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 deciqAI/knowledge-skills --skill 10-10-10git clone --depth 1 https://github.com/deciqAI/knowledge-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/deciqai/knowledge-skills/10-10-10)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/10-10-10"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/10-10-10/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/deciqai/knowledge-skills/10-10-10"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/10-10-10.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 | $0.00140 | $0.01887 |
| Opus 5 | $0.00070 | $0.00944 |
| Sonnet 5 | $0.00028 | $0.00377 |
| Haiku 4.5 | $0.00014 | $0.00189 |
Grade A, and why
10-10-10 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
10-10-10
Overview
Faced with a non-trivial decision, ask three questions: How will I feel in 10 minutes? In 10 months? In 10 years? The three horizons are spaced an order of magnitude apart to surface the systematic bias toward the immediate — hyperbolic discounting — that makes decisions under stress go wrong. Coined by Suzy Welch (2009); the 10-year horizon is operationally identical to Jeff Bezos's regret-minimization framework (1994).
Composes with regret-minimization, second-order-thinking, first-principles, and metacognition.
When to Use
- A personal life decision is being made under emotional pressure
- A career or professional choice has long-term consequences that current anxiety is obscuring
- A relationship decision (start, deepen, end) requires weighing what feels acute vs what will matter
- A high-stakes business call is being made by someone who would benefit from a forced retrospect
- An impulsive action is about to be taken that would feel embarrassing later
- A hard conversation is being deferred because it's uncomfortable now
- Someone says "10-10-10," "regret minimization," "what would future me say," "Suzy Welch," "Bezos framework," "long-term perspective"
Not when: the decision genuinely has no medium- or long-term consequences (which lunch to order); the 10-10-10 frame produces three identical answers (low-stakes — stop deliberating); urgent operational decisions where deliberation cost exceeds the framework's value; decisions someone else has made and you're being asked to ratify.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete case → run The Process directly.
- Coach mode: user is unfamiliar or has no concrete case → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 124 lines · 140 tokens per session scan A 1c057de9e67c
10-10-10 is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 8d ago), licensed MIT. It adds 140 tokens to every session and 1,887 once invoked, about $0.0007 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 2026-08-31.
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