Skip to content
Automation
Skill

/skill-decision-support

Present options with trade-offs for informed decision-making — use when choosing between approaches

From plugin
octo
4.3k70 skills49 agents53 commands18 hooks

Claude Code

$ npx -y skills add nyldn/claude-octopus --skill skill-decision-support --agent claude-code

SKILL.md

skill-decision-support.SKILL.md
name: skill-decision-support
description: "Present options with trade-offs for informed decision-making — use when choosing between approaches"
disable-model-invocation: true

> **Host: Codex CLI** — This skill was designed for Claude Code and adapted for Codex. > Cross-reference commands use installed skill names in Codex rather than `/octo:*` slash commands. > Use the active Codex shell and subagent tools. Do not claim a provider, model, or host subagent is available until the current session exposes it. > For host tool equivalents, see `skills/blocks/codex-host-adapter.md`.

Decision Support & Options Presentation

Overview

Structured approach to presenting options and alternatives with clear trade-offs, enabling informed decision-making.

**Core principle:** Understand context → Generate options → Analyze trade-offs → Present clearly → Support choice.

When to Use

**Use this skill when user:**

  • Asks for options or alternatives
  • Says "fix or provide options"
  • Needs help deciding between approaches
  • Wants to see different ways to solve a problem
  • Is uncertain about best path forward

**Do NOT use for:**

  • General research ("what is X?") → use flow-probe
  • Implementation work → use flow-tangle
  • Simple yes/no questions
  • Already-decided approaches

The Process

Phase 1: Context Understanding

Step 1: Understand the Decision Point

**Decision Context:**

What needs to be decided: [the core question]
Why it matters: [impact of this decision]
Constraints: [time, resources, compatibility, etc.]
Current state: [what exists now]

Step 2: Gather Requirements

Use AskUserQuestion if needed to understand:

  • Must-have requirements
  • Nice-to-have features
  • Deal-breakers
  • Timeline constraints
  • Budget/resource constraints

Step 3: Set the decision criteria before scoring

Choose criteria, scoring definitions and weights before evaluating the options. Use the user's stated priorities. If priorities are missing, state the assumed weights and the effect those assumptions may have. Weights must total 100%. Keep the same criteria and weights for every option. Do not change them to make a preferred option win; record any later revision and rescore all options.

Phase 2: Generate Options

Step 1: Identify Viable Approaches

Generate 2-4 distinct options, including the status quo. Always include doing nothing as the comparison baseline and state its cost, risks and consequences of delay. If it violates a requirement, retain it for comparison and explain why it is not viable. Do not assume that changing something is beneficial.

| Option Type | When to Include | |-------------|-----------------| | **Status quo / do nothing** | Always; include its ongoing cost and cost of delay | | **Conservative** | Low risk, proven approach | | **Moderate** | Balanced risk/reward | | **Innovative** | Higher risk, potentially better outcome | | **Minimal** | Simplest possible solution |

**Except for the required status-quo baseline, don't generate options that:**

  • Violate stated constraints
  • Are clearly inferior to others
  • Are essentially the same with minor tweaks

Step 2: Research Each Option

For each option, understand:

  • How it works
  • What it requires
  • What the outcome looks like
  • What could go wrong

Phase 3: Trade-off Analysis

For each option, analyze the trade-offs below, then score it against the criteria and weights set in Phase 1. Show raw scores beside weighted scores and the total. Label uncertain inputs and assumptions; do not invent measurements to fill a scoring table. Choose the recommendation only after this analysis, with reasons that refer to the user's requirements and the comparison baseline.

### Option N: [Name]

**Description:**
[1-2 sentence description]

**Pros:**
- ✅ [Advantage 1]
- ✅ [Advantage 2]
- ✅ [Advantage 3]

**Cons:**
- ❌ [Disadvantage 1]
- ❌ [Disadvantage 2]
- ❌ [Disadvantage 3]

**Effort:** [Low/Medium/High]
**Risk:** [Low/Medium/High]
**Reversibility:** [Easy/Moderate/Difficult to undo]

**Best for:** [when this option makes sense]

Optional scenario stress test

For a decision that depends on uncertain assumptions, select the two drivers with the most uncertainty and impact. Describe three or four plausible futures and check how each option performs in each. Report which option holds up across the futures and which assumptions would change the recommendation. Keep this optional; do not add provider calls without the user's existing authorization.

Phase 4: Present Options

Format for Presentation

Omit unused option sections and table columns when presenting fewer than four options.

# Decision: [What needs to be decided]

**Context:** [Brief summary of why this decision is needed]


## Option 1: [Option name]

**What it is:**
[Clear explanation in 1-2 sentences]

**Pros:**
- ✅ [Pro 1]
- ✅ [Pro 2]
- ✅ [Pro 3]

**Cons:**
- ❌ [Con 1]
- ❌ [Con 2]

**Implementation:**
[Brief overview of what's involved]

**Timeline:** [estimate]
**Risk Level:** Low/Medium/High


## Option 2: [Option name]

[Same structure as Option 1]


## Option 3: [Option name, if needed]

[Same structure as Option 1]


## Option 4: [Option name, if needed]

[Same structure as Option 1]


## Quick Comparison

| Criteria | Option 1 | Option 2 | Option 3 | Option 4 |
|----------|----------|----------|----------|----------|
| Effort | [level] | [level] | [level] | [level] |
| Risk | [level] | [level] | [level] | [level] |
| Reversible | [yes/no] | [yes/no] | [yes/no] | [yes/no] |
| Timeline | [time] | [time] | [time] | [time] |
| Best for | [scenario] | [scenario] | [scenario] | [scenario] |

## Criteria and scores

| Criterion | Weight | Option 1 raw / weighted | Option 2 raw / weighted | Option 3 raw / weighted | Option 4 raw / weighted |
|-----------|--------|-------------------------|-------------------------|-------------------------|-------------------------|
| [Criterion fixed bef
Read more
@nyldn
Ships withocto

Every AI model has blind spots. Claude Octopus supports twelve external provider integrations — Codex, Antigravity CLI, Copilot, Qwen, Ollama, Perplexity, OpenRouter, OrcaRouter, OpenCode, Cursor CLI, Grok, and Kimi Code — alongside the built-in Claude Code

4.3k70 skills49 agents
Get the whole plugin

Stars on GitHub

Momentum

stars in total
4.3k
Star history of nyldn/claude-octopus on GitHub, a chart by star-history.com

Other skills on octo.

extract-skill

extract-skill

Reverse-engineer design systems, tokens, and components from live products or screenshots

@nyldn@nyldnInstall Skill
flow-define

flow-define

Multi-AI requirements scoping using available external providers (Double Diamond Define phase). Priority triggers: octo define,…

@nyldn@nyldnInstall Skill
flow-deliver

flow-deliver

Multi-AI validation, scoring, and review using available external providers (Double Diamond Deliver phase)

@nyldn@nyldnInstall Skill
flow-develop

flow-develop

Multi-AI implementation using available external providers (Double Diamond Develop phase). DO NOT use for simple code edits,…

@nyldn@nyldnInstall Skill
flow-discover

flow-discover

Multi-AI research using available external providers (Double Diamond Discover phase)

@nyldn@nyldnInstall Skill
flow-parallel

flow-parallel

Decompose and execute large changes, migrations, or multi-issue fixes in parallel with quality gates

@nyldn@nyldnInstall Skill

More skills from other plugins.

agent-builder

agent-builder

Load immediately after an Agent intent, before the first agent_builder_* call. Governs how you create, configure, test, and…

n8n11d209k
@n8n-io@n8n-ioInstall Skill
browser-use

browser-use

Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…

@browser-use@browser-useInstall Skill
agent-browser

agent-browser

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling…

@vercel-labs-2@vercel-labs-2Install Skill
add-anydoc

add-anydoc

Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when…

@nanocoai@nanocoaiInstall Skill

Questions about skill-decision-support.

Which coding agents can use skill-decision-support?
skill-decision-support installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.