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 agentmods add skills/binary16labs/prime-silo/data_auditornpx skills add binary16labs/prime-silo --skill data_auditorgit clone --depth 1 https://github.com/binary16labs/prime-siloWrote 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/binary16labs/prime-silo/data_auditor)<a href="https://agentmods.dev/skills/binary16labs/prime-silo/data_auditor"><img src="https://agentmods.dev/badge/skills/binary16labs/prime-silo/data_auditor.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00020 | $0.00225 |
| Opus 5 | $0.00010 | $0.00112 |
| Sonnet 5 | $0.00004 | $0.00045 |
| Haiku 4.5 | $0.00002 | $0.00022 |
Grade A, and why
data-auditor 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 3d 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
Data Auditor Skill
This skill allows an agent to audit stateless data pipelines defined by Pypes JSON execution contracts. It extracts the agentic reasoning and planning logic previously bundled inside the Pypes execution engine, turning it into a portable skill.
Capabilities
- Contract Analysis: Analyze a
.jsonPypes execution contract. - Move Analysis: Evaluate historical data to determine statistically significant drift (move analysis thresholding).
- Execution Oversight: Use the local Pypes environment to dry-run contracts and inspect the provenance.
When to use
Use this skill when the user requests an audit of a dataset, wants to generate a new Pypes execution contract, or needs to debug a pipeline validation failure.
Execution
- To dry-run, construct a Pypes execution contract in memory and run the local Pypes validators.
- Analyze the
ValidationResultreturned by the core engine. - Report any threshold breaches or completeness issues to the user.
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.
- 3d ago First seen · 26 lines · 20 tokens per session scan A 5d8c46c6b6bf
data-auditor is a skill published in the GitHub repository binary16labs/prime-silo (5 stars, last pushed 10d ago), licensed MIT. It adds 20 tokens to every session and 225 once invoked, about $0.0001 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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