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Agent skill

Review Automation Orchestrator

by TencentCloudBase in TencentCloudBase/CloudBase-AI-Toolkit

A skill your agent uses when running or scheduling periodic repository review cycles that must dispatch the correct reviewer, aggregate findings, and escalate outcomes into reports, issues, or…

MITAuto-check passedDevelopment

Install Review Automation Orchestrator

skills CLI
$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill review-automation-orchestrator -a claude-code

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

GitHub CLI
$ gh skill install TencentCloudBase/CloudBase-AI-Toolkit review-automation-orchestrator --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/TencentCloudBase/CloudBase-AI-Toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review-automation-orchestrator .claude/skills/review-automation-orchestrator && 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
review-automation-orchestrator
GitHub stars
1.1k
Token cost
~1.2k tokens
SKILL.md length
570 words
Files
2 (incl. references)
Skills in repo
48
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when running or scheduling periodic repository review cycles that must dispatch the correct reviewer, aggregate findings, and escalate outcomes into reports, issues, or…

  • Works in 5 steps: Define the run → Dispatch to the right reviewer → Normalize findings → …
  • Scheduling periodic repository review cycles that must dispatch the correct reviewer
  • SKILL.md covers When to use this skill, Workflow, Routing and Evaluation prompts, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Review Automation Orchestrator is an agent skill from TencentCloudBase/CloudBase-AI-Toolkit. Use when running or scheduling periodic repository review cycles that must dispatch the correct reviewer, aggregate findings, and escalate outcomes into reports, issues, or corrective PRs across API contracts, documentation freshness, code quality, and CloudBase skill quality.

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/escalation-matrix.md`).

It sits in Development, covering API design and Code quality. The repository describes itself as: Backend for AI coding agents on CloudBase — database, auth, functions via Plugin, Skills & MCP. The licence is MIT.

When your agent uses it

  • Scheduling periodic repository review cycles that must dispatch the correct reviewer
  • Aggregate findings
  • Escalate outcomes into reports
  • Corrective PRs across API contracts

Example prompts

  • “/review-automation-orchestrator”

Workflow steps

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

  1. Define the run
  2. Dispatch to the right reviewer
  3. Normalize findings
  4. Escalate
  5. Scheduling discipline

What it can do on your machine

Read from SKILL.md and the folder at commit 5360dde. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • 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

    No URLs in SKILL.md.

    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.

Context cost

Review Automation Orchestrator 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 77 tokens; SKILL.md has 570 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~77
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 TencentCloudBase/CloudBase-AI-Toolkit at commit 5360dde, republished under its MIT licence (© TencentCloudBase). 570 words, ~1,155 tokens.

Download SKILL.mdSave it as .claude/skills/review-automation-orchestrator/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
review-automation-orchestrator
description
Use when running or scheduling periodic repository review cycles that must dispatch the correct reviewer, aggregate findings, and escalate outcomes into reports, issues, or corrective PRs across API contracts, documentation freshness, code quality, and CloudBase skill quality.
alwaysApply
false

Review Automation Orchestrator

Coordinate recurring repository review work without turning one skill into every reviewer at once.

When to use this skill

Use this skill when you need to:

  • Run a periodic repository review across several quality dimensions
  • Decide which specialized review skill should own each finding type
  • Aggregate review results into one report with clear escalation
  • Convert high-confidence, low-risk findings into corrective PRs when feasible
  • Configure or run a scheduled review cycle without duplicating the underlying reviewer logic

Do NOT use for:

  • Acting as the primary reviewer for API contracts, docs, or code quality by itself
  • Replacing the existing CloudBase skill review flow under skill-authoring
  • Fixing a single known issue without a broader review cycle
  • Merging PRs or making final release decisions

Workflow

Phase 1 — Define the run
  1. Clarify whether the run is one-time or periodic.
  2. Define the review surfaces and target outputs:
    • report only
    • issue + report
    • fix + PR
  3. Read references/escalation-matrix.md before dispatching work.
Phase 2 — Dispatch to the right reviewer

Route by finding type, not by convenience:

  • CloudBase API contract correctness → api-contract-review
  • Published docs and README drift → doc-freshness-review
  • Broad code hygiene and proactive repository health → codebase-audit
  • Existing open PR triage and repair → pr-review-fix
  • CloudBase source skill quality under config/source/skills → skill-authoring, then load references/repo-skill-review.md and references/cloudbase-skill-review.md

Do not create a redundant top-level CloudBase skill reviewer when the existing skill-authoring flow already covers it.

Phase 3 — Normalize findings
  1. Deduplicate overlaps between reviewers.
  2. Normalize each finding with:
    • scope
    • severity
    • confidence
    • smallest useful fix batch
    • recommended action from the escalation matrix
  3. Keep reports readable: separate API, docs, code, and skill findings.
Phase 4 — Escalate
  1. Use report only for lower-confidence or lower-impact findings.
  2. Use issue + report for confirmed but broader or riskier problems.
  3. Use fix + PR when the finding is confirmed, mechanically fixable, and small enough for a focused review.
  4. Prefer concrete PRs over issue-only churn when the path is already clear and low-risk.
Show full SKILL.md (249 more words)Show less
Phase 5 — Scheduling discipline
  1. If the user asks for recurrence, create automation that runs the review cycle and stores the task prompt separately from schedule details.
  2. Keep the scheduled prompt short and routing-focused.
  3. Do not duplicate reviewer checklists inside the automation definition.

Routing

TaskRead
Decide escalation from severity and confidencereferences/escalation-matrix.md
Review CloudBase API contract correctnessapi-contract-review
Review doc and README driftdoc-freshness-review
Run broad repository code reviewcodebase-audit
Repair existing PRs after reviewpr-review-fix
Review CloudBase source skillsskill-authoring

Evaluation prompts

Should-trigger
  1. Run a weekly repository review that checks CloudBase API contracts, docs freshness, and skill quality, then decide what should become PRs.
  2. Help me set up a periodic review flow that routes findings to the right reviewer and escalates only the high-confidence fixes.
  3. Aggregate findings from code, docs, and CloudBase skill review into one actionable maintenance report.
Should-not-trigger
  1. Review this one MCP tool for parameter casing errors.
  2. Audit doc/ for stale links and missing files.
  3. Rewrite a CloudBase source skill description to improve its trigger wording.

Minimum self-check

  • Did I dispatch each finding class to the correct specialized reviewer?
  • Did I reuse skill-authoring for CloudBase skill review instead of inventing a duplicate flow?
  • Did I normalize findings by severity, confidence, and smallest useful fix batch?
  • Did I choose report, issue, or PR based on evidence rather than habit?
  • If the run is periodic, did I keep the automation prompt focused on routing instead of embedding whole checklists?

© TencentCloudBase, 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/review-automation-orchestrator of TencentCloudBase/CloudBase-AI-Toolkit.

  • SKILL.md
  • references/escalation-matrix.md

Open the folder on GitHubat commit 5360dde

Compare with similar skills

Review Automation Orchestrator 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.

Review Automation Orchestrator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Review Automation Orchestrator this skillTencentCloudBase/CloudBase-AI-Toolkit1.1k—~1.2kAutomated safety check: PassMIT
Modern Csharp Coding Standardssketch7/FluentlyHttpClient1213 repos~2.7kAutomated safety check: PassMIT
Code Qualitypiomin/claude-ai-spring-boot1.3k—~2.2kAutomated safety check: PassApache-2.0
Code Qualitystatic-web-server/static-web-server2.4k—~1.1kAutomated safety check: PassApache-2.0
Go Pedantrychromedp/chromedp13k—~3.7kAutomated safety check: PassMIT
LangBot Core Developmentlangbot-app/LangBot18k—~1.4kAutomated safety check: NotesApache-2.0

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Categories

Questions about Review Automation Orchestrator

What does Review Automation Orchestrator do?

A skill your agent uses when running or scheduling periodic repository review cycles that must dispatch the correct reviewer, aggregate findings, and escalate outcomes into reports, issues, or…. Review Automation Orchestrator is an agent skill from TencentCloudBase/CloudBase-AI-Toolkit. Use when running or scheduling periodic repository review cycles that must dispatch the correct reviewer, aggregate findings, and escalate outcomes into reports, issues, or corrective PRs across API contracts, documentation freshness, code quality, and CloudBase skill quality.

When should I use Review Automation Orchestrator?

Review Automation Orchestrator fits situations like: scheduling periodic repository review cycles that must dispatch the correct reviewer; aggregate findings; escalate outcomes into reports; corrective PRs across API contracts.

How do I install Review Automation Orchestrator in Claude Code?

Run `npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill review-automation-orchestrator -a claude-code`. Or copy the skill folder (skills/review-automation-orchestrator in TencentCloudBase/CloudBase-AI-Toolkit) into .claude/skills/review-automation-orchestrator in your project. Claude Code loads it when a task matches its description.

How do I install Review Automation Orchestrator in Codex?

Run `npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill review-automation-orchestrator -a codex`. Or copy the skill folder (skills/review-automation-orchestrator in TencentCloudBase/CloudBase-AI-Toolkit) into .agents/skills/review-automation-orchestrator in your project. Codex loads it when a task matches its description.

Can I use Review Automation Orchestrator 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 TencentCloudBase/CloudBase-AI-Toolkit --skill review-automation-orchestrator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-automation-orchestrator, .gemini/skills/review-automation-orchestrator, .github/skills/review-automation-orchestrator and .opencode/skills/review-automation-orchestrator in your project.

What does Review Automation Orchestrator need to run?

SKILL.md names no scripts, command-line tools or credentials: Review Automation Orchestrator is instructions for the agent only.

Does Review Automation Orchestrator access the network?

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.

Is Review Automation Orchestrator 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 Review Automation Orchestrator use?

Review Automation Orchestrator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review Automation Orchestrator use?

About 1.2k tokens (SKILL.md is roughly 4.6k 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 295 tokens, read only when the agent opens those files.

What are the alternatives to Review Automation Orchestrator?

Skills that share tags, products or a category with Review Automation Orchestrator: Modern Csharp Coding Standards (sketch7/FluentlyHttpClient, 121 stars), Code Quality (piomin/claude-ai-spring-boot, 1.3k stars), Code Quality (static-web-server/static-web-server, 2.4k stars) and Go Pedantry (chromedp/chromedp, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Automation Orchestrator?

TencentCloudBase (a GitHub organization) maintains it in TencentCloudBase/CloudBase-AI-Toolkit, which has 1,134 GitHub stars. The repository holds 48 skills in this directory. The repository was last updated on October 10, 2026.

Source: TencentCloudBase/CloudBase-AI-Toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.