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+# Critical Questions by Document Type
+
+This reference provides type-specific questions for Third Pass critical analysis. Use these to supplement the universal questions in SKILL.md.
+
+## Tech Blog
+
+**Core Analysis:**
+- What problem does this solve, and for whom?
+- What are the trade-offs of this solution vs alternatives?
+- What's the assumed technical environment (stack, scale, team size)?
+- How would this approach fail or scale poorly?
+
+**Design & Implementation:**
+- Why this approach instead of simpler alternatives?
+- What are the hidden costs (complexity, maintenance, performance)?
+- What edge cases or error scenarios are not addressed?
+- How testable/debuggable is this approach?
+
+**Applicability:**
+- What prerequisites or constraints does this assume?
+- How well does this generalize to other contexts?
+- What would need to change for my use case?
+- Are there better-suited alternatives for my situation?
+
+**Evidence Quality:**
+- Are benchmarks/metrics provided? Are they representative?
+- Is there production experience or just prototypes?
+- What's missing from the evaluation?
+
+## Retrospective
+
+**Context & Validity:**
+- What was the specific context (team, org, timeline, constraints)?
+- How much is success due to approach vs context/luck?
+- Would this work in a different setting? Which aspects are transferable?
+
+**Lessons & Generalization:**
+- Are lessons backed by specific evidence or anecdotal?
+- What's the sample size (one project, multiple iterations)?
+- Are there alternative explanations for outcomes?
+- What would have happened with different decisions?
+
+**Missing Perspectives:**
+- What didn't work that isn't mentioned?
+- Who else was involved? What's their perspective?
+- What conflicts or tensions were glossed over?
+- What failed attempts preceded success?
+
+**Temporal Factors:**
+- When was this? Are lessons still valid?
+- How has the landscape changed since then?
+- What would be different if done today?
+
+## Technical Documentation
+
+**Design & Rationale:**
+- What design philosophy underlies this approach?
+- Why these abstractions vs alternatives?
+- What trade-offs were made (flexibility vs simplicity, etc.)?
+- What's explicitly not supported, and why?
+
+**Completeness & Accuracy:**
+- What common use cases are not documented?
+- Are there undocumented edge cases or gotchas?
+- Is error handling clearly explained?
+- What's the migration/upgrade story?
+
+**Context & Constraints:**
+- What assumptions about usage patterns?
+- What scale/performance characteristics?
+- What dependencies or prerequisites?
+- What's the intended audience expertise level?
+
+**Alternatives & Ecosystem:**
+- How does this compare to competing approaches?
+- What problems does this NOT solve well?
+- When should you use something else?
+
+## Personal Writing
+
+**Argument Structure:**
+- What's the core thesis or claim?
+- Is the claim clearly stated or implicit?
+- What evidence supports each point?
+- Are there logical gaps or leaps?
+
+**Assumptions & Biases:**
+- What's taken for granted without justification?
+- What perspectives or counterarguments are missing?
+- Are there hidden biases in framing?
+- What's the assumed audience knowledge?
+
+**Clarity & Coherence:**
+- Is the argument easy to follow?
+- Do examples actually support the points?
+- Are terms used consistently?
+- Is the conclusion justified by the body?
+
+**Rigor & Evidence:**
+- Are claims supported by evidence or assertion?
+- Are sources credible and relevant?
+- Are alternative explanations considered?
+- What would strengthen this argument?
+
+**Practical Application:**
+- Is this actionable or purely theoretical?
+- Who benefits from these ideas?
+- What's needed to implement these suggestions?
+- What could go wrong in practice?
+
+## Academic Paper
+
+**Research Design:**
+- Are research questions clearly stated?
+- Is methodology appropriate for questions?
+- Are there confounding variables not controlled?
+- Is sample size adequate and representative?
+- Could results be explained differently?
+
+**Assumptions & Validity:**
+- What theoretical assumptions underlie this work?
+- Are measurements valid for constructs?
+- Are there threats to internal/external validity?
+- How replicable is this research?
+
+**Related Work:**
+- Is related work comprehensive and fair?
+- What relevant prior work is missing?
+- How does this advance beyond existing work?
+- Are comparisons appropriate and fair?
+
+**Results & Interpretation:**
+- Do conclusions follow from results?
+- Are alternative interpretations possible?
+- Is statistical significance practical significance?
+- What are limitations and boundary conditions?
+
+**Contribution & Impact:**
+- What's genuinely novel here?
+- Is contribution incremental or significant?
+- What future research does this enable?
+- What are real-world applications?
+
+## Cross-Cutting Questions
+
+These apply to all document types:
+
+**Authority & Credibility:**
+- What's the author's expertise in this area?
+- What potential conflicts of interest exist?
+- Is tone confident or overconfident?
+
+**Temporal Context:**
+- When was this written?
+- What was the state of the field then?
+- What's changed since publication?
+
+**Rhetorical Choices:**
+- What's emphasized vs downplayed?
+- What language choices reveal assumptions?
+- What's the intended audience and purpose?
+
+**Actionability:**
+- What can I do with this information?
+- What would I need to verify before using this?
+- What risks come with applying this?