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 gravity-field-empowermentgit 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/gravity-field-empowerment)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/gravity-field-empowerment"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/gravity-field-empowerment/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/gravity-field-empowerment"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/gravity-field-empowerment.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 | $0.00117 | $0.01928 |
| Opus 5 | $0.00059 | $0.00964 |
| Sonnet 5 | $0.00023 | $0.00386 |
| Haiku 4.5 | $0.00012 | $0.00193 |
Grade A, and why
gravity-field-empowerment 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 8d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gravity Field Empowerment
Overview
Most improvement frameworks measure interventions by immediate effect — quarter-over-quarter lift, year-one ROI. This systematically undervalues interventions that produce permanent velocity changes vs. point-in-time additions. A consulting engagement adding $1M this year looks identical in a snapshot to one that permanently raises growth velocity 3 points — but over 10 years the compounded difference can be 10x.
The framework applies General Relativity: a gravitational field accelerates objects passing through it, leaving them at a permanently higher velocity afterward. The value of empowerment is the integral — cumulative area between empowered and baseline trajectory over all future time (the integral effect).
Compose with [second-order-thinking] (map downstream consequences of velocity change) · [margin-of-safety] (survive the intervention's cost) · [s-curve-technology-adoption] (identify which S-curve the business is on).
When to Use
- Evaluating a major transformation (leadership, strategy, capital raise, org restructure) by long-term velocity, not short-term lift
- Diagnosing whether a past intervention produced a velocity change or merely an addition
- Choosing between competing empowerment options based on integral effect, not immediate cost
- Business has had repeated transformations with no lasting effect
When NOT to use: Survival horizon < integral materialization window · Baseline velocity unmeasurable · Evaluation horizon < 18 months · Justifying pre-decided programs.
Coaching Novices (Adaptive Front Door)
Engine mode: user has a concrete case → run The Process directly. Coach mode: user is unfamiliar → 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-it-is: "Gravity field model distinguishes additions (revenue up in one period) from velocity changes (growth rate permanently higher). This framework identifies which interventions change the engine, not just fill the tank — the integral effect."
- Check fit: "What is your current baseline growth velocity — revenue or key metric — and what is it vs. 12 months ago?"
- Elicit the real case: "Name a specific transformation you've implemented or are considering. Was it an addition or a velocity change?"
[WAIT — do not advance until user responds]
- Run The Process: "Measure growth velocity before and 12-18 months after the empowerment ends. Which of the eight levers did it engage?"
[WAIT — do not advance until user responds]
- Name the insight: "Which lever would create a permanent 3-5% velocity increase right now? What is the 5-year integral effect worth in dollars?"
[WAIT — do not advance until user responds]
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.
- 8d ago First seen · 106 lines · 117 tokens per session scan A a6fc21543722
gravity-field-empowerment is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 117 tokens to every session and 1,928 once invoked, about $0.0006 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.
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