enterprise infrastructure patterns. Handles complex module design, multi-cloud deployments, GitOps workflows, policy as code, and CI/CD integration. Covers migration strategies, security best practices, and modern IaC…

wshobson/agents · 83 tokens

nw-platform-architect-reviewer

Use for review and critique tasks - Platform design, CI/CD pipeline, infrastructure, observability, deployment readiness, and production handoff review specialist. Runs on Haiku for cost efficiency.

nWave-ai/nWave · 44 tokens

retrospective

Reflective analyst who extracts learnings through structured retrospective frameworks, diagnosing agent performance, identifying error patterns, and documenting success strategies. Uses Five Whys, timeline analysis, and learning matrices. Use when you need root-cause analysis, atomicity scoring, or to transform…

rjmurillo/ai-agents · 62 tokens

09-Diagnose

Interactive diagnostic agent that guides users through Azure resource health assessment, issue identification, and remediation planning. Approval-first execution, single-resource scope, reports to agent-output/{project}/.

jonathan-vella/apex-accelerator · 40 tokens

debug

Debug your application to find and fix a bug. Systematic root cause analysis through structured phases: assessment, investigation, resolution, and quality assurance.

rjmurillo/ai-agents · 31 tokens

fixer

Reproduce failures and apply targeted fixes.

juliusz-cwiakalski/agentic-delivery-os · 11 tokens