AC war-room
Run adversarial multi-agent war-room evaluations for any strategic decision. Spawns 5 parallel subagents (Analyst, Guardian, Treasurer, Builder, Strategist) to challenge a proposal from different angles, then synthesizes a GO/NO-GO/REWORK ruling. Use when: (1) evaluating proposals that need multi-perspective stress-testing, (2) making go/no-go decisions on investments, products, hires, or architecture, (3) any decision where adversarial challenge improves quality. Supports finance, product, engineering, and hiring domains. NOT for: simple questions, routine tasks, or decisions that do not need formal evaluation.
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Consistency. Frontmatter name (war-room) differs from the folder (iris-war-room)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (git) that frontmatter does not declare
- 70Failures and branches. 4 branches
- 100Steps. 24 steps
- 100Execution cost. Instruction body is 886 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
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
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 619: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 24 items
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.