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 agentmods add skills/3243dwon/clear-eye/second-ordernpx skills add 3243dwon/clear-eye --skill second-ordergit clone --depth 1 https://github.com/3243dwon/clear-eyeWhat 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 | $0.00157 | $0.00847 |
| Opus 5 | $0.00078 | $0.00424 |
| Sonnet 5 | $0.00031 | $0.00169 |
| Haiku 4.5 | $0.00016 | $0.00085 |
Grade A, and why
second-order 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 2d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Second-Order Thinking
Most analysis stops at the first consequence. The edge is in the second, third, and long-tail effects — and in who quietly wins or loses once everyone adapts.
Core principle
First-order thinking asks "what happens?" Second-order thinking asks "...and then what? — and then what?"
Every effect becomes a new cause. People and markets react to the first consequence, and the reaction is often where the real story is.
The process
- Name the change. State the decision or event precisely.
- First order. The immediate, intended effect. (Usually obvious — get it on the table fast.)
- Second order. How do the affected parties respond to that first effect? Incentives shift; people route around constraints; prices and behavior adjust.
- Third order and beyond. What do those responses cause? Keep asking "and then what?" until the chain goes speculative — then stop and say so.
- Winners & losers. After everyone adapts, who is better and worse off? Look hard for the non-obvious ones — the party nobody mentioned.
- Reflexivity & time. What second-order effect partially cancels (or amplifies) the first? What only appears over months or years?
Output format
- The change — one line.
- The cascade — first → second → third, as a short chain (or a couple of chains if it branches). Mark where confidence drops.
- Non-obvious winners & losers — the ones first-order analysis misses.
- The effect most people will underweight — your single highest-value call.
- Confidence — flag which links are solid vs. speculative.
Worked example
Change: A city introduces rent control on large apartment buildings.
First order: Existing tenants in covered units pay less. (Intended.)
Second order: Landlords cut maintenance on price-capped units (margin is squeezed), and some convert rentals to condos to exit the regime. New construction of covered buildings slows — why build what you can't price?
Third order: Rental supply tightens; uncovered and new units get more expensive; mobility drops as tenants cling to below-market leases, which gums up the whole market.
Non-obvious winners/losers: Winners — incumbent long-tenured renters; condo converters; owners of uncovered buildings (pricing power). Losers — newcomers to the city, future renters, and (slowly) the housing stock itself.
Most underweighted effect: The supply chill is invisible for years, then dominant — by the time it's obvious, it's structural.
Confidence: First/second order high (well-documented); third-order magnitude medium.
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.
- 2d ago First seen · 60 lines · 157 tokens per session scan A 869f06d35189
second-order is a skill published in the GitHub repository 3243dwon/clear-eye (1 stars, last pushed 3mo ago), licensed MIT. It adds 157 tokens to every session and 847 once invoked, about $0.0008 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.
Other skills, from other repositories
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thinking-red-team
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thinking-scientific-method
When a symptom has several plausible causes, rank falsifiable hypotheses and run the cheapest discriminating observation first; prefer least-assumptive survivors only after evidence fit.
thinking-systems
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thinking-circle-of-competence
Use when a specific claim may lack grounding. Check evidence boundary, size wrongness cost, then answer, fetch, or abstain — never confabulate.
thinking-five-whys-plus
When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.