SageMaker Production Defaults
huggingface/skills
Deploys SageMaker endpoints with autoscaling, CloudWatch alarms and tags on by default, using scripts for real-time, scale-to-zero and async setups.
Shared review framework that every domain reviewer (pci, oracle, gov, edtech, healthcare, mlops, etc.) MUST follow.
$ npx skills add avelikiy/great_cto --skill archetype-review-base -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install avelikiy/great_cto archetype-review-base --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/avelikiy/great_cto.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/archetype-review-base .claude/skills/archetype-review-base && 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 "archetype-review-base" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/archetype-review-base into .claude/skills/archetype-review-base/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "archetype-review-base", 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/avelikiy/great_cto/tree/main/skills/archetype-review-baseType 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 avelikiy/great_cto --skill archetype-review-base -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install avelikiy/great_cto archetype-review-base --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/archetype-review-base .agents/skills/archetype-review-base && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "archetype-review-base" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/archetype-review-base into .agents/skills/archetype-review-base/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "archetype-review-base", 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 avelikiy/great_cto --skill archetype-review-base -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install avelikiy/great_cto archetype-review-base --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/archetype-review-base .cursor/skills/archetype-review-base && 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 "archetype-review-base" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/archetype-review-base into .cursor/skills/archetype-review-base/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "archetype-review-base", 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/avelikiy/great_cto.git --path skills/archetype-review-base--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 avelikiy/great_cto --skill archetype-review-base -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install avelikiy/great_cto archetype-review-base --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/archetype-review-base .gemini/skills/archetype-review-base && 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 "archetype-review-base" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/archetype-review-base into .gemini/skills/archetype-review-base/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "archetype-review-base", 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 avelikiy/great_cto archetype-review-baseInstalls 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 avelikiy/great_cto --skill archetype-review-base -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/archetype-review-base .github/skills/archetype-review-base && 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 "archetype-review-base" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/archetype-review-base into .github/skills/archetype-review-base/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "archetype-review-base", 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 avelikiy/great_cto --skill archetype-review-base -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install avelikiy/great_cto archetype-review-base --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/archetype-review-base .opencode/skills/archetype-review-base && 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 "archetype-review-base" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/archetype-review-base into .opencode/skills/archetype-review-base/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "archetype-review-base", 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.
archetype-review-baseShared review framework that every domain reviewer (pci, oracle, gov, edtech, healthcare, mlops, etc.) MUST follow.
Archetype Review Base is an agent skill from avelikiy/great_cto. Shared review framework that every domain reviewer (pci, oracle, gov, edtech, healthcare, mlops, etc.) MUST follow. Defines the output artifact (TM-{slug}.md), mandatory sections, severity scale, verdict format, the workflow scaffold (when-invoked, Step-0 read-inputs, HANDOFF), and the "domain heuristic vs generic check" boundary. Eliminates duplication across the ~30 reviewer prompts.
Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `reviewer-template.md`).
It sits in DevOps & Cloud, covering MLOps and Educational content. The repository describes itself as: You already have the agent. This is everything around it. greatcto runs Claude Code as a pipeline of 70 specialist agents — an independent model checks each stage before the next… The licence is MIT.
Read from SKILL.md and the folder at commit 97dd037. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteGrepGlobBash(git:*)Bash(bd:*)From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
bashFrom 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.
Archetype Review Base loads about 3.1k tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 746 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 avelikiy/great_cto at commit 97dd037, republished under its MIT licence (© avelikiy). 746 words, ~3,148 tokens.
.claude/skills/archetype-review-base/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Every domain reviewer follows this skeleton. Each reviewer's own SKILL.md adds the domain heuristics on top. This skill defines the parts that must be IDENTICAL across all reviewers.
Pre-implementation reviewers (the *-reviewer agents — ~30 in agents/ —
invoked by architect BEFORE senior-dev claims tasks) write a threat model at
docs/sec-threats/TM-{slug}.md and append a <!-- HANDOFF --> block (see
"Workflow scaffold" below). That is the single convention for every reviewer.
One TM file per feature slug. Per-reviewer filename suffixes
(TM-api-{slug}.md, TM-extension-{slug}.md) are deprecated — consumers glob
TM-{slug}.md and per-suffix files silently escape their checks. When multiple
domain reviewers run on the same slug, each APPENDS its own ## {reviewer} findings section and its own <!-- HANDOFF --> block to the shared
TM-{slug}.md — never overwrite another reviewer's sections.
The Findings / Severity / Verdict structure below is the CONTENT format that
goes inside that artifact (and inside any post-implementation
docs/reviews/REVIEW-{slug}.md produced by a review-tier agent). Path differs by
phase; the section grammar is identical.
The report (TM or REVIEW) MUST contain these sections in this exact order:
# TM-{slug} — {reviewer name} <!-- pre-impl; post-impl review-tier files use REVIEW-{slug} -->
Reviewed: {commit-sha or file paths or ARCH doc reference}
Standard: {regulation / framework you applied — list specific clauses}
Date: {ISO timestamp}
## Scope
2-3 sentences. What did you look at? What's intentionally out of scope?
## Findings
For each finding, use this exact format:
- **[Critical|High|Medium|Low]** {one-sentence finding title}
- Location: {file:line or component name}
- Rationale: {why this matters IN THIS DOMAIN — cite a regulation or
domain-specific best practice. Generic "could be a problem" is
rejected.}
- Repro: {a command, or numbered steps, that SHOWS the finding. Required for
Critical and High.}
- Remediation: {specific fix — code change, config change, or
architectural change. NOT "consider adding X" — write the exact change.}
- References: {URL or document section}
Order findings: Critical → High → Medium → Low.
If no findings at a tier, write: "_None at {tier} severity._"
### Repro, and why it is required at Critical and High
A finding with no reproduction cannot be shown to be fixed, so closing it is an
opinion. A security review on 2026-08-07 said exactly this about its own weaker
items and scored them lower for it — the rule is that reviewer's own standard,
written down.
It is also what makes the finding survive you. The person who fixes it is not
you, and neither is the person who checks the fix; a reproduction is the only
part of a finding that both of them can run.
### File Critical and High as beads
A finding that lives only in a report is one nobody can track, and one whose
closure nobody can check. Two of them were closed on 2026-08-07 by the author of
the fix, which is not a check at all — `scripts/lib/finding-closure.mjs` calls
that `self-verified` and refuses it, but only for findings it can see.
```bash
bd create "[Critical] {title}" --label finding --type bug \
-d "Location: {file:line}
Repro: {command or steps}
Rationale: {why}
Remediation: {exact fix}"Then, as the finding moves:
bd comment <id> "fixed-by: <agent>" # whoever writes the fix
bd comment <id> "verified-by: <agent>
repro-result: passed" # someone who did NOT write it,
# stating what the repro did NOW
bd close <id> --reason "repro re-run after the fix, now passing"repro-result is passed, failed or not_run, and the VERIFIER writes it in
the same comment as verified-by. Nothing re-executes the reproduction on your
behalf: running a command out of a bead description is how a reporting channel
becomes an execution channel, and it produced three CRITICALs in
execution-claims on 2026-08-07. So this rung checks who says the repro passes
and whether they wrote the fix — not the command. That is a real limit and it is
the deliberate one.
A verification that does not say what the reproduction did leaves the finding
repro-not-run. "Looks fine to me" is not a result.
The verifier may not be the fixer, the verification must come after the fix, and the repro must pass now. Those are checked, not merely asked for.
VERDICT: {APPROVED|BLOCKED} reason="{specific reason}"
**Quotes must exist.** Before a finding quotes a file, run `node "${CLAUDE_PLUGIN_ROOT:-$(ls -d ~/.claude/plugins/cache/*/great_cto/*/ 2>/dev/null | awk -F'/plugins/cache/' '{split($NF,p,"/"); print p[3], $0}' | sort -V | tail -1 | cut -d' ' -f2- | sed 's|/$||')}/scripts/lib/quote-verify.mjs" --file <file> --quote "<passage>"` (or `--scan <report>`).
A quote that does not verify is removed, or rewritten as a paraphrase marked `(paraphrase)`.
## Severity scale (DOMAIN-anchored)
Severity is graded against THIS DOMAIN's regulatory or
correctness baseline, not generic STRIDE severity. Examples:
- A PCI reviewer rating an unencrypted PAN at REST = **Critical** (PCI
scope violation; immediate regulatory exposure)
- An oracle reviewer rating a Chainlink staleness < 1h = **High**
(likely OK now, MEV vulnerable in stress)
- A gov reviewer rating Section 508 a11y gaps = **High** (federal
contract risk; not Critical because not an immediate breach)
Cite the standard in Rationale. If you can't, the finding is probably
generic and should be reduced one severity tier (the security-officer
agent handles generic concerns).
## Verdict rules
- `VERDICT: APPROVED` is allowed only when ALL Critical and ALL High
findings have remediation in the bd backlog. (Use
`bd ready --label {your-archetype}` to check.)
- `VERDICT: BLOCKED` is required when even one Critical or High has no
remediation, OR when discovery surfaced an unknown that you couldn't
resolve.
- Medium and Low findings do NOT block. Note them; pipeline continues.
## Domain heuristic vs generic check
You are the SPECIALIST. Your job is the domain-specific stuff that
generic STRIDE / OWASP misses. Decision rule:
| The check is about… | Belongs to |
|---|---|
| Card data, PCI scope, idempotency in payments | pci-reviewer |
| Oracle staleness, MEV, contract upgradeability | oracle-reviewer |
| PHI flows, BAA chain, FHIR/HL7 | healthcare-reviewer |
| Generic XSS, SQLi, weak hashing, secrets in source | security-officer (NOT you) |
| Generic "needs error handling" | senior-dev / code-reviewer (NOT you) |
If a finding is generic, mention it briefly but DON'T inflate severity.
Defer to the appropriate generic reviewer.
## Apply skeptical-triage
Before emitting `VERDICT: BLOCKED`, apply the `skeptical-triage` skill
(3 rounds of self-challenge). False-positive BLOCKED at gate:plan wastes
CTO time. Only block when 3/3 rounds confirm.
## Verdict log line
After writing your report, record the canonical verdict via the helper (see
`agents/_shared/verdict-format.md` — do NOT hand-write the line; the helper
guarantees the format the board parser and the pipeline dispatcher both read,
and `auto` records real token cost):
```bash
bash scripts/log-verdict.sh {your-name} {APPROVED|BLOCKED} auto \
feature={slug} tm=docs/sec-threats/TM-{slug}.md criticals={N} highs={M} \
need={implementer|decision} finding={id} # need/finding on BLOCKED onlyAPPROVED and BLOCKED are the only two words, and on BLOCKED need says who
acts — the rules, and why no third word, are in agents/_shared/reviewer-verdict.md.
Every reviewer's own prompt carries this line with its name filled in.
prose-styleEscalate to security-officer (not just BLOCK) when:
Escalation: create a bd task with label security-officer and
blocks your review verdict.
Before writing your verdict line, grep your draft for:
\b(generally|somewhat|fairly|mostly|possibly|perhaps|maybe)\b — rewriteIf any check fires in a non-quoted block, fix before signing off.
Every reviewer shares the same skeleton. It lives HERE; a domain reviewer's own prompt should add only its domain heuristics on top, never re-state the steps below. (Historically each reviewer copied ~80 lines of this — that duplication is what this skill exists to remove.)
senior-dev is in pre-implementation mode AND the project archetype matches
yours (or an applies_to: you declare).You run BEFORE senior-dev claims tasks. Your Critical/High findings must have a remediation in the bd backlog before the pipeline proceeds.
mkdir -p docs/sec-threats
ARCH=$(ls docs/architecture/ARCH-*.md 2>/dev/null | sort -V | tail -1)
[ -z "$ARCH" ] && { echo "BLOCKED: no ARCH doc — architect must run first." >&2; exit 1; }
SLUG=$(basename "$ARCH" .md | sed 's/^ARCH-//')
TM="docs/sec-threats/TM-${SLUG}.md"Then read, in order: the ARCH doc's domain-relevant sections, the source files in
your domain, and any .great_cto/PROJECT.md fields your domain needs (e.g.
code-sets:, payers:, compliance:).
docs/sec-threats/TM-${SLUG}.mdUse your domain template at skills/great_cto/templates/TM-{archetype}.md if one
exists, else the Findings/Severity/Verdict grammar above. End the file with a
hand-off block the orchestrator parses:
<!-- HANDOFF -->
{your-name}-verdict: signed-off | blocked
critical-findings: <N>
high-findings: <M>
must-implement-before-senior-dev:
- <specific change 1>
- <specific change 2>
gate: <gate:domain-signoff or — if none>skills: frontmatter is the source of truth.See skills/archetype-review-base/reviewer-template.md for the minimal shape a
domain reviewer should follow after this scaffold is factored out.
© avelikiy, 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 skills/archetype-review-base of avelikiy/great_cto.
Open the folder on GitHubat commit 97dd037
Archetype Review Base 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 |
|---|---|---|---|---|---|---|
| Archetype Review Base this skillavelikiy/great_cto | 102 | — | ~3.1k | Automated safety check: Pass | MIT | |
| SageMaker Production Defaultshuggingface/skills | 11k | 1 repos | ~6.9k | Automated safety check: Pass | Apache-2.0 | |
| SkyPilot Multi-Cloud OrchestrationOrchestra-Research/AI-Research-SKILLs | 13k | 4 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Model Garden Deploymentgoogle/skills | 21k | — | ~5k | Automated safety check: Pass | Apache-2.0 | |
| Register ModelSunshow/droidgear | 127 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Build ML Pipelineprobabl-ai/skills | 138 | — | ~4.4k | Automated safety check: Pass | BSD-3-Clause |
huggingface/skills
Deploys SageMaker endpoints with autoscaling, CloudWatch alarms and tags on by default, using scripts for real-time, scale-to-zero and async setups.
Orchestra-Research/AI-Research-SKILLs
Runs ML training and batch jobs across clouds with SkyPilot, using spot instances, automatic region selection and managed recovery to cut GPU cost.
google/skills
Deploys open models or custom weights from Model Garden to Agent Platform endpoints, checks deployment status and cleans up endpoints, confirming before any change.
Sunshow/droidgear
Register a new AI model in DroidGear's model registry by fetching specs from models.dev.
probabl-ai/skills
Declare the pipeline from data source to predictor as a skrub DataOps graph.
wshobson/agents
Guides an agent through designing an MLOps pipeline that covers data preparation, training, validation and deployment, with DAG orchestration and reference guides.
avelikiy/great_cto
Analyzes a screenshot, website or Figma file and writes a `design.md` with its token system, component inventory and reconstruction notes, or an `element.md` for one element.
avelikiy/great_cto
Builds an Opportunity Solution Tree that links one measurable outcome to customer opportunities, candidate solutions and experiments.
avelikiy/great_cto
Rewrites a feature-list roadmap into outcome statements that name the customer segment, the result they get and the business impact, grouped into themes.
avelikiy/great_cto
Turns a leaked key, token or password into one tracked rotation task the moment it's spotted, instead of a reminder repeated every session.
avelikiy/great_cto
Runs a three-round self-challenge plus an arbiter over high-stakes findings, so false positives from reviews, audits and flaky-test verdicts do not become blockers.
avelikiy/great_cto
greatcto's own committed aesthetic — the instrument panel. An agent skill from avelikiy/great_cto.
Categories
Shared review framework that every domain reviewer (pci, oracle, gov, edtech, healthcare, mlops, etc.) MUST follow. Archetype Review Base is an agent skill from avelikiy/great_cto.) MUST follow.
Archetype Review Base fits situations like: tasks that involve MLOps; tasks that involve Educational content.
Run `npx skills add avelikiy/great_cto --skill archetype-review-base -a claude-code`. Or copy the skill folder (skills/archetype-review-base in avelikiy/great_cto) into .claude/skills/archetype-review-base in your project. Claude Code loads it when a task matches its description.
Run `npx skills add avelikiy/great_cto --skill archetype-review-base -a codex`. Or copy the skill folder (skills/archetype-review-base in avelikiy/great_cto) into .agents/skills/archetype-review-base 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 avelikiy/great_cto --skill archetype-review-base -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/archetype-review-base, .gemini/skills/archetype-review-base, .github/skills/archetype-review-base and .opencode/skills/archetype-review-base in your project.
Going by SKILL.md and its folder, Archetype Review Base needs the command-line tools its instructions call (bash). Its frontmatter pre-approves these tools: Read, Write, Grep, Glob, Bash(git:*), Bash(bd:*).
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.
Archetype Review Base is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.1k tokens (SKILL.md is roughly 13k 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 Archetype Review Base: SageMaker Production Defaults (huggingface/skills, 11k stars), SkyPilot Multi-Cloud Orchestration (Orchestra-Research/AI-Research-SKILLs, 13k stars), Model Garden Deployment (google/skills, 21k stars) and Register Model (Sunshow/droidgear, 127 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
avelikiy (a GitHub user) maintains it in avelikiy/great_cto, which has 102 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 9, 2026.
Source: avelikiy/great_cto on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.