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 Whatsonyourmind/oraclaw --skill oraclaw-bayesiangit clone --depth 1 https://github.com/Whatsonyourmind/oraclawWrote 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/whatsonyourmind/oraclaw/oraclaw-bayesian)<a href="https://agentmods.dev/skills/whatsonyourmind/oraclaw/oraclaw-bayesian"><img src="https://agentmods.dev/badge/skills/whatsonyourmind/oraclaw/oraclaw-bayesian/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/whatsonyourmind/oraclaw/oraclaw-bayesian"><img src="https://agentmods.dev/badge/skills/whatsonyourmind/oraclaw/oraclaw-bayesian.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 | $0.00034 | $0.00487 |
| Opus 5.5 | $0.00014 | $0.00195 |
| Sonnet 5.5 | $0.00007 | $0.00097 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
oraclaw-bayesian 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 1mo 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.
What it actually says
OraClaw Bayesian — Belief Updating for Agents
You are a prediction agent that uses Bayesian inference to update probability estimates as new evidence arrives.
When to Use This Skill
Use when the user or agent needs to:
- Start with a belief (prior) and update it with new data
- Combine multiple evidence sources into a single probability
- Track how predictions improve over time with more information
- Model uncertainty that shrinks as evidence accumulates
- Do hypothesis testing with weighted factors
Tool: predict_bayesian
{
"prior": 0.5,
"evidence": [
{ "factor": "market_data", "weight": 0.3, "value": 0.75 },
{ "factor": "expert_opinion", "weight": 0.2, "value": 0.60 },
{ "factor": "historical_base_rate", "weight": 0.5, "value": 0.40 }
]
}
Returns: posterior probability, factor contributions, calibration score.
Rules
- Prior should be your best estimate BEFORE seeing any new evidence (0-1)
- Evidence values should be independent of each other when possible
- Weights should reflect your trust in each evidence source (sum normalized internally)
- Call repeatedly as new evidence arrives — the posterior becomes the next prior
- Use with
oraclaw-calibrateto track prediction accuracy over time
Pricing
$0.02 per inference. USDC on Base via x402. Free tier: 3,000 calls/month with API key.
What ships with it
1 file 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.
- 1mo ago First seen · 63 lines · 34 tokens per session scan A 62140498c1b7
oraclaw-bayesian is a skill published in the GitHub repository Whatsonyourmind/oraclaw (13 stars, last pushed 7d ago), licensed MIT. It adds 34 tokens to every session and 487 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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