SKILLEMALL.ai

BB fintech-agreement-drafting-stephane-boghossian

An end-to-end method for drafting and finalising a complex, multi-pillar regulated fintech agreement — from intake to signature. Authored from a senior fintech lawyer's manual: a licensed payment-services provider engaging a counterparty across agent cash-in/cash-out, QR payments, wallet e-payments, and a marketplace, each with its own regulatory profile. Runs five phases and fourteen steps: regulatory mapping (activity-to-licence matrix, grey-zone classification gates), architecture (framework-plus-sub-agreement structure, ring-fenced marketplace), the regulatory–commercial balance (what flexes vs what cannot), core drafting (authority, float mechanics, hard-coded regulator caps, liability — all tracking control), execution-blocker triage, and a pre-signature check closing open blockers as conditions precedent. It refuses to invent licence-specific values or draft a representation as true without executed evidence. Use it to structure, draft, negotiate, or review any regulated payments contract.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 4 files body ≈ 7 249 tokens Open the sourcegithub.com↗ analyzed 89 min ago

An end-to-end method for drafting and finalising a complex, multi-pillar regulated fintech agreement — from intake to signature.

As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, running it twice

GeneratorSecurityCommerceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
B
72/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Failures and branches w 10
50
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 7249 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 72/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 3 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 7249 tokens
  • 85Steps. 31 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 23 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)
  • +3Description length 1011: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 31 items
  • +3Output format is stated explicitly
  • +4Has examples (0 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.