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 guia-matthieu/clawfu-skills --skill regret-minimizationgit clone --depth 1 https://github.com/guia-matthieu/clawfu-skillsWrote 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/guia-matthieu/clawfu-skills/regret-minimization)<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/regret-minimization"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/regret-minimization/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/guia-matthieu/clawfu-skills/regret-minimization"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/regret-minimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00089 | $0.04696 |
| Opus 5 | $0.00044 | $0.02348 |
| Sonnet 5 | $0.00018 | $0.00939 |
| Haiku 4.5 | $0.00009 | $0.00470 |
Grade A, and why
regret-minimization 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 9d 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 — 649 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regret Minimization Framework
Make decisions that your 80-year-old self will thank you for. Master Jeff Bezos' mental model for bold choices that minimize long-term regret.
When to Use This Skill
- Career decisions with long-term implications
- Startup vs. safe job choices
- Major life pivots (relocations, relationships, changes)
- Risk-taking decisions where fear is a factor
- Opportunity evaluation when considering bold moves
- Any decision you'll look back on in 10-20+ years
Methodology Foundation
| Aspect | Details |
|---|---|
| Source | Jeff Bezos - The framework he used to decide to start Amazon in 1994 |
| Core Principle | "Project yourself forward to age 80. Which choice will you regret NOT taking? Minimize regret for inaction on things that matter." |
| Why This Matters | Most people overweight short-term risk and underweight long-term regret. This framework corrects that bias and enables bold, fulfilling decisions. |
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Structures analysis frameworks | Strategic priorities |
| Synthesizes market data | Competitive positioning |
| Identifies opportunities | Resource allocation |
| Creates strategic options | Final strategy selection |
| Suggests implementation approaches | Execution decisions |
What This Skill Does
- Reframes decisions to long-term view - Cuts through short-term fear
- Distinguishes regrets of action vs. inaction - Most regrets are things we didn't do
- Evaluates opportunity uniqueness - Is this a one-time window?
- Assesses downside survivability - Can you recover if it fails?
- Clarifies personal values - What actually matters to you?
- Enables bold action - Gives permission to take calculated risks
How to Use
Evaluate a Major Decision
Apply the regret minimization framework to this decision:
[Describe the choice you're facing]
Help me think through what my 80-year-old self would advise.
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.
- 9d ago First seen · 649 lines · 89 tokens per session scan A 8dee28f46862
regret-minimization is a skill published in the GitHub repository guia-matthieu/clawfu-skills (149 stars, last pushed 5mo ago), licensed MIT. It adds 89 tokens to every session and 4,696 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
ads-creative-development
How to produce ad creative that converts at performance scale. Hook patterns, format selection, video pacing, variation systems, sequential testing methodology, fatigue detection, brand-voice alignment without conversion dilution, and platform-specific creative norms. Triggers on ad creative, ad design, hook patterns…
ads-performance-analytics
How to read paid media dashboards without fooling yourself. Attribution models, platform reporting quirks, multi-platform reconciliation, ROAS vs LTV horizon traps, statistical noise in performance metrics, incrementality testing, and the failure modes that produce expensive lessons. Triggers on read paid media…
paid-media-strategy
A discipline for running paid media that does not light money on fire. Hypothesis writing for paid spend, channel selection, budget allocation, audience targeting, bid strategy, campaign types, what NOT to spend on, attribution reality, and the failure modes that produce expensive lessons. Triggers on paid media…
community-outreach
Systemneutrale Automatisierung für lösungsorientierten Community Outreach und Repo-Recommender in Foren, Reddit und Plattformen nach dem Human-in-the-Loop-Prinzip (EU AI Act konform).
error-log
Apply when learning from a mistake. Central memory of past errors and derived rules; consult before logging a new error to avoid duplicates.
python
Apply when writing Python code. Type hints, error handling, mutable defaults, async patterns, and packaging conventions.