Kubeshark Installer
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
Ask the user to rate the code/output just produced on a 1-5 star scale, then ask rating-appropriate follow-up questions, log the rating, and iterate until the work reaches 4+ stars.
$ npx skills add templetongroup/radiant --skill star-system -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install templetongroup/radiant star-system --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/templetongroup/radiant.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/star-system .claude/skills/star-system && rm -rf skills-srcUse ~/.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/
Install the "star-system" agent skill from https://github.com/templetongroup/radiant/tree/master/.claude/skills/star-system into .claude/skills/star-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "star-system", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/templetongroup/radiant/tree/master/.claude/skills/star-systemType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add templetongroup/radiant --skill star-system -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install templetongroup/radiant star-system --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/templetongroup/radiant.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/star-system .agents/skills/star-system && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "star-system" agent skill from https://github.com/templetongroup/radiant/tree/master/.claude/skills/star-system into .agents/skills/star-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "star-system", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add templetongroup/radiant --skill star-system -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install templetongroup/radiant star-system --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/templetongroup/radiant.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/star-system .cursor/skills/star-system && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "star-system" agent skill from https://github.com/templetongroup/radiant/tree/master/.claude/skills/star-system into .cursor/skills/star-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "star-system", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/templetongroup/radiant.git --path .claude/skills/star-system--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add templetongroup/radiant --skill star-system -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install templetongroup/radiant star-system --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/templetongroup/radiant.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/star-system .gemini/skills/star-system && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "star-system" agent skill from https://github.com/templetongroup/radiant/tree/master/.claude/skills/star-system into .gemini/skills/star-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "star-system", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install templetongroup/radiant star-systemInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add templetongroup/radiant --skill star-system -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/templetongroup/radiant.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/star-system .github/skills/star-system && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "star-system" agent skill from https://github.com/templetongroup/radiant/tree/master/.claude/skills/star-system into .github/skills/star-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "star-system", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add templetongroup/radiant --skill star-system -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install templetongroup/radiant star-system --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/templetongroup/radiant.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/star-system .opencode/skills/star-system && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "star-system" agent skill from https://github.com/templetongroup/radiant/tree/master/.claude/skills/star-system into .opencode/skills/star-system/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "star-system", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
star-systemAsk the user to rate the code/output just produced on a 1-5 star scale, then ask rating-appropriate follow-up questions, log the rating, and iterate until the work reaches 4+ stars.
Star System is an agent skill from templetongroup/radiant. Ask the user to rate the code/output just produced on a 1-5 star scale, then ask rating-appropriate follow-up questions, log the rating, and iterate until the work reaches 4+ stars. Use when the user says "run the star system", "rate this", or invokes /star-system after a deliverable is complete — AND automatically after every deployment, without being asked.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `SOURCE.md`).
It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: A local coding harness for Mac. Chat with coding agents across cloud and local models, watch every tool call in a live activity feed, and drive a real terminal — in one window… The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 94838ca. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Star System loads about 2.2k tokens when it runs. Until then it costs about 93 tokens; SKILL.md has 1,254 words of instructions outside code blocks.
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.
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.
The full file from templetongroup/radiant at commit 94838ca, republished under its MIT licence (© templetongroup). 1,254 words, ~2,173 tokens.
.claude/skills/star-system/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.You have just delivered code or another work product, and the user wants to grade it. Run this process exactly.
This protocol is model-agnostic and harness-agnostic: it works for any AI model under any agent harness, IDE, or plain chat window. Where a step mentions a tool or file, treat it as an example — use your harness's equivalent, and fall back to plain chat when no equivalent exists. No step may fail just because a tool is unavailable.
Ask the user to rate the output you just produced, presenting this scale (if your harness has a structured choice/question tool, present the five options with it; otherwise ask in plain chat):
Wait for the user's answer. Do not guess or self-assign a rating.
If the rating is 2 or 3 stars, offer an optional breakdown so the follow-up questions target the weak dimension. Ask the user to score (1-5) any of these that apply, or skip:
If the user provides sub-scores, focus Step 3's questions on the lowest-scoring dimensions and skip questions about dimensions scored 4+.
The lower the rating, the more you must learn before touching the code again. Ask the questions for the given rating (one message; use a structured question tool where your harness has one, free-form chat otherwise). Adapt wording to the actual deliverable — these are topics, not scripts.
The output is being discarded, so re-establish requirements from zero:
Major surgery, not a restart:
It works; find out what separates MVP from exceptional:
Close to perfect; identify the specific minor tweaks:
Ask nothing. Instead run the Gold Standard procedure (Step 6).
Every rating round is recorded. In the project being reviewed, create or append to ratings.md at the project root (create it with the structure below if absent):
# Star System Ratings
## Gold Standards
<!-- 5-star outputs live here permanently — see Step 6 -->
## Rating LogAppend each round under Rating Log as:
### <YYYY-MM-DD> — <short deliverable name> — <stars as ★ characters> (round <N>)
- **Feedback:** <1-3 bullet summary of the user's answers>
- **Plan:** <1-2 line summary of the agreed action plan, or "n/a" for 5 stars>Use the real current date. Round number increments each time the same deliverable is re-rated (Step 7). If the project has no writable root or the user declines the log, skip silently — never block the flow on logging.
For ratings 1-4:
ratings.md:### <short deliverable name> — <YYYY-MM-DD>
- **Where:** <file paths or directory of the exemplary code>
- **Why:** <the 2-4 bullets from above>After executing the action plan (Step 5), return to Step 1 and ask the user to re-rate the revised output.
Ask again after every deployment, unprompted. Any time fixed work reaches the user — shipped, released, installed on their device, pushed to the environment they will look at — that is a deployment, and it ends with the Step 1 question. Do not wait to be asked, do not batch several deployments into one rating, and do not decide on the user's behalf that a change was too small to be worth grading. The user should never have to remember to ask for the star system; the loop is what makes the rating a habit instead of an event.
Two things this is not. It is not a rating on work the user cannot see yet — if a change is committed but not deployed, finish deploying first. And it is not a prompt after every message: a turn that only investigates, answers a question, or reports findings has deployed nothing and ends normally.
© templetongroup, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in .claude/skills/star-system of templetongroup/radiant.
Open the folder on GitHubat commit 94838ca
Star System 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Star System this skilltempletongroup/radiant | 113 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Kubeshark Installerkubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Mirrord Operatormetalbear-co/mirrord | 5.4k | 1 repos | ~4.6k | Automated safety check: Pass | MIT | |
| KubeSphere ServiceMesh Managerkubesphere/kubesphere | 17k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| Vercelremotion-dev/remotion | 63k | — | ~1.2k | Automated safety check: Pass | Custom licence |
kubeshark/kubeshark
Installs and configures Kubeshark on a Kubernetes cluster, choosing between the quick CLI path and a Helm install with custom values.
GreptimeTeam/greptimedb
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
metalbear-co/mirrord
Help users install and configure the mirrord Operator for team/enterprise environments.
kubesphere/kubesphere
Installs, checks and troubleshoots the KubeSphere ServiceMesh extension (Istio, Kiali, Jaeger), including grayscale release, sidecar injection, topology and tracing issues.
remotion-dev/remotion
Set up a Codex monitor for Vercel deployments and preview URLs.
zxkane/aws-skills
AWS Cloud Development Kit (CDK) expert for building cloud infrastructure with TypeScript/Python.
templetongroup/radiant
A skill your agent uses to generate or audit design systems, check visual consistency, and review PRs that touch styling.
templetongroup/radiant
Design, redesign, build, audit, polish, and production-verify exceptional interfaces across web, mobile, and native apps.
templetongroup/radiant
Expert guidance for developing with the tinystruct Java framework.
templetongroup/radiant
Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets.
templetongroup/radiant
Production-ready UI motion system for React/Next.js. An agent skill from templetongroup/radiant.
templetongroup/radiant
Read a plan document, decompose it into steps, design a per-step agent chain from the ECC catalogue, and emit ready-to-paste /orchestrate custom prompts.
Categories
Ask the user to rate the code/output just produced on a 1-5 star scale, then ask rating-appropriate follow-up questions, log the rating, and iterate until the work reaches 4+ stars. Star System is an agent skill from templetongroup/radiant. Ask the user to rate the code/output just produced on a 1-5 star scale, then ask rating-appropriate follow-up questions, log the rating, and iterate until the work reaches 4+ stars.
Star System fits situations like: the user says run the star system; invokes /star-system after a deliverable is complete — AND automatically after every deployment; without being asked.
Run `npx skills add templetongroup/radiant --skill star-system -a claude-code`. Or copy the skill folder (.claude/skills/star-system in templetongroup/radiant) into .claude/skills/star-system in your project. Claude Code loads it when a task matches its description.
Run `npx skills add templetongroup/radiant --skill star-system -a codex`. Or copy the skill folder (.claude/skills/star-system in templetongroup/radiant) into .agents/skills/star-system in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add templetongroup/radiant --skill star-system -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/star-system, .gemini/skills/star-system, .github/skills/star-system and .opencode/skills/star-system in your project.
SKILL.md names no scripts, command-line tools or credentials: Star System is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
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.
Star System is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.2k tokens (SKILL.md is roughly 8.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Star System: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), Mirrord Operator (metalbear-co/mirrord, 5.4k stars) and KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
templetongroup (a GitHub user) maintains it in templetongroup/radiant, which has 113 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 6, 2026.
Source: templetongroup/radiant on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.