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 hidden-elite-advantagesgit 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/hidden-elite-advantages)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/hidden-elite-advantages"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/hidden-elite-advantages/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/hidden-elite-advantages"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/hidden-elite-advantages.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 | $0.00112 | $0.01815 |
| Opus 5 | $0.00056 | $0.00907 |
| Sonnet 5 | $0.00022 | $0.00363 |
| Haiku 4.5 | $0.00011 | $0.00181 |
Grade A, and why
hidden-elite-advantages 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hidden Elite Advantages
Overview
Top performers' results stem from nine hidden advantage dimensions — not visible actions. Replicability differs radically: largely learnable (🟢), partially imitable (🟡), or talent/network-dependent (🔴). The Matthew Effect (Merton, 1968) explains why early advantage compounds non-linearly. Most development programs waste effort on unteachable (red) dimensions while neglecting green ones. Use as a targeting instrument: concentrate on green/yellow gaps, design around red.
Cross-skill composition: AFTER [three-radius-model] (skills-2) to map specific gaps. BEFORE [okr-goal-setting] to set goals only on learnable dimensions. WITH [non-consensus-thinking] (skills-2) for what elite contrarian thinking actually looks like.
When to Use
- Designing a personal development plan — need to distinguish investable vs. structurally constrained dimensions
- Studying elite performers — identify which advantages are replicable vs. path-dependent
- Coaching someone — direct effort to highest-leverage learnable dimensions
- Evaluating a hire or partner — map advantage profile against your gaps
When NOT to use: Immediate performance improvement needed; no performance history; using it to rationalize inaction ("I lack the right network").
Coaching Novices (Adaptive Front Door)
Engine mode: user has a concrete case → run The Process directly. Coach mode: user unfamiliar or 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 it is: Nine behind-the-surface dimensions drive elite results — three replicability levels; developing the wrong ones is wasted effort.
- Check fit: Do you have a specific elite performer you're studying and real domain performance data?
- Elicit the real case: Which elite performer? Which of their visible results look like talent but might be decades of green-dimension practice?
[WAIT — do not advance until user responds]
- Run The Process: Rate yourself on green dimensions (mental models, tactics) first. Where is your biggest gap vs. your domain's top performers?
[WAIT — do not advance until user responds]
- Close: Once you've categorized green/yellow/red in your domain, you can stop trying to develop unteachable advantages and concentrate where compound learning is possible.
[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.
- 9d ago First seen · 123 lines · 112 tokens per session scan A 7b49515f467e
hidden-elite-advantages is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 112 tokens to every session and 1,815 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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