AC lgpd
Expert LGPD compliance advisor for Brazil's Lei Geral de Proteção de Dados (Law 13,709/2018). Use this skill whenever a user asks about LGPD, Brazilian data protection, ANPD, personal data processing in Brazil, data subject rights under Brazilian law, legal bases for processing, sensitive data handling, DPO appointment in Brazil, data breach notification to ANPD, LGPD penalties (fines up to 2% of revenue / R$50M), international data transfers from Brazil, Brazil-EU mutual adequacy (January 2026 — SCCs/BCRs no longer needed for Brazil-EU transfers), LGPD gap assessments, privacy policy drafting for Brazilian operations, DPIA under LGPD, consent management, or comparing LGPD with GDPR. Trigger for any Brazil privacy or data protection question even if LGPD is not named explicitly.
Expert LGPD compliance advisor for Brazil's Lei Geral de Proteção de Dados (Law 13,709/2018).
As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency
How to improve
- 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
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low Risky intent
intent-offensive-securityREADME.md:132Offensive-security / dual-use content (legitimate for authorised testing; review intended use)We discovered a ransomware attack that encrypted a database containing personal
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 63/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 40Consistency. Frontmatter name (lgpd) differs from the folder (lgpd-tanaji-hemant-naik)
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 85Steps. 68 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 3531 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 12 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)
- +4No input/output examples
- +2Single-language instructions
- +3Description length 789: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 68 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (3 of 3)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.