assumption-audit
The assumption-audit skill systematically identifies hidden assumptions within methods, theories, or research gaps and classifies them by vulnerability using a load-bearing versus likely-false matrix. Use it when you need to surface dangerous assumptions that are both foundational to an argument yet remain unexamined or unstated, validating their causal logic through structured validation checks.
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine /tmp/assumption-audit && cp -r /tmp/assumption-audit/skills/assumption-audit ~/.claude/skills/assumption-auditSKILL.md
# Assumption Audit Systematically audit assumptions underlying a method, theory, or gap. ## When to Use Need to identify which hidden assumptions are most dangerous — load-bearing yet unexamined. ## Budget | Base SOP | Target | ±10% Range | |----------|--------|------------| | web-search | 30 | 27–33 | | web-research | 10 | 9–11 | | paper-overview | 30 | 27–33 | | paper-search | 20 | 18–22 | | paper-research | 10 | 9–11 | ## State Ledger ``` <HARD-GATE> | SOP | Done | Target | % | |-----|------|--------|---| | web-search | ? | 30 | ? | | web-research | ? | 10 | ? | | paper-overview | ? | 30 | ? | | paper-search | ? | 20 | ? | | paper-research | ? | 10 | ? | Budget Gate: OPEN/CLOSED (>=80% required to exit) </HARD-GATE> ``` ## Available Tactics - assumption-stress-test ## Available SOPs **Import:** web-search, web-research, paper-overview, paper-search, paper-research **Subagent:** abp-vulnerability-classification, clr-validation **Shared:** assumption-surfacing ## Execution Guidance Surface all assumptions (shared SOP), classify by vulnerability (ABP), validate causal logic (CLR 8-check). Focus on load-bearing + non-explicit assumptions. ## Output Format Assumption Audit Report — assumption inventory, vulnerability matrix, CLR validation results, priority list for challenging.
Experiment-specific - summarize the DARE executor's research design into a clean research_result report, forced to write back into the spec file produced by formated-specs.
Experiment-specific - replaces writing-specs, emits DARE's 4-layer call plan as a clean research_graph schema. Last step forces load formated-result.
loss-1 judge - read a sample's full dialogue and decide whether the user simulator semantically enacted its Policy Card. check-blind.
loss-2 judge - pairwise quality comparison across the n rungs within one topic; decide monotonicity and endpoint separation. check-blind, D1-D5 only.
Strategy: 面对异常的最佳解释推理
Remove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
Map system architecture to ablatable units for ablation studies
Design ablation studies to isolate component contributions in ML systems