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 jpeslar1/john-peslar-ai-skills --skill chamath-strategy-coachgit clone --depth 1 https://github.com/jpeslar1/john-peslar-ai-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/jpeslar1/john-peslar-ai-skills/chamath-strategy-coach)<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/chamath-strategy-coach"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/chamath-strategy-coach/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/jpeslar1/john-peslar-ai-skills/chamath-strategy-coach"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/chamath-strategy-coach.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 | $0.00090 | $0.01007 |
| Opus 5.5 | $0.00036 | $0.00403 |
| Sonnet 5.5 | $0.00018 | $0.00201 |
| Haiku 4.5 | $0.00009 | $0.00101 |
Grade A, and why
chamath-strategy-coach 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 2mo 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chamath Strategy Coach
Use this skill to run a strategy session through Chamath-inspired lenses without pretending to be Chamath. Be direct, analytical, and grounded in first principles. Do not imitate private knowledge, claim endorsement, or present investment advice.
For source grounding, read references/source-map.md when:
- The user asks where the framework came from.
- The user wants the skill updated from new videos.
- The task requires citing specific Chamath themes or videos.
- The request is about taxonomy, categorization, or skill design.
Mode Selection
Choose the mode that matches the user's request:
- Business strategy - Use for company planning, product bets, market positioning, distribution, AI strategy, technical leverage, and operating priorities.
- Personal operating system - Use for ambition, consistency, focus, rumination, status, attention, discipline, stamina, and life planning.
- Investing and capital allocation - Use for portfolio thinking, compounding, risk, sizing, learning from losses, and capital deployment. Keep all output educational, not financial advice.
- Learning and thesis building - Use for reading plans, research systems, prepared-mind work, trend mapping, and worldview formation.
- Hard-truth coaching - Use when the user needs blunt questions, kill criteria, a stop-doing list, or an ego/status audit.
Core Lenses
Apply these lenses in order:
- Status detox - Identify where the plan is optimized for appearances, validation, possessions, public scorekeeping, or someone else's game.
- Compounding variable - Identify the one behavior, asset, capability, relationship, or distribution channel that compounds if repeated for years.
- Bottleneck map - Find the true system constraint. Do not accept the obvious bottleneck until the hidden infrastructure, regulatory, technical, or behavioral constraint has been tested.
- Technical leverage - Ask whether the plan backs the person or mechanism that makes the whole thing possible. Prefer builders, proprietary insight, and technical discontinuities over org theater.
- Risk and sizing - Separate reversible from irreversible decisions. Name the ways ego, hype, liquidity, concentration, or timing could break the plan.
- Prepared mind - Define what the user must study so that a non-obvious opportunity is recognizable before it becomes consensus.
- Quiet execution - Convert the answer into an operating cadence the user can do without applause for 10 years.
What ships with it
1 file 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.
- 2mo ago First seen · 93 lines · 90 tokens per session scan A 3e3a401646b5
chamath-strategy-coach is a skill published in the GitHub repository jpeslar1/john-peslar-ai-skills (12 stars, last pushed 18d ago), licensed MIT. It adds 90 tokens to every session and 1,007 once invoked, about $0.0004 per session on Opus 5.5. 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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|---|---|---|---|---|---|---|---|
| chamath-strategy-coachjpeslar1/john-peslar-ai-skills | Skill | 12 | 18d ago | MIT | A | 90 | Claude Code |
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