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 human-avatar/skills-for-humanity --skill s4h-decision-reversibility-analysisgit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-decision-reversibility-analysis)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-decision-reversibility-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-decision-reversibility-analysis/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/human-avatar/skills-for-humanity/s4h-decision-reversibility-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-decision-reversibility-analysis.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 | $0.00064 | $0.01134 |
| Opus 5 | $0.00032 | $0.00567 |
| Sonnet 5 | $0.00013 | $0.00227 |
| Haiku 4.5 | $0.00006 | $0.00113 |
Grade A, and why
s4h-decision-reversibility-analysis 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 13d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision Reversibility Analysis
Most people apply the same amount of thinking to every decision. This is wrong in both directions: it produces analysis paralysis on easy reversible choices, and recklessness on decisions that cannot be undone. The right question before deciding is not "what should I choose?" — it is "how much should I invest in choosing?"
Your Process
Step 1: State the Decision Write the decision clearly. Include what is actually being committed to — not the framing, the underlying commitment.
Framing check: Confirm the decision and its underlying commitment before continuing. State what you've identified — the actual decision being assessed and what would be locked in if made — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the decision and its underlying commitment]. Is that right?"
- Header: "Framing"
- Options:
- Yes — proceed — framing is correct
- Adjust — one element is off; user will correct it before you continue
- Reframe — different decision than read; incorporate the correction before proceeding
Step 2: Assess Reversal Cost If this decision turns out to be wrong, how expensive is it to undo? Consider: financial cost, time cost, relationship or trust cost, technical debt introduced, market position lost, and optionality foreclosed. Be concrete — not "expensive" but "six months of re-architecture and two broken partnerships."
Step 3: Classify — Type 1 or Type 2
- Type 1 (one-way door): reversing is very costly or practically impossible. Wrong here means significant, durable damage.
- Type 2 (two-way door): can be walked back at low cost if wrong. A review point or small experiment can reveal the error before it compounds.
Step 4: Apply the Appropriate Process
- Type 1: slow down. Consult broadly. Surface dissent. Apply full analytical rigour. Set explicit criteria for what "good" looks like before committing.
- Type 2: decide quickly. Set a review point. Move. Do not let this consume the time budget of a Type 1 decision.
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.
- 13d ago First seen · 112 lines · 64 tokens per session scan A e3001afb842c
s4h-decision-reversibility-analysis is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,134 once invoked, about $0.0003 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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