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 non-zero-sumgit 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/non-zero-sum)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/non-zero-sum"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/non-zero-sum/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/non-zero-sum"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/non-zero-sum.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 | $0.00127 | $0.02293 |
| Opus 5 | $0.00063 | $0.01146 |
| Sonnet 5 | $0.00025 | $0.00459 |
| Haiku 4.5 | $0.00013 | $0.00229 |
Grade A, and why
non-zero-sum 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Non-Zero-Sum
Overview
A non-zero-sum interaction is one where mutual gain (or mutual loss) is possible — the parties' outcomes do not simply cancel each other out. Most real-world conflicts and negotiations are not zero-sum, but feel zero-sum because we focus on the visible resource rather than underlying interests. Robert Axelrod's computer tournament showed cooperation can emerge without central authority when interactions repeat and the future is valued. Robert Wright extended this: the arc of history is driven by accumulating non-zero-sum arrangements — specialization, trade, institutions.
Compose with neighbors: Use prisoners-dilemma to model the payoff structure first. Use repeated-games-reputation when the key variable is whether interaction repeats. Use nash-equilibrium to find whether a stable cooperative outcome exists.
When to Use
- A negotiation or conflict is deadlocked in zero-sum framing — each side treating every gain as the other's loss
- You want to find latent cooperative value in an adversarial relationship
- Designing an institution, platform, or contract to align incentives for competing parties
- Someone says: "this is win-lose," "we can't both win," "what's in it for them," "could we cooperate instead of compete?"
- A market is framed as winner-take-all — "AI will take all the jobs / margin," "the AI capex will only pay off for the platform," "AI-native startups will crush incumbents (or vice versa)" — and you need to test whether the layers can grow together instead
When NOT to use:
- Genuinely fixed-pool, one-shot interaction with no side effects — non-zero-sum framing is wishful, not analytical
- Interests are fundamentally incompatible (ideological, identity-based) with no concrete trade creating net value
- The real constraint is power asymmetry → use batna-zopa instead
Coaching Novices (Adaptive Front Door)
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.
- 9d ago First seen · 124 lines · 127 tokens per session scan A 11fad925722e
non-zero-sum is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 127 tokens to every session and 2,293 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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