SKILLEMALL.ai

BB timeline-generator-scott-margetts

Build dependency network and critical path from a matter plan. Produce an interactive Gantt, flag near-critical tasks, and run what-if cascade scenarios when delays occur — showing programme impact and drafting communications. Produces filtered workstream or jurisdiction views for local counsel. Trigger on: 'build a timeline', 'Gantt chart', 'critical path', 'what if X is delayed', 'what moves if', 'schedule impact', 'how does this affect the programme', 'when do we finish', 'can we still close on time', 'if we miss this deadline', 'run a what-if', 'visualise the plan', 'Germany timeline', 'what does the Employment workstream look like', 'timeline for local counsel', 'just show me the [workstream] tasks'.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 3 files body ≈ 9 496 tokens Open the sourcegithub.com↗ analyzed 89 min ago

Build dependency network and critical path from a matter plan.

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, execution cost, running it twice

GeneratorResearchInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Execution cost w 6
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 9496 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 68/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 5 mutating operations with no state check
  • 40Execution cost. Instruction body is 9496 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 57 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 11 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)
  • +2Single-language instructions
  • +3Description length 714: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 57 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.