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BC scotus-argument-analyzer

Analyze a U.S. Supreme Court oral argument transcript for a lawyer who has not read it: each advocate's position, authorities discussed, the bench's concerns, tentative judicial leanings, possible dispositions, and advocacy strengths and weaknesses, with transcript pinpoints. Use for oral argument analysis, a SCOTUS argument report, or an assessment of how the justices approached a case. Requires readable transcript content; research, Python tallying, and document creation are optional, with disclosed fallbacks.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 4 files · 1 script body ≈ 3 430 tokens Open the sourcegithub.com↗ analyzed 89 min ago

Analyze a U.S. Supreme Court oral argument transcript for a lawyer who has not read it: each advocate's position, authorities discussed, the bench's concerns…

As a process C 50/100 · Has gaps — References files that are not bundled: NOTICE

AnalyzerData and analyticsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
50/100
Has gaps
References files that are not bundled: NOTICE
Tools and files w 18
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 missing-ref reference to a missing file: NOTICE

Process rating: all ten parameters 50/100

Will not run. References files that are not bundled: NOTICE
  • 0Tools and files. 1 referenced file(s) missing: NOTICE
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Consistency. Frontmatter name (scotus-argument-analyzer) differs from the folder (scotus-argument-analyzer-seth-chandler)
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 27 steps
  • 100Execution cost. Instruction body is 3430 tokens

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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 517: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (1 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.