BD oral-argument
Prepare a lawyer for an adversarial proceeding the way Neal Katyal's "Harvey" prepared him for the SCOTUS tariffs argument: profile the tribunal from their prior opinions and questions, predict the specific questions you will face, map narrow "escape routes" each judge can walk through without abandoning prior commitments, and spar adversarially until only the strongest answers survive. The model is the sparring partner. The human still wins the case. Use when: preparing for oral argument, appellate argument, motion hearing, evidentiary hearing, deposition (taking or defending), arbitration, mediation, or any proceeding where a known decision-maker will fire questions at you in real time. Also useful for stress-testing a brief before filing. Proactively suggest when: the user mentions an upcoming hearing/argument with named judges or arbitrators, drafts a brief and wants it pressure-tested, asks "what will Justice X / Judge Y ask me," or talks about preparing for a specific bench.
Prepare a lawyer for an adversarial proceeding the way Neal Katyal's "Harvey" prepared him for the SCOTUS tariffs argument: profile the tribunal from their…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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
- note
frontmatter-keyunknown frontmatter key "triggers"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (oral-argument) differs from the folder (oral-argument-stephane-boghossian)
- 50Failures and branches. 0 branches, has a failure section
- 85Steps. 35 steps, 2 vague phrases
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 1830 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 997: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +4Structure: 9 headings
- +3Step-by-step instructions: 35 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.