Cto Plan Reviewer logo

Cto Plan Reviewer

Community
Ibrahim-3d
cto-plan-reviewer

Technical architecture review agent for execution plans. Uses cto-advisor skill to evaluate technical decisions, architecture patterns, tech debt implications, and technology choices in plan.md. Triggered by: 'review technical plan', 'cto review', 'architecture review', or automatically during Step 2 (Evaluate Plan) for tracks involving architecture decisions, integrations, or infrastructure changes.

Overview

PublisherIbrahim-3d
Repositoryorchestrator-supaconductor
Skill namecto-plan-reviewer
Stars
378
Forks
38
Bundled files
Instructions only
LicenseAGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Ibrahim-3d on GitHub. Read the source before you install it.

Installation

Install the Cto Plan Reviewer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Ibrahim-3d/orchestrator-supaconductor.git /tmp/orchestrator-supaconductor
mkdir -p .claude/skills
cp -r /tmp/orchestrator-supaconductor/skills/cto-plan-reviewer .claude/skills/cto-plan-reviewer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cto Plan Reviewer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cto Plan Reviewer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cto Plan Reviewer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CTO Plan Reviewer -- Technical Architecture Review

This agent provides CTO-level technical review of execution plans before implementation begins. It catches architectural issues, tech debt accumulation, and suboptimal technology choices during the planning phase.

When to Use

Automatically invoked during Step 2: EVALUATE PLAN when the track involves:

  • Architecture decisions or changes
  • Technology selection or integration
  • Infrastructure setup or changes
  • Database schema or migrations
  • API design or contracts
  • Scalability or performance concerns
  • Security-critical implementations

Also manually invocable via:

bash
claude /cto-advisor

Inputs Required

  1. Track's plan.md -- execution plan to review
  2. Track's spec.md -- requirements and context
  3. conductor/tech-stack.md -- current technology decisions
  4. conductor/product.md -- product requirements and constraints
  5. Codebase state -- existing architecture patterns

Review Framework

The agent leverages the cto-advisor skill to perform deep technical analysis across multiple dimensions:

1. Architecture Review

CheckUses CTO Advisor For
Architecture patternsEvaluate proposed patterns against team topologies, scalability needs
Design decisionsADR template guidance, decision documentation quality
System designComponent boundaries, separation of concerns, modularity
Technology standardsAlignment with existing stack, consistency

CTO Advisor Frameworks Used:

  • Architecture Decision Records (ADRs)
  • System Design Review checklist
  • Technology Standards evaluation

2. Tech Debt Assessment

CheckUses CTO Advisor For
Debt introductionWill this plan create technical debt? Quantify and justify
Debt mitigationIf debt is introduced, is there a paydown plan?
Complexity analysisIs the approach over-engineered or under-engineered?
Maintenance burdenLong-term ownership and maintenance implications

CTO Advisor Tools Used:

  • Tech Debt Analyzer framework
  • Tech Debt Strategy (40/25/15 allocation)
  • Red flags checklist

3. Technology Evaluation

CheckUses CTO Advisor For
Technology choicesAre new libraries/services necessary and well-justified?
Vendor dependenciesLock-in risk, SLA monitoring, cost implications
Integration complexityAPI design, error handling, retry logic
Cost implicationsInfrastructure costs, API usage costs, scaling costs

CTO Advisor Frameworks Used:

  • Technology Evaluation Framework (4-week process)
  • Vendor Management checklist
  • Cost optimization principles

4. Engineering Excellence

CheckUses CTO Advisor For
Testing strategyCoverage targets, test types, TDD applicability
Performance criteriaLoad requirements, optimization strategy
Security reviewOWASP top 10, input validation, auth patterns
ObservabilityMonitoring, logging, alerting, debugging

CTO Advisor Metrics Used:

  • DORA Metrics targets (deployment frequency, lead time, MTTR, CFR)
  • Quality Metrics (test coverage >80%, code review 100%, tech debt <10%)
  • Success Indicators checklist

5. Team & Process

CheckUses CTO Advisor For
Complexity appropriatenessCan the team execute this plan effectively?
Knowledge distributionSingle points of failure in knowledge?
Onboarding impactWill this make onboarding harder?
Documentation needsWhat documentation is required for maintainability?

CTO Advisor Principles Used:

  • Team Topologies
  • Engineering metrics (sprint velocity, unplanned work <20%)
  • Communication templates

Review Process

Step 1: Load Context

Use context-loader skill to efficiently load:

  1. Track's plan.md and spec.md
  2. conductor/tech-stack.md -- current stack decisions
  3. conductor/product.md -- product constraints
  4. Recent architectural decision files or ADRs
  5. Existing component/module patterns in codebase

Step 2: Invoke CTO Advisor Frameworks

For each technical aspect of the plan, invoke relevant cto-advisor frameworks:

For architecture decisions:
- Apply ADR template guidance
- Check system design review criteria
- Validate against technology standards

For tech debt concerns:
- Run tech debt analyzer concepts
- Apply debt strategy allocation principles
- Check red flags

For new technologies:
- Apply technology evaluation framework
- Assess vendor management needs
- Calculate cost implications

For quality:
- Check against DORA metrics targets
- Verify testing strategy
- Validate security checklist

Step 3: Generate Technical Review Report

markdown
## CTO Technical Review Report

**Track**: [track-id]
**Reviewer**: cto-plan-reviewer (using cto-advisor frameworks)
**Date**: [YYYY-MM-DD]

### Architecture Assessment

#### Design Decisions
- [x] Architecture pattern: [pattern name] -- appropriate for [reason]
- [ ] CONCERN: [specific issue with decision]
- Recommendation: [specific guidance from ADR framework]

#### System Design
- [x] Component boundaries clear and well-defined
- [x] Separation of concerns maintained
- [ ] CONCERN: Tight coupling between [module A] and [module B]
- Recommendation: [refactoring suggestion]

### Tech Debt Analysis

#### Debt Introduction: [NONE / LOW / MEDIUM / HIGH]
- Debt items introduced:
  1. [Description] -- Severity: [Critical/High/Medium/Low] -- Justification: [why necessary]
  2. [Description] -- Severity: [level] -- Justification: [reason]

#### Mitigation Plan
- [ ] Debt paydown plan required: [yes/no]
- [ ] Capacity allocated: [percentage] -- Aligns with cto-advisor 40/25/15 strategy: [yes/no]

### Technology Evaluation

#### New Dependencies
| Library/Service | Necessity | Alternatives Considered | Lock-in Risk | Cost Impact |
|----------------|-----------|------------------------|--------------|-------------|
| [name] | [justified] | [yes/no - list] | [low/med/high] | [amount/impact] |

#### Integration Assessment
- API design: [quality assessment]
- Error handling: [adequate/needs improvement]
- Retry logic: [present/missing]
- Cost monitoring: [planned/missing]

### Engineering Excellence

#### Testing Strategy: [STRONG / ADEQUATE / WEAK]
- Coverage targets: [percentage] -- Meets cto-advisor 80% threshold: [yes/no]
- TDD applicability: [high/medium/low] -- Justification: [reason]
- Test types planned: [unit/integration/e2e]

#### Performance Criteria: [DEFINED / VAGUE / MISSING]
- Load requirements: [specified/missing]
- Optimization strategy: [present/absent]

#### Security Review: [PASS / NEEDS ATTENTION]
- OWASP top 10 considered: [yes/no]
- Input validation: [planned/missing]
- Auth patterns: [appropriate/needs review]

#### Observability: [COMPREHENSIVE / BASIC / MISSING]
- Monitoring: [planned/missing]
- Logging: [planned/missing]
- Alerting: [planned/missing]

### Team & Process

#### Execution Feasibility: [HIGH / MEDIUM / LOW]
- Team capability match: [assessment]
- Knowledge distribution: [good/concerning]
- Onboarding impact: [low/medium/high]

#### Documentation Plan: [ADEQUATE / NEEDS EXPANSION]
- Technical docs needed: [list]
- ADR required: [yes/no]
- Onboarding docs: [needed/not needed]

### Red Flags

[List any critical concerns from cto-advisor red flags checklist]:
- Increasing technical debt without paydown plan
- Vendor lock-in without escape hatch
- Security vulnerabilities introduced
- Performance bottlenecks designed in
- Tight coupling reducing maintainability

### DORA Metrics Impact Assessment

| Metric | Current Target | Impact of Plan | Assessment |
|--------|---------------|----------------|------------|
| Deployment Frequency | >1/day | [positive/neutral/negative] | [explanation] |
| Lead Time | <1 day | [positive/neutral/negative] | [explanation] |
| MTTR | <1 hour | [positive/neutral/negative] | [explanation] |
| Change Failure Rate | <15% | [positive/neutral/negative] | [explanation] |

### Recommendations

#### Must Fix (Blocking Issues)
1. [Critical issue] -- [specific action required]
2. [Critical issue] -- [specific action required]

#### Should Consider (Improvements)
1. [Suggestion] -- [benefit]
2. [Suggestion] -- [benefit]

#### Nice to Have (Enhancements)
1. [Enhancement] -- [optional benefit]

### Verdict

**Technical Review**: [PASS / PASS WITH CONDITIONS / FAIL]

**PASS**: Technical approach is sound, no blocking issues
**PASS WITH CONDITIONS**: Approved, but recommendations must be addressed during execution
**FAIL**: Blocking issues must be resolved before execution begins

**Rationale**: [1-2 sentence summary of verdict reasoning]

Handoff Protocol

If PASS or PASS WITH CONDITIONS

  • Technical review complete
  • Append this report to the track's plan.md under "## Technical Review"
  • Continue to other plan evaluation checks (scope, overlap, dependencies)
  • If ALL evaluations pass -> Conductor dispatches loop-executor

If FAIL

  • Return to loop-planner with specific technical fixes required
  • Planner revises plan addressing CTO concerns
  • Re-run technical review after revision
  • Max 2 revision cycles before escalating to user for architectural decision

Integration with Evaluate-Loop

This agent is automatically invoked by conductor-orchestrator during Step 2 (EVALUATE PLAN) when the track's spec.md or plan.md contains technical architecture keywords:

Trigger Keywords:

  • Architecture, system design, integration, API, database, schema, migration, infrastructure, scalability, performance, security, authentication, authorization, deployment, monitoring, logging, vendor, technology selection, framework, library

Invocation:

conductor-orchestrator -> detects technical track -> dispatches cto-plan-reviewer -> receives report -> includes in plan evaluation -> proceeds or blocks

Supporting Skills

This agent uses:

  • cto-advisor -- Core technical leadership frameworks and tools
  • context-loader -- Efficient project context loading
  • plan-critiquer -- Deep strategic critique (when architectural decisions require strategic analysis)

Success Criteria

A successful technical review:

  1. Catches architectural issues before code is written
  2. Prevents tech debt accumulation without justification
  3. Ensures technology choices are well-reasoned
  4. Validates testing and quality strategy
  5. Provides actionable recommendations with specific guidance from CTO advisor frameworks
  6. Enables confident execution by addressing technical concerns upfront

Example Usage

Manual invocation:

bash
# User wants technical review of current plan
claude /cto-advisor

# Agent loads plan.md, applies cto-advisor frameworks, generates technical review report

Automatic invocation:

bash
# User runs conductor implement
/conductor implement

# Conductor detects Step 2 (Evaluate Plan) + technical track -> automatically calls cto-plan-reviewer
# Report generated -> included in plan evaluation -> execution proceeds or blocks

Frequently asked questions

What does the Cto Plan Reviewer AI skill do?

Technical architecture review agent for execution plans. Uses cto-advisor skill to evaluate technical decisions, architecture patterns, tech debt implications, and technology choices in plan.md. Triggered by: 'review technical plan', 'cto review', 'architecture review', or automatically during Step 2 (Evaluate Plan) for tracks involving architecture decisions, integrations, or infrastructure changes.

Why use Cto Plan Reviewer on TypingMind?

Because you install it once and use it with any model. Cto Plan Reviewer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cto Plan Reviewer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Ibrahim-3d/orchestrator-supaconductor/tree/master/skills/cto-plan-reviewer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cto Plan Reviewer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cto Plan Reviewer?

As many as you like. As long as a model supports skills, you can use Cto Plan Reviewer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cto Plan Reviewer AI skill free?

Yes. It is published on GitHub by Ibrahim-3d under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇