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 event4u-app/agent-config --skill data-handling-judgmentgit clone --depth 1 https://github.com/event4u-app/agent-configWrote 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/event4u-app/agent-config/data-handling-judgment)<a href="https://agentmods.dev/skills/event4u-app/agent-config/data-handling-judgment"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/data-handling-judgment/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/event4u-app/agent-config/data-handling-judgment"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/data-handling-judgment.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00047 | $0.02573 |
| Opus 5 | $0.00023 | $0.01287 |
| Sonnet 5 | $0.00009 | $0.00515 |
| Haiku 4.5 | $0.00005 | $0.00257 |
Grade A, and why
data-handling-judgment 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 8d 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
data-handling-judgment
When to use
- A data category needs classification (PII / PHI / financial / public / pseudonymous / aggregate) and downstream retention, access, and transfer rules depend on the classification.
- A retention default is being set (or audited) and the question is how long is defensible, how long is useful, how long is dangerous.
- A cross-border transfer is proposed (analytics in US, support in Philippines, backup in EU) and the transfer-mechanism + sub-processor obligations need a read.
- A data-subject-rights (DSR) workflow is being designed: access, deletion, portability, correction, objection, automated-decision-objection.
Do NOT use as a regulatory-regime delta read (route to privacy-review (P6); this skill composes P6 for the regime floor), for contract-clause depth (route to contracts-cognition (P5)), or for data-loss-prevention tool administration / classifier-engine configuration.
Cognition cluster
- Mental model 28 — Inversion. "If this data category leaked in this form, who would we have to notify and what would the headline read?" The headline inversion forces honest classification ahead of operational convenience. See
mental-models.md§ 28. - Mental model 1 — First principles. Strip every retention claim to: what purpose does keeping this another day serve, and whose risk does it grow? Most retention defaults are inherited from the previous system, not chosen. See
mental-models.md§ 1. - Mental model 26 — Optionality. Aggressive retention preserves analytical optionality but forecloses deletion optionality and grows breach optionality for the attacker. Each retention choice is a trade. See
mental-models.md§ 26. - Context-spine — regulatory-regime + customer-segment + product. Read regulatory-regime (J1) for floor (GDPR storage-limitation principle; HIPAA retention minimums for medical records; financial-regulator retention mandates). Read customer-segment for whose data sets the floor. Read product for which features actually need the data.
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.
- 8d ago First seen · 161 lines · 47 tokens per session scan A 269d0b56fe3a
data-handling-judgment is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 2,573 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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