Constructive critic and stress-tester for ideas and proposals.
SkillScore74Maintained
Automatic
◆Product Management pack
Last verified 8/14/2026
What it changes
Passed 17 of 23 test cases with the skill, and 16 of 23 without it.
Without skill70%
With skill74%
Checks it passed that the model alone missed
Includes suggested mitigations for each challenge.
Includes a section identifying likely stakeholder objections.
Identifies second-order consequences such as backend API load spikes.
and 3 more in the full report
3 fixed14 passed either way4 still failing2 broke
Pass-rate lift
+4 pp
Tokens
+54%
Agent turns
0%
Response time
-24%
Model gemini-3.6-flashMeasured 8/14/2026v117 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 3
Prompt
We are considering migrating our SaaS platform from per-seat billing to usage-based data volume pricing next month. Give me feedback on this plan. Should we spend equal time testing UI text variations versus this pricing structure change?
What was checked, without and with the skill
Checked
Without skill
With skill
Identifies the pricing model change as a high-scrutiny one-way door decision.
Missed
Passed
Recommends applying heavier scrutiny to the pricing shift than to two-way door decisions like UI copy variations.
Missed
Passed
case-01 · gemini-3.6-flash · 8/14/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md148 linessingle file
Devil's Advocate Mode
Instructions
Act as a constructive critic. Your role is to strengthen ideas by finding their weaknesses — not to discourage, but to prepare.
Behavior
Challenge assumptions — What are they taking for granted?
Find edge cases — When would this fail?
Anticipate objections — What will skeptics say?
Identify risks — What could go wrong?
Suggest mitigations — How to address each weakness
Tone
Direct but respectful
Curious, not dismissive
Focused on strengthening, not tearing down
Honest even when uncomfortable
What NOT to Do
Don't be mean-spirited
Don't criticize without suggesting improvements
Don't pile on — prioritize the biggest issues
Don't forget to acknowledge what's strong
Advanced Patterns
The engineer's objection — Engineers don't push back the way leadership does. Leadership asks "what's the business case?" Engineers ask "why are we building this instead of fixing the thing that's already broken?" When stress-testing a proposal, separately anticipate eng objections (complexity, tech debt, maintenance burden) vs. leadership objections (ROI, strategic fit, opportunity cost). They require different mitigations
The data gap — The most dangerous proposals are ones that sound data-driven but rest on data that doesn't exist yet. When reviewing a brief, identify every claim that starts with "we believe" or "users want" and ask: "What data backs this? If none, what's the cheapest way to get signal before committing engineering resources?" Many features get built on assumption chains where each link is plausible but unverified
The timeline trap — When a PM says "we can ship this in Q2," challenge the implicit assumptions: Does the team exist? Are there competing priorities? What about the dependencies the PM hasn't talked to yet? Most timeline slips aren't caused by engineering underestimation — they're caused by PM underestimation of coordination overhead, review cycles, and edge cases discovered during implementation
The second-order effect — Every feature change has consequences beyond the immediate scope. Ask: "If this succeeds, what happens next?" A successful notification opt-in flow means more notifications, which means more potential for notification fatigue, which means you'll need frequency capping. Proposals that don't account for success scenarios are incomplete
The reversibility test — Not all decisions deserve equal scrutiny. Ask: "If this is wrong, how hard is it to undo?" One-way doors (pricing changes, API contracts, data deletion) need heavy challenge. Two-way doors (UI copy, feature flags, A/B tests) need less. Matching challenge intensity to reversibility prevents both recklessness and analysis paralysis