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 tamdogood/builder-essential-skills --skill top-one-percentgit clone --depth 1 https://github.com/tamdogood/builder-essential-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/tamdogood/builder-essential-skills/top-one-percent)<a href="https://agentmods.dev/skills/tamdogood/builder-essential-skills/top-one-percent"><img src="https://agentmods.dev/badge/skills/tamdogood/builder-essential-skills/top-one-percent/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/tamdogood/builder-essential-skills/top-one-percent"><img src="https://agentmods.dev/badge/skills/tamdogood/builder-essential-skills/top-one-percent.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 | $0.00111 | $0.03153 |
| Opus 5 | $0.00056 | $0.01577 |
| Sonnet 5 | $0.00022 | $0.00631 |
| Haiku 4.5 | $0.00011 | $0.00315 |
Grade A, and why
top-one-percent 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Top One Percent
Produce unusually clear understanding and evidence-backed mastery. Treat “top one percent” as a direction and a quality standard, not a percentile promise that cannot be measured.
Follow the Answer-First Contract
Match the response to the user's actual intent:
- Answer a question as a complete explanation. Do not replace the answer with a roadmap, diagnostic, study plan, or quiz.
- Build a mastery system when the user asks to become excellent, requests a curriculum, or wants sustained practice.
- Tutor interactively when the user asks for lessons, exercises, assessment, or ongoing coaching.
- Combine these only when the combination directly serves the request. If the user asks “Why is X special?”, explain X first; a brief learning path may follow only if useful.
Infer the learner's level, goals, and constraints from the request and conversation. State only assumptions that materially affect the answer. Ask at most one high-leverage question when different answers would produce substantially different work; otherwise begin with a sensible default. Personalize examples to the learner's background when known.
Do not force every learning-science technique into every response. Retrieval, diagnostics, spacing, and deliberate practice are valuable for building durable capability, but they must not become friction before a user receives the explanation they asked for.
Route the Request
Select the narrowest useful mode.
| Mode | Trigger | Primary deliverable |
|---|---|---|
| Deep explainer | “What is…?”, “Why…?”, “How…?”, “What is special about…?”, “Teach me…”, “Help me understand…”, comparisons, or requests to learn more | A layered, first-principles explanation that fully answers the question |
| Mastery map | A broad or unfamiliar field | The landscape, important boundaries, prerequisites, specialization choices, and dependency-aware path |
| Learning plan | A defined performance goal, deadline, or weekly capacity | Milestones, practice, resources, evidence, and readiness gates |
| Interactive tutor | A request for a lesson sequence or ongoing teaching | One meaningful unit at a time with explanation, guided work, assessment, and adaptation |
| Practice coach | A request to improve a skill through exercises or feedback | Deliberate drills, quality criteria, critique, revision, and the next drill |
| Diagnostic | An unclear starting level or a request to identify gaps | A short assessment, gap analysis, and revised starting point |
| Capstone review | A request to prove or evaluate capability | A realistic brief, rigorous rubric, review, and improvement loop |
What ships with it
3 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.
- 13d ago First seen · 240 lines · 111 tokens per session scan A 161da0c8ecbd
top-one-percent is a skill published in the GitHub repository tamdogood/builder-essential-skills (197 stars, last pushed 27d ago), licensed MIT. It adds 111 tokens to every session and 3,153 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 2026-08-30.
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