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 arrow-information-paradoxgit 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/arrow-information-paradox)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/arrow-information-paradox"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/arrow-information-paradox/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/arrow-information-paradox"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/arrow-information-paradox.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 138 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00255 | $0.05318 |
| Opus 5 | $0.00128 | $0.02659 |
| Sonnet 5 | $0.00051 | $0.01064 |
| Haiku 4.5 | $0.00026 | $0.00532 |
Grade A, and why
arrow-information-paradox 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 12d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arrow's Information Paradox
Overview
You have something valuable to sell — a technology, a formula, a method, a dataset, a research result. A buyer wants to know what it is worth before paying. But to judge its worth, they must know what it is. And the moment they know what it is, they have already received it — for free. You have nothing left to sell. This is Arrow's information paradox, stated by Nobel laureate Kenneth J. Arrow in 1962:
"there is a fundamental paradox in the determination of demand for information; its value for the purchaser is not known until he knows the information, but then he has in effect acquired it without cost." — Kenneth J. Arrow (1962), Economic Welfare and the Allocation of Resources for Invention
Arrow traced the paradox to three problematic properties that make information behave unlike an ordinary good. It is indivisible — you cannot sell a fractional peek that conveys proportional value; the useful unit is often the whole thing. It is inappropriable — once disclosed it is non-excludable and non-rivalrous; the buyer's use does not diminish yours, and you cannot easily stop them (or others) from using it without paying. And it is subject to uncertainty — neither party knows in advance what the information will be worth, and the seller cannot credibly resolve that uncertainty for the buyer without dissolving the sale. The whole discipline of this skill is the executable move that follows: choose the mechanism that lets the buyer estimate value while the seller retains appropriability. The standard mechanisms are patents/IP, non-disclosure agreements, staged (partial) disclosure, trusted third-party intermediaries with escrow, reputation, and demonstrating value on a proxy (redacted samples, blind evaluations). Akerlof (1970) later showed the market-failure cousin — when no such mechanism exists, quality-uncertain markets can collapse to lemons.
Compose with neighbors. Use signaling-games after this skill when the problem narrows from "how do I disclose without leaking" to "how do I credibly reveal quality without full disclosure" — signaling supplies the single-crossing test for a costly, hard-to-fake proof (a working demo, a warranty, escrowed source). Use principal-agent instead of this skill when the information asymmetry lives inside an ongoing relationship (you already transact; the question is hidden action/hidden type between principal and agent), not at the one-shot gate of a sale. Use batna-zopa alongside staged disclosure in a deal negotiation — each disclosure stage is a concession that should be traded for a reciprocal commitment, and your walk-away is what a broken NDA cannot recover. Use economic-moat before you choose patent-vs-secret, because the disclosure-24-month-into-a-published-patent decision is a moat-durability decision, not just a deal tactic. Use winners-curse from the buyer's seat — a buyer forced to value an asset under the seller's private information should price the adverse selection of what they were not shown.
What ships with it
5 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.
- 12d ago First seen · 163 lines · 255 tokens per session scan A 2e587bffd751
arrow-information-paradox is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 255 tokens to every session and 5,318 once invoked, about $0.0013 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.
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