SKILLEMALL.ai

CD gibraltar-law-osint-philip-vasquez

A jurisdiction-grounding reference file for AI assistants working on Gibraltar legal, regulatory, and compliance research. Corrects systematic errors AI models make when applying English law to Gibraltar — a distinct jurisdiction under the Gibraltar Constitution Order 2006, with its own court hierarchy, civil procedure rules, employment law, and regulatory framework. Covers the source hierarchy, court structure, civil procedure divergences (14-day deemed service, post-Jackson reforms not adopted), employment law specifics (uncapped discrimination awards, 5-employee redundancy threshold), FSC financial services regulation, AML/KYC compliance sources, Gibraltar Companies Act 2014 with UBO public register, and a structured directory of official public record sources. Includes research profiles for lawyers, compliance professionals, and due diligence practitioners. Not legal advice.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 3 files body ≈ 8 978 tokens Open the sourcegithub.com↗ analyzed 70 min ago

A jurisdiction-grounding reference file for AI assistants working on Gibraltar legal, regulatory, and compliance research.

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
C
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
D
42/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • 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 · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 8978 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 42/100

  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 12 mutating operations with no state check
  • 40Consistency. Frontmatter name (gibraltar-law-osint-philip-vasquez) differs from the folder (gibraltar-regulatory-compliance-osint-philip-vasquez)
  • 40Execution cost. Instruction body is 8978 tokens: crowds the task out of the window
  • 100Tools and files. No external tools needed
  • 100Steps. 32 steps
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • +3Description length 891: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +4Structure: 46 headings
  • +3Step-by-step instructions: 32 items
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.