Agent skill

Castai Core Workflow B

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Enable CAST AI optimization through a measured canary with explicit node and workload policy boundaries.

MITAuto-check passedDevOps & Cloud

Install Castai Core Workflow B

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill castai-core-workflow-b -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace castai-core-workflow-b --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/castai-core-workflow-b .claude/skills/castai-core-workflow-b && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
castai-core-workflow-b
GitHub stars
2.8k
Token cost
~1.2k tokens
SKILL.md length
457 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Enable CAST AI optimization through a measured canary with explicit node and workload policy boundaries.

  • Works in 6 steps: Define the control matrix → Set guardrails → Preview the change → …
  • Observation-first onboarding is complete and Node Autoscaling
  • SKILL.md covers Overview, Prerequisites, Instructions and Tool Discipline, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Castai Core Workflow B is an agent skill from jeremylongshore/tons-of-skills-marketplace. Enable CAST AI optimization through a measured canary with explicit node and workload policy boundaries. Use when observation-first onboarding is complete and Node Autoscaling, Workload Autoscaling, or managed HPA behavior can be activated. Trigger with: "enable CAST AI automation", "canary CAST AI autoscaling", "apply CAST AI optimization policies".

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/official-docs.md`). Compatibility notes: Requires a connected cluster, representative baseline, and approved ownership of node and workload scaling controls

It sits in DevOps & Cloud, covering Deployment. It works with Bash. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Observation-first onboarding is complete and Node Autoscaling
  • Workload Autoscaling
  • Managed HPA behavior can be activated
  • With: enable CAST AI automation

Example prompts

  • “enable CAST AI automation”
  • “canary CAST AI autoscaling”
  • “apply CAST AI optimization policies”
  • “/castai-core-workflow-b”

Requirements

  • Compatibility (from SKILL.md): Requires a connected cluster, representative baseline, and approved ownership of node and workload scaling controls
  • Pre-approved tools (allowed-tools): Read, Grep, Write, Edit, Bash(kubectl:*), Bash(terraform:*), Bash(castctl:*)

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Define the control matrix
  2. Set guardrails
  3. Preview the change
  4. Enable a workload canary
  5. Observe capacity and workload outcomes
  6. Expand or roll back

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Write
    • Edit
    • Bash(kubectl:*)
    • Bash(terraform:*)
    • Bash(castctl:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.cast.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires a connected cluster, representative baseline, and approved ownership of node and workload scaling controls

    From compatibility in the SKILL.md frontmatter.

Context cost

Castai Core Workflow B loads about 1.2k tokens when it runs, and up to ~1.4k if it reads all its reference files. Until then it costs about 94 tokens; SKILL.md has 457 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~94
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 457 words, ~1,213 tokens.

Download SKILL.mdSave it as .claude/skills/castai-core-workflow-b/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
castai-core-workflow-b
description
Enable CAST AI optimization through a measured canary with explicit node and workload policy boundaries. Use when observation-first onboarding is complete and Node Autoscaling, Workload Autoscaling, or managed HPA behavior can be activated. Trigger with: "enable CAST AI automation", "canary CAST AI autoscaling", "apply CAST AI optimization policies".
allowed-tools
Read, Grep, Write, Edit, Bash(kubectl:*), Bash(terraform:*), Bash(castctl:*)
compatibility
Requires a connected cluster, representative baseline, and approved ownership of node and workload scaling controls
version
2.0.0
argument-hint
[cluster-and-canary-workload]
model
inherit
effort
high
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, kubernetes, cast-ai, autoscaling, rollout

CAST AI Controlled Optimization Rollout

Overview

Turn recommendations into automation one bounded control at a time. Separate node capacity, vertical workload rightsizing, and horizontal replica control so each has an observable success condition and rollback.

Prerequisites

  • A healthy connected cluster and representative cost/workload baseline
  • Current scaling policies, node templates, PDBs, HPAs, quotas, and protected namespaces
  • A low-risk canary workload with an accountable owner

Instructions

Step 1: Define the control matrix

Use Read and Grep to map Node Autoscaling, Workload Autoscaler vertical mode, horizontal autoscaling, existing HPAs, and external provisioners. Record one owner for each control. Do not transfer HPA ownership implicitly.

Step 2: Set guardrails

Use Write or Edit to define approved node templates, availability zones, instance lifecycle constraints, maximum CPU, workload minimums/maximums, policy assignment, PDB expectations, and rollback thresholds. Do not add the deprecated cluster minimum CPU setting.

Step 3: Preview the change

Use Bash(terraform:) to produce a saved reviewed plan when Terraform owns the configuration. Use Bash(castctl:) only for supported inspection or documented feature operations. Confirm the diff affects the intended cluster and canary only.

Step 4: Enable a workload canary

Choose Immediate mode only when controlled pod replacement is acceptable; the Eviction API will enforce PDBs. Choose Deferred mode when recommendations should apply on natural recreation. If horizontal autoscaling is enabled, review the native autoscaling/v2 HPA configuration and any take-ownership decision.

Step 5: Observe capacity and workload outcomes

Use Bash(kubectl:*) to inspect pending pods, scheduling events, HPA state, pod replacements, PDBs, requests, and node changes. Compare availability, latency, saturation, and spend to the pre-change baseline; do not optimize on cost alone.

Show full SKILL.md (193 more words)Show less
Step 6: Expand or roll back

Expand one policy assignment group at a time only after the canary window passes. Roll back automation or policy assignment when error budget, capacity, disruption, or performance thresholds fail, while preserving evidence.

Tool Discipline

Use Read and Grep for ownership and policy evidence. Use Write and Edit for the control matrix and rollback record. Use Bash(terraform:), Bash(castctl:), and Bash(kubectl:*) only inside the approved plan, rollout, and observation boundaries.

Output

  • Node/workload/HPA ownership matrix
  • Guardrails and canary selection
  • Before-and-after availability, capacity, and cost evidence
  • Expansion decision or tested rollback receipt

Examples

A stateless deployment starts in Deferred vertical mode with no HPA ownership transfer. A later reviewed change enables policy-managed horizontal scaling after the workload owner approves replica bounds and stabilization behavior.

Error Handling

FailureResponse
PDB blocks Immediate modePreserve availability and select Deferred mode or revise with owner approval
Pending pods cannot match templatesRoll back and correct template constraints
Existing HPA is unexpectedly replacedDisable managed horizontal scaling and restore declared ownership
Cost falls while latency regressesRoll back; performance guardrails take precedence

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/castai-core-workflow-b of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/official-docs.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Castai Core Workflow B next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Castai Core Workflow B compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
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Deploy Checklistwednesday-solutions/ai-agent-skills170—~702Automated safety check: PassMIT
Mac App Releasesteipete/agent-scripts7.3k—~2.3kAutomated safety check: PassMIT
ReleaseTypedDevs/bashunit434—~618Automated safety check: NotesMIT
Kubeshark Installerkubeshark/kubeshark12k—~3.6kAutomated safety check: NotesApache-2.0

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Works with

Categories

Questions about Castai Core Workflow B

What does Castai Core Workflow B do?

Enable CAST AI optimization through a measured canary with explicit node and workload policy boundaries. Castai Core Workflow B is an agent skill from jeremylongshore/tons-of-skills-marketplace. Enable CAST AI optimization through a measured canary with explicit node and workload policy boundaries.

When should I use Castai Core Workflow B?

Castai Core Workflow B fits situations like: observation-first onboarding is complete and Node Autoscaling; workload Autoscaling; managed HPA behavior can be activated; with: enable CAST AI automation.

How do I install Castai Core Workflow B in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill castai-core-workflow-b -a claude-code`. Or copy the skill folder (skills/.curated/castai-core-workflow-b in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/castai-core-workflow-b in your project. Claude Code loads it when a task matches its description.

How do I install Castai Core Workflow B in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill castai-core-workflow-b -a codex`. Or copy the skill folder (skills/.curated/castai-core-workflow-b in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/castai-core-workflow-b in your project. Codex loads it when a task matches its description.

Can I use Castai Core Workflow B in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill castai-core-workflow-b -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/castai-core-workflow-b, .gemini/skills/castai-core-workflow-b, .github/skills/castai-core-workflow-b and .opencode/skills/castai-core-workflow-b in your project.

What does Castai Core Workflow B need to run?

SKILL.md names no scripts, command-line tools or credentials: Castai Core Workflow B is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Write, Edit, Bash(kubectl:*), Bash(terraform:*), Bash(castctl:*). Compatibility (from SKILL.md): Requires a connected cluster, representative baseline, and approved ownership of node and workload scaling controls.

Does Castai Core Workflow B access the network?

SKILL.md names 1 domain. As links in the text: docs.cast.ai. This is read from the text; nothing was executed.

Is Castai Core Workflow B safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Castai Core Workflow B use?

Castai Core Workflow B is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Castai Core Workflow B use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 219 tokens, read only when the agent opens those files.

What are the alternatives to Castai Core Workflow B?

Skills that share tags, products or a category with Castai Core Workflow B: Aspire (microsoft/aspire.dev, 195 stars), Deploy Checklist (wednesday-solutions/ai-agent-skills, 170 stars), Mac App Release (steipete/agent-scripts, 7.3k stars) and Release (TypedDevs/bashunit, 434 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Castai Core Workflow B?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.