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Agent Skill · 研究检索

cto-advisor(首席技术官顾问)

cto-advisor 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

cto-advisor 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 1,538。

总安装 88,077周安装 3,563GitHub Stars 5下载 27,649核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
2.1.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cto-advisor(首席技术官顾问)
来源仓库:https://github.com/alirezarezvani/cto-advisor
安装命令:
openclaw skills install cto-advisor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install cto-advisor

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

cto-advisor 为技术决策和工程治理提供专业指导,适合在 OpenClaw 中辅助架构评估。适用于技术债务分析、团队扩展规划和架构策略制定等工程场景。基于关键词和任务目标提供结构化建议,支持多维度技术风险评估。

安装命令:openclaw skills install cto-advisor,需确认维护状态和权限范围。输出结果应作为参考,实际决策需结合组织实际情况验证。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install cto-advisor;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

cto-advisor 怎么安装?

在终端执行 openclaw skills install cto-advisor。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

cto-advisor 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

cto-advisor 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

cto-advisor 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

cto-advisor 用的人多吗?

公开数据是累计安装 88,077 次,近一周安装 3,563 次,下载 27,649 次,GitHub 5 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

cto-advisor 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
cto-advisor

首席技术官顾问 · 本页

88,0775需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
cto-advisor
description
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
license
MIT
metadata
version
2.0.0
author
Alireza Rezvani
category
c-level
domain
cto-leadership
updated
2026-03-05
python-tools
tech_debt_analyzer.py, team_scaling_calculator.py
frameworks
architecture-decisions, engineering-metrics, technology-evaluation

CTO Advisor

Technical leadership frameworks for architecture, engineering teams, technology strategy, and technical decision-making.

Keywords

CTO, chief technology officer, tech debt, technical debt, architecture, engineering metrics, DORA, team scaling, technology evaluation, build vs buy, cloud migration, platform engineering, AI/ML strategy, system design, incident response, engineering culture

Quick Start

python scripts/tech_debt_analyzer.py      # Assess technical debt severity and remediation plan
python scripts/team_scaling_calculator.py  # Model engineering team growth and cost

Core Responsibilities

1. Technology Strategy

Align technology investments with business priorities.

Strategy components:

  • Technology vision (3-year: where the platform is going)
  • Architecture roadmap (what to build, refactor, or replace)
  • Innovation budget (10-20% of engineering capacity for experimentation)
  • Build vs buy decisions (default: buy unless it's your core IP)
  • Technical debt strategy (management, not elimination)

See references/technology_evaluation_framework.md for the full evaluation framework.

2. Engineering Team Leadership

Scale the engineering org's productivity — not individual output.

Scaling engineering:

  • Hire for the next stage, not the current one
  • Every 3x in team size requires a reorg
  • Manager:IC ratio: 5-8 direct reports optimal
  • Senior:junior ratio: at least 1:2 (invert and you'll drown in mentoring)

Culture:

  • Blameless post-mortems (incidents are system failures, not people failures)
  • Documentation as a first-class citizen
  • Code review as mentoring, not gatekeeping
  • On-call that's sustainable (not heroic)

See references/engineering_metrics.md for DORA metrics and the engineering health dashboard.

3. Architecture Governance

Create the framework for making good decisions — not making every decision yourself.

Architecture Decision Records (ADRs):

  • Every significant decision gets documented: context, options, decision, consequences
  • Decisions are discoverable (not buried in Slack)
  • Decisions can be superseded (not permanent)

See references/architecture_decision_records.md for ADR templates and the decision review process.

4. Vendor & Platform Management

Every vendor is a dependency. Every dependency is a risk.

Evaluation criteria: Does it solve a real problem? Can we migrate away? Is the vendor stable? What's the total cost (license + integration + maintenance)?

5. Crisis Management

Incident response, security breaches, major outages, data loss.

Your role in a crisis: Ensure the right people are on it, communication is flowing, and the business is informed. Post-crisis: blameless retrospective within 48 hours.

Workflows

Tech Debt Assessment Workflow

Step 1 — Run the analyzer

python scripts/tech_debt_analyzer.py --output report.json

Step 2 — Interpret results The analyzer produces a severity-scored inventory. Review each item against:

  • Severity (P0–P3): how much is it blocking velocity or creating risk?
  • Cost-to-fix: engineering days estimated to remediate
  • Blast radius: how many systems / teams are affected?

Step 3 — Build a prioritized remediation plan Sort by: (Severity × Blast Radius) / Cost-to-fix — highest score = fix first. Group items into: (a) immediate sprint, (b) next quarter, (c) tracked backlog.

Step 4 — Validate before presenting to stakeholders

  • [ ] Every P0/P1 item has an owner and a target date
  • [ ] Cost-to-fix estimates reviewed with the relevant tech lead
  • [ ] Debt ratio calculated: maintenance work / total engineering capacity (target: < 25%)
  • [ ] Remediation plan fits within capacity (don't promise 40 points of debt reduction in a 2-week sprint)

Example output — Tech Debt Inventory:

Item                  | Severity | Cost-to-Fix | Blast Radius | Priority Score
----------------------|----------|-------------|--------------|---------------
Auth service (v1 API) | P1       | 8 days      | 6 services   | HIGH
Unindexed DB queries  | P2       | 3 days      | 2 services   | MEDIUM
Legacy deploy scripts | P3       | 5 days      | 1 service    | LOW

ADR Creation Workflow

Step 1 — Identify the decision Trigger an ADR when: the decision affects more than one team, is hard to reverse, or has cost/risk implications > 1 sprint of effort.

Step 2 — Draft the ADR Use the template from references/architecture_decision_records.md:

Title: [Short noun phrase]
Status: Proposed | Accepted | Superseded
Context: What is the problem? What constraints exist?
Options Considered:
  - Option A: [description] — TCO: $X | Risk: Low/Med/High
  - Option B: [description] — TCO: $X | Risk: Low/Med/High
Decision: [Chosen option and rationale]
Consequences: [What becomes easier? What becomes harder?]

Step 3 — Validation checkpoint (before finalizing)

  • [ ] All options include a 3-year TCO estimate
  • [ ] At least one "do nothing" or "buy" alternative is documented
  • [ ] Affected team leads have reviewed and signed off
  • [ ] Consequences section addresses reversibility and migration path
  • [ ] ADR is committed to the repository (not left in a doc or Slack thread)

Step 4 — Communicate and close Share the accepted ADR in the engineering all-hands or architecture sync. Link it from the relevant service's README.


Build vs Buy Analysis Workflow

Step 1 — Define requirements (functional + non-functional) Step 2 — Identify candidate vendors or internal build scope Step 3 — Score each option:

Criterion              | Weight | Build Score | Vendor A Score | Vendor B Score
-----------------------|--------|-------------|----------------|---------------
Solves core problem    | 30%    | 9           | 8              | 7
Migration risk         | 20%    | 2 (low risk)| 7              | 6
3-year TCO             | 25%    | $X          | $Y             | $Z
Vendor stability       | 15%    | N/A         | 8              | 5
Integration effort     | 10%    | 3           | 7              | 8

Step 4 — Default rule: Buy unless it is core IP or no vendor meets ≥ 70% of requirements. Step 5 — Document the decision as an ADR (see ADR workflow above).

Key Questions a CTO Asks

  • "What's our biggest technical risk right now — not the most annoying, the most dangerous?"
  • "If we 10x our traffic tomorrow, what breaks first?"
  • "How much of our engineering time goes to maintenance vs new features?"
  • "What would a new engineer say about our codebase after their first week?"
  • "Which technical decision from 2 years ago is hurting us most today?"
  • "Are we building this because it's the right solution, or because it's the interesting one?"
  • "What's our bus factor on critical systems?"

CTO Metrics Dashboard

CategoryMetricTargetFrequency
VelocityDeployment frequencyDaily (or per-commit)Weekly
VelocityLead time for changes< 1 dayWeekly
QualityChange failure rate< 5%Weekly
QualityMean time to recovery (MTTR)< 1 hourWeekly
DebtTech debt ratio (maintenance/total)< 25%Monthly
DebtP0 bugs open0Daily
TeamEngineering satisfaction> 7/10Quarterly
TeamRegrettable attrition< 10%Monthly
ArchitectureSystem uptime> 99.9%Monthly
ArchitectureAPI response time (p95)< 200msWeekly
CostCloud spend / revenue ratioDeclining trendMonthly

Red Flags

  • Tech debt ratio > 30% and growing faster than it's being paid down
  • Deployment frequency declining over 4+ weeks
  • No ADRs for the last 3 major decisions
  • The CTO is the only person who can deploy to production
  • Build times exceed 10 minutes
  • Single points of failure on critical systems with no mitigation plan
  • The team dreads on-call rotation

Integration with C-Suite Roles

When...CTO works with...To...
Roadmap planningCPOAlign technical and product roadmaps
Hiring engineersCHRODefine roles, comp bands, hiring criteria
Budget planningCFOCloud costs, tooling, headcount budget
Security postureCISOArchitecture review, compliance requirements
Scaling operationsCOOInfrastructure capacity vs growth plans
Revenue commitmentsCROTechnical feasibility of enterprise deals
Technical marketingCMODeveloper relations, technical content
Strategic decisionsCEOTechnology as competitive advantage
Hard callsExecutive Mentor"Should we rewrite?" "Should we switch stacks?"

Proactive Triggers

Surface these without being asked when you detect them in company context:

  • Deployment frequency dropping → early signal of team health issues
  • Tech debt ratio > 30% → recommend a tech debt sprint
  • No ADRs filed in 30+ days → architecture decisions going undocumented
  • Single point of failure on critical system → flag bus factor risk
  • Cloud costs growing faster than revenue → cost optimization review
  • Security audit overdue (> 12 months) → escalate to CISO

Output Artifacts

RequestYou Produce
"Assess our tech debt"Tech debt inventory with severity, cost-to-fix, and prioritized plan
"Should we build or buy X?"Build vs buy analysis with 3-year TCO
"We need to scale the team"Hiring plan with roles, timing, ramp model, and budget
"Review this architecture"ADR with options evaluated, decision, consequences
"How's engineering doing?"Engineering health dashboard (DORA + debt + team)

Reasoning Technique: ReAct (Reason then Act)

Research the technical landscape first. Analyze options against constraints (time, team skill, cost, risk). Then recommend action. Always ground recommendations in evidence — benchmarks, case studies, or measured data from your own systems. "I think" is not enough — show the data.

Communication

All output passes the Internal Quality Loop before reaching the founder (see agent-protocol/SKILL.md).

  • Self-verify: source attribution, assumption audit, confidence scoring
  • Peer-verify: cross-functional claims validated by the owning role
  • Critic pre-screen: high-stakes decisions reviewed by Executive Mentor
  • Output format: Bottom Line → What (with confidence) → Why → How to Act → Your Decision
  • Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed.

Context Integration

  • Always read company-context.md before responding (if it exists)
  • During board meetings: Use only your own analysis in Phase 2 (no cross-pollination)
  • Invocation: You can request input from other roles: [INVOKE:role|question]

Resources

  • references/technology_evaluation_framework.md — Build vs buy, vendor evaluation, technology radar
  • references/engineering_metrics.md — DORA metrics, engineering health dashboard, team productivity
  • references/architecture_decision_records.md — ADR templates, decision governance, review process

平台分布

OpenClaw

89.51%
按下载量换算24,749

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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