SKILLEMALL.ai

CC invoice-review-compliance

Invoice review, non-compliance flagging, rejection communication, billing trend analysis, and conversation preparation for in-house legal ops teams managing outside counsel. Review invoices against billing guidelines; flag block billing, prohibited fees, rate violations, staffing violations, late submission. Produce line-item review report and approval note. Draft rejection letter to outside counsel. Build invoice review checklist. Analyse billing trends across multiple invoices and produce a structured conversation guide for the relationship review. Identify systemic patterns and produce formal non-compliance notice. Trigger on: 'review this invoice', 'flag billing issues', 'check invoice against guidelines', 'write the rejection letter', 'build an invoice checklist', 'block billing', 'UTBMS', 'billing non-compliance', 'analyse our invoices', 'billing trends', 'prep for the billing conversation', 'relationship review', 'the firm keeps doing this', 'escalate'.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 2 files body ≈ 11 959 tokens Open the sourcegithub.com↗ analyzed 70 min ago

Invoice review, non-compliance flagging, rejection communication, billing trend analysis, and conversation preparation for in-house legal ops teams managing…

As a process C 57/100 · Has gaps — weak spots: result and completion, consistency, execution cost

AnalyzerGoogle DriveFinanceSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 11959 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 57/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 15 mutating operations with no state check
  • 40Consistency. Frontmatter name (invoice-review-compliance) differs from the folder (invoice-review-compliance-scott-margetts)
  • 40Execution cost. Instruction body is 11959 tokens: crowds the task out of the window
  • 55Failures and branches. 1 branches
  • 60Steps. 96 steps, 4 vague phrases
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 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 974: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 96 items
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.