Drivers’ Hours & WTD Infringement Coach (UK)

v1.0.0

Creates a 1-page driver-facing tacho/WTD infringement note plus corrective actions and review date. USE WHEN you need to explain infringements and schedule follow-up.

1· 1.8k·1 current·1 all-time
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
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Benign
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Benign
high confidence
Purpose & Capability
Name/description match the runtime instructions and included templates. Required inputs (driver identifier, infringement list, working time context, optional prior RAG history/SOP excerpt) are exactly what a tacho/WTD coaching note generator needs. No unrelated binaries, credentials, or system access are requested.
Instruction Scope
SKILL.md stays within scope: validate input, summarise facts, apply the local RAG rule (provided in references), produce two .md artefacts from templates, and stop to ask for missing/ambiguous items. It does not instruct reading system files, accessing environment variables, or sending data to external endpoints. It explicitly relies on user-supplied summaries of uploaded files unless a trusted parser exists in the environment.
Install Mechanism
Instruction-only skill with no install spec, no code files to write or execute, and no downloads — lowest-risk installation posture.
Credentials
No environment variables, credentials, or config paths are requested. Inputs are user-provided case data only, which is appropriate for the stated purpose.
Persistence & Privilege
always: false and normal agent invocation defaults. The skill does not request permanent presence or attempt to modify other skills or system settings. Autonomous invocation is allowed by platform default but the skill's actions are limited to producing templated outputs.
Scan Findings in Context
[no-findings] expected: The regex-based scanner had no code to analyze because this is an instruction-only skill; that is expected for a template/instructions pack.
Assessment
This skill appears coherent and low-risk, but consider the following before installing/using it: 1) Data sensitivity — the outputs and inputs include personal data (driver names, shift details). Only paste the minimum necessary records and follow your privacy/data-retention policies. 2) Policy alignment — replace or confirm references/rag-escalation-rule.md with your official internal lookback window, escalation thresholds, and authorisers before relying on generated notes for disciplinary action. The skill explicitly advises not to use its outputs as investigatory/legal evidence; route those cases through your formal investigation workflow. 3) File parsing — the skill relies on user summaries of .ddd/CSV/PDF files unless you have a trusted parser in your environment; do not assume it will extract data from uploaded files automatically. 4) Source provenance — the skill's source/homepage is unknown; test with non-sensitive sample data to confirm outputs meet tone and legal requirements. 5) Storage and sharing — ensure generated notes are stored and shared according to HR/compliance rules. If you want stronger guardrails, restrict autonomous invocation in your agent configuration or require user confirmation before producing or saving outputs.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

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