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.
curl -O https://raw.githubusercontent.com/mckinsey/agents-at-scale-ark/main/.claude/skills/analysis/SKILL.mdgit clone --depth 1 https://github.com/mckinsey/agents-at-scale-arkWrote 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.
[](https://agentmods.dev/skills/mckinsey/agents-at-scale-ark/analysis)<a href="https://agentmods.dev/skills/mckinsey/agents-at-scale-ark/analysis"><img src="https://agentmods.dev/badge/skills/mckinsey/agents-at-scale-ark/analysis.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 81 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 81 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 81 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.00816 |
| Opus 5 | $0.00023 | $0.00408 |
| Sonnet 5 | $0.00009 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade C, and why
Ark Analysis scanned grade C with 1 finding 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 4d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
5. **Clean up**: Optionally remove the temp directory when done: `rm -rf /tmp/ark-analysis` How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ark Analysis
This skill helps you analyze the Ark codebase by cloning the repository and examining its contents.
When to use this skill
Use this skill when:
- User asks "how does X work in Ark?"
- User wants to understand Ark's architecture or implementation
- User needs to examine Ark source code, CRDs, or controllers
- User mentions analyzing the Ark repository
Quick start
Clone the Ark repository to a temporary location:
git clone [email protected]:mckinsey/agents-at-scale-ark.git /tmp/ark-analysis
cd /tmp/ark-analysis
Codebase structure
The Ark repository is organized as follows:
-
ark/- Kubernetes operator and default executor (Go)- Controller dispatches queries to executors via A2A protocol
- CRDs: Agent, Model, Query, Team, MCPServer, ExecutionEngine, A2AServer
executors/completions/- Built-in default execution engine
-
lib/ark-sdk/- Python SDK (generated + overlay)BaseExecutorABC andExecutorAppfor pluggable executor interface
-
services/- Component servicesark-api/- REST API gateway (Python/FastAPI)ark-broker/- In-memory event bus (Node.js/Express)ark-dashboard/- Web UI (Next.js/React)
-
samples/- Example YAML configurations -
docs/- Documentation site (Next.js/MDX)
Common analysis tasks
Find controllers
ls ark/internal/controller/
grep -r "Reconcile" ark/internal/controller/
Find CRDs
ls ark/config/crd/bases/
grep -r "kind: Agent" samples/
Find A2A implementations
find . -path "*/a2a*" -type f
grep -r "A2AServer" .
Search for specific features
# Use ripgrep or grep to search
rg "query controller" --type go
grep -r "team coordination" --include="*.go"
Best practices
- Clone to /tmp: Always clone to
/tmp/ark-analysisto avoid cluttering the workspace - Navigate first:
cd /tmp/ark-analysisbefore running analysis commands - Use search tools: Prefer
rg(ripgrep) orgrepfor code searches - Check CLAUDE.md: Look for project-specific guidance in
CLAUDE.mdfiles - Clean up: Optionally remove the temp directory when done:
rm -rf /tmp/ark-analysis
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.
- 4d ago First seen · 107 lines · 45 tokens per session scan C 3338cf031fbf
Ark Analysis is a skill published in the GitHub repository mckinsey/agents-at-scale-ark (422 stars, last pushed today), licensed Apache-2.0. It adds 45 tokens to every session and 816 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
container-manager-kubernetes-operations
Full operational Kubernetes surface via the container-manager-mcp MCP server — workloads (pods/rollouts/StatefulSets/DaemonSets/ReplicaSets/Jobs/CronJobs), config (ConfigMaps/Secrets/Namespaces/CRDs/patch), networking (Ingress/native Services/NetworkPolicy/DNS), storage (PV/PVC/StorageClass/snapshots/CSI), RBAC…
k8s-ops
Opinionated multi-step Kubernetes workflows on top of the k8s-mcp server. Encodes tool-sequencing logic and failure-mode decision trees for deploying from a repo, debugging pods/rollouts, performing safe restarts, and auditing cluster posture. Use when the user asks to deploy, diagnose, restart, roll out, or audit…
kubernetes-mesh-provisioner
Kubernetes Mesh Provisioner atomic skill. Stands up an RKE2 cluster (server + agents) with Cilium CNI and the NVIDIA GPU device plugin, the Kubernetes parallel of swarm-mesh-provisioner. Idempotent — re-runnable.
cost-optimization
Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
linkerd-patterns
Implement Linkerd service mesh patterns for lightweight, security-focused service mesh deployments. Use when setting up Linkerd, configuring traffic policies, or implementing zero-trust networking with minimal overhead.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.