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Comprehensive peer review from skeptical economist and "lazy AI" perspectives. Identifies missing LaTeX equations, charts, hardcoded values, weak arguments, and context-loss vulnerabilities. Reviews calculation chains for all parameters.

mikepsinn By mikepsinn schedule Updated 1/29/2026

name: peer-review description: Comprehensive peer review from skeptical economist and "lazy AI" perspectives. Identifies missing LaTeX equations, charts, hardcoded values, weak arguments, and context-loss vulnerabilities. Reviews calculation chains for all parameters. allowed-tools: - Read - Edit - Grep - Glob - Bash - Write - TodoWrite

/peer-review <file.qmd>

Four-perspective review AND fix: (1) Skeptical economist, (2) Lazy AI vulnerabilities, (3) Calculation audit, (4) Enhancement opportunities. Generates report then implements all high/medium priority fixes. If no file specified, ask which to review.


Phase 1: Load Context

Read the file, then:

grep "_latex\":" _variables.yml | head -100
ls knowledge/figures/*.qmd | head -50

Phase 2: Skeptical Economist Review

Read as a hostile peer reviewer skeptical of large claims.

Category Check
Methodology Causal claims justified? Counterfactual specified? CIs appropriate? Assumptions stated?
Sources Peer-reviewed? Old (>5y)? Over-reliance on single studies?
Logic Conclusions follow? Unstated assumptions? Strongest counterargument addressed?
Framing Neutral language? Limitations discussed? Costs AND benefits quantified?

Bullshit Detection

Pattern Example Fix
Problem-solution mismatch Defending against Goodhart when metrics are real-world outcomes (income, mortality) that can't be gamed without improvement Ask: does this problem actually apply here? Cut irrelevant defenses
Speculative mechanisms "staking," "immutable rules," "distributed ledgers," "zero-knowledge proofs" when simpler solutions exist Replace with realistic mechanisms: institutional diversity, median aggregation, transparency
Internal contradictions "Immutable rules solve X" then later "immutable rules are insufficient" Grep for key claims, verify consistency throughout
Overconfident claims "trivial to influence," "guaranteed," "impossible" Soften: "incentive is enormous," "difficult," "unlikely"
Self-congratulatory framing "A sophisticated objection," "The honest assessment:" Cut framing, state content directly
Conflated problems Treating Goodhart gaming (behavior) and measurement capture (methodology) as same problem Distinguish clearly; different problems need different solutions
Over-defense 60 lines defending against non-problem, key point buried at end Lead with "why this doesn't apply," cut irrelevant mitigations
Unexplained jargon "mētis," "Schelling points," "Sybil attacks" Define inline or replace with plain language
Academic pomposity "This paper makes three contributions," "We formalize the X Condition" Cut if content is covered elsewhere; keep only if adds navigation value

Key question: For each defense/mitigation, ask "What specific attack does this prevent?" If answer is vague or doesn't apply to actual proposal, cut it.

Clarity & Concision

Write simply for general audience without losing precision. Target 8th-grade reading level, 10-15 word sentences average. Can a smart 8th-grader understand this? If not, simplify. Never sacrifice accuracy—use precise terms but define immediately. Break complex ideas into 2-3 short sentences. Delete ruthlessly.

Delete/Replace Example
Redundancy "past history" -> "history"
Hedging/blather "It could potentially be argued that" -> delete or "This suggests"
Filler phrases "It is important to note that", "In order to", "the fact that"
Nominalizations "the implementation of" -> "implementing"
Passive voice "was conducted by" -> "X conducted"
Em-dashes (—) Replace with period (preferred), comma, parenthesis, or semicolon
Long sentences "X happened, which caused Y, and this led to Z" -> "X happened. This caused Y. Y led to Z."

Flag and fix: Sentences >25 words, paragraphs >5 sentences, sections repeating earlier content, jargon without definition.

Appropriate Humor (Philomena Cunk Style)

Inject deadpan, absurdist humor when it clarifies without detracting from credibility.

Use when Avoid when
Highlighting absurd contradictions/inefficiencies Methodology sections (maintains rigor)
Making abstract concepts concrete via absurd comparisons Serious topics (deaths, suffering, failures)
Breaking up dense technical sections Executive summaries/abstracts
Calling out obvious but unstated truths If it undermines credibility

Style guide:

  • Deadpan delivery: State absurdities as simple facts
  • Absurd comparisons: "Like trying to solve climate change by asking everyone to think harder"
  • Obvious questions: "Why does this exist? Nobody knows."
  • Understated observations: "This seems inefficient. But it's the system we have."

Examples: ❌ "Regulatory delays kill people. LOL." ✅ "Regulatory delays kill people. This is not controversial. Yet the system continues."


Phase 3: Lazy AI Vulnerability Analysis

What survives if AI only reads first 3 paragraphs?

Pattern Fix
Late Caveats Front-load qualifications
CI Collapse ("102M" loses CI) Add CI inline at every mention
Scope Loss Repeat scope with each figure
Conditional Loss Add "(under X assumption)" inline
Conservative framing loss Bold the conservative note

Phase 4: Enhancement Opportunities

Hardcoded Values

python scripts/preview-qmd-with-variables.py <file> --numbers-only

Red flags: Dollar amounts, percentages, large numbers not using {{< var ... >}}. Numbers in $$ blocks should use _latex variables.

Missing LaTeX

For calculated values, check for _latex version: {{< var parameter_name_latex >}}

Citations

Prefer @citation-key from references.bib over manual superscripts. Web search for missing sources.

Charts

Check knowledge/figures/*<variable>*.qmd for tornado, mc-distribution, sensitivity-table charts.


Phase 5: Calculation Chain Audit

For each calculated parameter:

grep -B5 -A50 "^PARAMETER_NAME = Parameter" dih_models/parameters.py
Check Criteria
Distribution Normal (symmetric), Lognormal (costs, positive), Beta (probabilities), Fixed (constants only)
Formula No double-counting, independent factors, units match
CI Width <±20% overconfident, ±30-100% reasonable, >±200% uninformative
Sources Meta-analysis > peer-reviewed > government stats > industry reports > assumptions (flag prominently)

Phase 6: Report Template

## Peer Review: <filename>

### Summary
[1-2 sentences]

### Issues Found
| Issue | Type | Severity | Location | Fix |

Types: methodology, sources, logic, framing, clarity, lazy-ai, hardcoded, calculation, enhancement

### Priority Actions
1. **High:** 2. **Medium:** 3. **Low:**

Phase 7: Implement Fixes

Do not just report. Fix all High/Medium issues using Edit tool.

Re-read edited sections to verify. Track remaining issues with TodoWrite.


Rules

  1. Fix, don't just flag - implement High/Medium issues immediately
  2. Verify by re-reading edited sections
  3. Be specific - vague critiques aren't actionable
  4. If no issues found, say "No changes needed" and stop - don't invent problems
Install via CLI
npx skills add https://github.com/mikepsinn/disease-eradication-plan --skill peer-review
Repository Details
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