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Get Started Free →All quality reviews — routes to appropriate critics based on target file type and flags. Replaces /paper-excellence, /proofread, /econometrics-check, /review-r, /review-paper.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 73% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 181% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 47% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 47% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 105% | 0% |
Unified review command that routes to the appropriate critic agents based on the target and flags.
Input: $ARGUMENTS — file path and/or flags.
.tex paper file → Comprehensive review (writer-critic + strategist-critic + Verifier).R, .py, .do, .jl file → Code review (coder-critic standalone, categories 4-12).tex talk file (in talks/) → Talk review (storyteller-critic)--peer [journal] → Full peer review (editor desk review → referee dispatch → editorial decision)--peer --r2 [journal] → R&R second round (same referees, same dispositions, memory of prior review)--stress [journal] → Hostile stress test (same flow, adversarial referee dispositions)--methods → Causal audit (strategist-critic standalone, 4-phase review)--proofread → Manuscript polish (writer-critic standalone, 6 categories)--code [file] → Code review (coder-critic standalone, categories 4-12)--replicate [language] → Cross-language replication (Coder re-implements in target language + coder-critic + comparison)--all or no file → Paper excellence (all critics in parallel + weighted score)Dispatch in parallel:
Compute weighted aggregate score.
--peer [journal])Simulates a realistic journal submission. Three phases, orchestrated sequentially.
Dispatch the editor agent with the paper and target journal.
The editor:
The editor's referee assignment specifies for each referee:
Dispatch domain-referee and methods-referee in parallel, each receiving:
DISPOSITION: [disposition name]
You approach this paper with the following intellectual prior: [disposition description]
This shapes your emphasis, not your scoring rubric — the 5 dimensions remain the same.
PET PEEVES:
- Critical: [critical pet peeve]
- Constructive: [constructive pet peeve]
Give extra weight to these in your review. The critical peeve is something you particularly
care about and will scrutinize. The constructive peeve is something you appreciate and will
reward when present.Both reviews are independent and blind — neither referee sees the other's report.
Every major comment MUST include a "What would change my mind" statement — not just "this is wrong" but the specific evidence, test, or analysis that would resolve the concern.
Dispatch the editor agent again with both referee reports.
The editor:
Save all outputs to quality_reports/reviews/:
YYYY-MM-DD_desk_review.md (Phase 1)YYYY-MM-DD_referee_domain.md (Phase 2)YYYY-MM-DD_referee_methods.md (Phase 2)YYYY-MM-DD_editorial_decision.md (Phase 3)Log the referee assignments (dispositions + pet peeves) in the editorial decision so the user can re-run with different combinations.
--peer --r2 [journal])Continues the review cycle after the author has revised the paper.
quality_reports/reviews/You previously reviewed this paper. Your prior report is attached.
Check whether each concern you raised has been adequately addressed.
New concerns may arise from the revisions. Score the revision, not
the original — improvement matters.They check whether each concern was: Resolved / Partially resolved / Not addressed. They may flag new concerns from the revisions.
_r2 or _r3 suffix to quality_reports/reviews/--stress [journal])Same three-phase flow as --peer, with these changes:
You are looking for reasons to REJECT this paper. Your prior is that
the paper is not good enough for [journal]. The authors must convince
you otherwise. Be specific about what would change your mind.This is for pre-submission stress testing. If the paper survives two hostile referees, it's ready.
--code or auto-detect .R/.py/.do/.jl)Dispatch coder-critic in standalone mode.
Strategic alignment (categories 1-3) — only run within the pipeline or via --methods:
| # | Category | What It Checks | |---|----------|----------------| | 1 | Design fidelity | Does code implement the strategy memo's design? | | 2 | Estimand alignment | Does code estimate what the paper claims? | | 3 | Specification match | Do controls, fixed effects, and samples match the paper? |
Code quality (categories 4-12) — always run in standalone mode:
| # | Category | What It Checks | |---|----------|----------------| | 4 | Script structure | Header, sections, logical flow | | 5 | Console hygiene | No print/cat pollution, clean output | | 6 | Reproducibility | set.seed, relative paths, no hardcoded values | | 7 | Function design | DRY, appropriate abstraction level | | 8 | Figure quality | Labels, dimensions, theme, transparency | | 9 | RDS pattern | saveRDS for all computed objects | | 10 | Comments | Explain why, not what | | 11 | Error handling | Graceful failures, informative messages | | 12 | Polish | Consistent style, no dead code, clean namespace |
| Example | Severity | |---------|----------| | Missing set.seed() in stochastic script | Major | | Hardcoded absolute path (/Users/name/...) | Major | | No error handling on data load | Major | | Missing comment on complex transformation | Minor | | Inconsistent naming convention | Minor | | Dead code left in script | Minor | | Missing figure axis labels | Major | | Using print() for debugging left in production | Minor | | No package loading section at top of script | Major |
Do NOT edit any source files. Only produce reports. Fixes are applied after user review, either manually or by re-dispatching the Coder agent.
Save report to quality_reports/[file]_code_review.md
--methods)Dispatch strategist-critic standalone for a full 4-phase causal inference review.
Phase 1: Claim Identification
Phase 2: Core Design Validity
Phase 3: Inference
Phase 4: Polish and Completeness
Save report to quality_reports/[file]_strategy_review.md
--proofread)Dispatch writer-critic standalone:
quality_reports/[file]_proofread_report.md--replicate [language]).claude/references/domain-profile.md Quality Tolerance ThresholdsThe Verifier produces a binary PASS/FAIL result:
For papers (.tex):
??, no undefined citations)For code (.R, .py, .do, .jl):
set.seed() present once at top if stochasticFor replication packages:
Verifier score maps to 0 (FAIL) or 100 (PASS) for weighted aggregation.
| Mode | Blocking? | Gate | |------|-----------|------| | Comprehensive | Yes | 80 commit, 90 PR | | Peer Review | Yes | Editorial decision | | Stress Test | Advisory | Reported, non-blocking | | Code Review | Yes | 80 commit | | Causal Audit | Yes | 80 commit | | Proofread | Yes (paper), Advisory (talks) | 80 commit |
/review --peer twice gives different feedback — just like submitting to two journals would.set.seed() is Major; missing comment is Minor.Other measured skills in the registry, with their headline benchmark lift.