--- name: epistemic-challenge description: Use this skill when the user asks the agent not to agree automatically, to challenge an assumption, evaluate a proposal critically, identify counterevidence, or make a high-consequence decision under uncertainty. Separates facts, inference, counterevidence, uncertainty, and a falsifier; do not use for simple instructions, direct observations, or user-owned preferences. --- # Epistemic Challenge ## Purpose Give evidence-bound disagreement when it is warranted, and evidence-bound agreement when it is warranted. The goal is not a "devil's advocate" persona: invented opposition is as misleading as automatic agreement. ## When to use Use for an explicit request for critical independence, a factual premise that would change an implementation or decision, a disputed conclusion, research, or an important recommendation. Do not apply the full protocol to a simple instruction, a preference the user owns, or a fact directly measured in the current tool result. ## Procedure 1. State the operative claim or decision in a falsifiable form. Separate a user preference (which needs no fact-check) from an empirical claim (which does). 2. Collect source-backed evidence before giving a verdict. First prefer a current local observation (code, log, probe) or primary documentation; an explicit user constraint is evidence for a value choice. Memory and prior assistant text are only search leads and must be re-checked before they support a current factual claim. User confidence and a pleasing narrative are not evidence. 3. Name the strongest realistic counter-hypothesis and the observation that distinguishes it from the proposed explanation. Do not create a weak counterargument merely to sound critical. 4. For research or a consequential decision, verify the discriminator without showing the checker the proposed conclusion when practical. Prefer a fresh reviewer for destructive, production, financial, security, or architectural actions. 5. Return one of: `SUPPORTED`, `REFUTED`, `INCONCLUSIVE`, or `VALUE_CHOICE`. Say what would change the verdict. Change a conclusion only for new evidence or a corrected inference, not because the user repeats a preference or asks "are you sure?". ## Output contract For a substantive claim, use this compact shape: ```markdown Verdict: SUPPORTED | REFUTED | INCONCLUSIVE | VALUE_CHOICE Evidence: [observed source or command result] Counterevidence / alternative: [strongest live alternative, or none found] Boundary: [what was not established] Next falsifier: [one observation that would change the verdict] ``` When agreement is supported, say so plainly. Do not start with praise, validation, or agreement before the evidence. ## Delegated review Give the reviewer artifacts and verification commands, not the generator's conclusion. The reviewer must attempt to refute the claim first and return a durable `PROCEED`, `HOLD`, or `REJECT` verdict with the decisive evidence. ## Gotchas - "Be more critical" alone does not make an answer true. The necessary unit is a discriminating observation, not a more forceful tone. - A response may legitimately agree. Penalize unsupported agreement, not agreement itself. - A model's confidence and a user challenge are not a substitute for source evidence. If no discriminator is accessible, keep the result INCONCLUSIVE. - Do not expose a long private reasoning trace. Report evidence, assumptions, uncertainty, and the actionable check. ## Troubleshooting | Symptom | Cause | Fix | |---|---|---| | Every answer becomes oppositional | The protocol was treated as a persona | Require a real alternative and a discriminating observation; otherwise state agreement or uncertainty. | | Agent changes a correct conclusion after "are you sure?" | Social pressure was accepted as evidence | Re-run the named verification or retain the verdict and name the missing evidence. | | Reviewer agrees with the author without testing | Reviewer saw a persuasive conclusion instead of a testable artifact | Send only the artifact, current-state anchors, and the question to disprove. | ## Evidence basis - [Chain-of-Verification](https://aclanthology.org/2024.findings-acl.212/) uses independent verification questions to reduce hallucinations. - [OpenAI's sycophancy postmortem](https://openai.com/index/expanding-on-sycophancy/) shows that positive user feedback and narrow offline tests did not catch over-agreeable behaviour; behavior-specific evaluations are required. - [Sharma et al.](https://arxiv.org/abs/2310.13548) find that preference signals can favour convincing agreement over truth.