AF gdpr-compliant
Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.
Apply GDPR-compliant engineering practices across your codebase.
As a process F 43/100 · Will not run — References files that are not bundled: references/operations.md
The same skill appears in 1 more place: RA-Skills
How to improve
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 1
✓ No critical or high findings
Medium and low: 1
-
low Risky intent
intent-offensive-securityreferences/Security.md:215Offensive-security / dual-use content (legitimate for authorised testing; review intended use)1. **Detection** — Define criteria: what triggers an incident (credential leak, DB dump exposed, ransomware, accidental public bucket).
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/operations.md
Process rating: all ten parameters 43/100
- 0Tools and files. 1 referenced file(s) missing: references/operations.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 70When it triggers. States when to use, but not when not to
- 100Steps. 92 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2787 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 676: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 92 items
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.