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 PlamenTSV/plamen --skill outcome-determinismgit clone --depth 1 https://github.com/PlamenTSV/plamenWrote 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/plamentsv/plamen/outcome-determinism)<a href="https://agentmods.dev/skills/plamentsv/plamen/outcome-determinism"><img src="https://agentmods.dev/badge/skills/plamentsv/plamen/outcome-determinism/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/plamentsv/plamen/outcome-determinism"><img src="https://agentmods.dev/badge/skills/plamentsv/plamen/outcome-determinism.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Anti-Refusal · line 120 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
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 | $0.00040 | $0.01950 |
| Opus 5 | $0.00020 | $0.00975 |
| Sonnet 5 | $0.00008 | $0.00390 |
| Haiku 4.5 | $0.00004 | $0.00195 |
Grade A, and why
outcome-determinism 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 6d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Injectable Skill: Outcome Determinism - Selection Fairness & Strategic Timing
Protocol Type Trigger:
outcome_determinism- detected when EITHER of these code patterns are present:
- Selection from finite depletable pool with fallback behavior (
while(full) next,modulowith shrinking domain, category/slot/validator selection)- Time-gated actions with observable default/fallback outcomes (
deadline,claimPeriod,defaultSelection,expiry+ fallback path that computes from predictable state) Inject Into: Breadth agents, depth-edge-case Language: All (rational actor patterns are chain-agnostic) Finding prefix:[OD-N]Added in: v1.1NOTE: Callback selective revert (Section 1a of the original skill) and RNG consumption enumeration (Section 1b) are now ALWAYS-ON checks in the depth agent template - they do not require this injectable to trigger.
What This Injectable Adds (beyond always-on checks)
The always-on depth template already covers:
- Callback selective revert: Full taxonomy of external execution transfers (ERC-721/1155/777/1363, flash loans, hooks, low-level calls, ETH transfers) - see depth-templates.md "CALLBACK SELECTIVE REVERT ANALYSIS"
- Tainted source consumption enumeration: RNG/oracle consumed by multiple functions → rate severity by worst consumer - see depth-templates.md PART 1 item 6
This injectable adds analysis that only applies when SPECIFIC structural patterns exist:
1. Selection Fairness Under Constraint Changes
For every selection algorithm operating on a set that can shrink, grow, or be modified between selections:
1a. Probability Redistribution on Depletion
| Selection Function | Pool Size | Depletion Mechanism | Fallback Behavior | Redistribution Fair? |
|---|
Fairness test: When element X is removed from a pool of N:
- Fair: Each remaining element gets probability 1/(N-1) - uniform redistribution
- Biased: Sequential fallback (
index++,next slot) - adjacent element gets doubled probability - Broken: Infinite loop (no exit when all depleted) or unreachable elements
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.
- 6d ago First seen · 141 lines · 40 tokens per session scan A 89549ccd7065
outcome-determinism is a skill published in the GitHub repository PlamenTSV/plamen (295 stars, last pushed 2d ago), licensed MIT. It adds 40 tokens to every session and 1,950 once invoked, about $0.0002 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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