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 plurigrid/asi --skill gflownetgit clone --depth 1 https://github.com/plurigrid/asiWrote 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/plurigrid/asi/gflownet)<a href="https://agentmods.dev/skills/plurigrid/asi/gflownet"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/gflownet/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/plurigrid/asi/gflownet"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/gflownet.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 analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00036 | $0.01770 |
| Opus 5 | $0.00018 | $0.00885 |
| Sonnet 5 | $0.00007 | $0.00354 |
| Haiku 4.5 | $0.00004 | $0.00177 |
Grade A, and why
gflownet 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GFlowNet Skill
"Sample x with probability proportional to R(x), not just maximize R(x)." — Yoshua Bengio
Overview
GFlowNets (Generative Flow Networks) are a new paradigm:
- RL: Maximize expected reward → single optimal solution
- MCMC: Sample from distribution → slow mixing
- GFlowNet: Learn to sample P(x) ∝ R(x) → fast, diverse sampling
Core Concept
GFlowNet Objective:
∀ terminal state x: P_θ(x) = R(x) / Z
Where:
P_θ(x) = probability of generating x via forward policy
R(x) = unnormalized reward function
Z = partition function (normalizing constant)
Key Insight: We DON'T need to know Z to train!
Architecture
┌─────────────────────────────────────────────────────┐
│ GFlowNet │
├─────────────────────────────────────────────────────┤
│ Initial State s₀ │
│ │ │
│ ▼ │
│ ┌─────────────┐ │
│ │ Forward │ P_F(s' | s) = learned policy │
│ │ Policy │ │
│ └──────┬──────┘ │
│ │ sample action │
│ ▼ │
│ ┌─────────────┐ │
│ │ Transition │ s → s' │
│ └──────┬──────┘ │
│ │ │
│ ▼ │
│ ┌─────────────┐ │
│ │ Terminal? │───No──▶ continue │
│ └──────┬──────┘ │
│ │ Yes │
│ ▼ │
│ ┌─────────────┐ │
│ │ R(x) │ Evaluate reward │
│ └─────────────┘ │
└─────────────────────────────────────────────────────┘
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 · 224 lines · 36 tokens per session scan A 3c37a104ee00
gflownet is a skill published in the GitHub repository plurigrid/asi (62 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 1,770 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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