Claude Octopus is an orchestration project that sends research, design, and coding tasks to Claude Code and other AI model providers so their results can be compared. Developers use it for multi-model work, disagreement detection, reviews, persistent context, and an optional workflow that moves from discovery through delivery. The catalogue entries are its commands, skills, agents, instructions, hooks, plugins, and settings.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nyldn/claude-octopus --skill skill-decision-supportgit clone --depth 1 https://github.com/nyldn/claude-octopusWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nyldn/claude-octopus/skill-decision-support)<a href="https://agentmods.dev/skills/nyldn/claude-octopus/skill-decision-support"><img src="https://agentmods.dev/badge/skills/nyldn/claude-octopus/skill-decision-support/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nyldn/claude-octopus/skill-decision-support"><img src="https://agentmods.dev/badge/skills/nyldn/claude-octopus/skill-decision-support.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.02569 |
| Opus 5 | $0.00010 | $0.01285 |
| Sonnet 5 | $0.00004 | $0.00514 |
| Haiku 4.5 | $0.00002 | $0.00257 |
Grade A, and why
skill-decision-support scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 460 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
Phase 2: Generate Options
Step 1: Identify Viable Approaches
Generate 2-4 distinct options (not just variations):
| Option Type | When to Include |
|---|---|
| Conservative | Low risk, proven approach |
| Moderate | Balanced risk/reward |
| Innovative | Higher risk, potentially better outcome |
| Minimal | Simplest possible solution |
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:
### 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]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 460 lines · 20 tokens per session scan A 55f1e78783e2
skill-decision-support is a skill published in the GitHub repository nyldn/claude-octopus (4,058 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 2,569 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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