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Agent Skill · 研究检索

seven-pass-review(七次通过审查)

seven-pass-review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

seven-pass-review 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 72,323。

总安装 188周安装 8GitHub Stars 973下载 66核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:seven-pass-review(七次通过审查)
来源仓库:https://github.com/pedrohcgs/claude-code-my-workflow
仓库路径:skills/seven-pass-review
安装命令:
npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill seven-pass-review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill seven-pass-review

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合根据关键词、任务场景或来源线索快速定位候选结果。可结合来源仓库、安装命令和原始 README 核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。seven-pass-review 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/seven-pass-review

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill seve…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

seven-pass-review 怎么安装?

在终端执行 npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill seven-pass-rev…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

seven-pass-review 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

seven-pass-review 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill seven-pass-review 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

seven-pass-review 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

seven-pass-review 用的人多吗?

公开数据是累计安装 188 次,近一周安装 8 次,下载 66 次,GitHub 973 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

seven-pass-review 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
seven-pass-review

七次通过审查 · 本页

188973执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Seven-Pass Adversarial Review

Runs seven independent reviewers, each focused on a single lens, then synthesizes their findings into one prioritized revision plan. Pattern 15 from the workflow guide, mechanized.

Why seven passes? A single-agent review blends lenses and softens each one. Seven forked agents each approach the paper with full context budget for their own lens, then a synthesizer resolves conflicts and de-duplicates.

When to pick this over /review-paper: This skill costs roughly 7× more tokens than /review-paper (default) and ~2× more than /review-paper --adversarial. Use it when the paper is submission-ready or at R&R stage and you need maximum lens coverage. For early drafts or iterative work, /review-paper is the right tool. For journal-simulation pressure test, use /review-paper --peer <journal> instead.

Inputs

  • $0 — manuscript path (.tex, .qmd, .md, or .pdf). Required.

The Seven Lenses

Each lens runs as a forked subagent (context: fork) so the main conversation stays clean.

#LensFocusAgent type
1Abstract auditDoes the abstract state the question, method, result, and contribution? Does it match the paper?general-purpose
2Intro structureDoes the intro follow Cochrane / Varian framework? Literature placement? Contribution clarity?general-purpose
3Methods / identificationAre assumptions stated? Is identification credible? Are alternatives addressed?domain-reviewer
4Results + tablesDo tables read standalone? Is magnitude + significance discussed? Units consistent?general-purpose
5RobustnessAre obvious threats pre-empted? Is the robustness section convincing or theatrical?general-purpose
6Prose qualitySentence-level clarity, hedging, passive voice, paragraph cohesionproofreader
7Citation auditInvokes /validate-bib --semantic; checks cite-claim direction for top-10 worksgeneral-purpose

Workflow

Phase 0: Pre-flight

  1. Resolve manuscript path.
  2. Decide if .pdf → extract text first (pdftotext -layout).
  3. Create output dir: quality_reports/seven_pass_[stem]/.

Phase 1: Spawn 7 reviewers in parallel

In a single message, spawn 7 Task tool calls (one per lens). Each subagent gets:

  • The manuscript path (to re-read with its own context).
  • The lens-specific prompt (below).
  • Instructions to write to quality_reports/seven_pass_[stem]/lens_[N]_[lens-name].md.
  • Severity tagging: CRITICAL / MAJOR / MINOR.

Lens prompt rubrics are embedded inline below — one summary paragraph per lens. Each forked subagent receives its lens's rubric plus the manuscript path.

Lens prompt summaries:

  • Lens 1 (Abstract): Does the first sentence state the question? Does it name the method? Quantify the headline result? State one-sentence contribution? Cross-check: do these four things match the body?
  • Lens 2 (Intro): Does the intro open with the question? Hook → context → contribution → roadmap? Lit review placed correctly (after the hook, not before)? Contribution-counted (1, 2, 3…)? Preview of findings with magnitudes?
  • Lens 3 (Methods): Is every assumption stated? Are they strong or weak? Is identification one-liner clear? Are known violations (selection, measurement, reverse causality, SUTVA) addressed? Are instruments / RDD / DiD assumptions explicit and defensible?
  • Lens 4 (Results): Does each table read standalone (caption, units, SEs clarified)? Is magnitude interpreted (not just significance)? Are units consistent across tables? Are figures legible at 8pt?
  • Lens 5 (Robustness): Does the paper ANTICIPATE a sharp referee's objections? Are robustness checks motivated, or just listed? Power/placebo tests present? Heterogeneity explored where promised?
  • Lens 6 (Prose): Sentences under 30 words? Active voice dominant? Hedging proportionate (neither overclaiming nor endless "may suggest")? Paragraph topic sentences?
  • Lens 7 (Citations): Invoke /validate-bib --semantic. For top-10 cited works, does the in-text claim match the cited paper's actual finding direction? Are contemporary / competing works cited?

Phase 2: Synthesize

Wait for all 7 lens reports. Then read them and produce:

quality_reports/seven_pass_[stem]/_SYNTHESIS.md

# Seven-Pass Review: [Manuscript]

**Date:** YYYY-MM-DD
**Path:** [manuscript]

## Executive verdict

**Overall state:** [SUBMIT / REVISE-MINOR / REVISE-MAJOR / REJECT-AND-RESTART]

## Cross-lens CRITICAL issues
| # | Lens(es) | Issue | Recommendation |
|---|---|---|---|

## MAJOR issues (second-round)
| # | Lens(es) | Issue |
|---|---|---|

## MINOR polish
[bulleted]

## Per-lens scorecard
| Lens | Critical | Major | Minor | Score/10 |
|---|---|---|---|---|
| 1. Abstract | | | | |
| 2. Intro | | | | |
| 3. Methods | | | | |
| 4. Results | | | | |
| 5. Robustness | | | | |
| 6. Prose | | | | |
| 7. Citations | | | | |
| **Overall** | | | | |

## Revision plan (in recommended order)
1. [Highest-leverage fix — usually a lens with 2+ CRITICALs]
2. …
7. [Lowest-leverage polish]

## Contradictions between lenses
[If two lenses disagree, surface here. E.g., Lens 2 says "expand contribution" but Lens 6 says "trim intro".]

Phase 3: Token-budget report

After synthesis, print:

Seven-pass review complete.
Subagents: 7 (parallel) + 1 synthesizer.
Approx token usage: ~80–120k (vs ~15k for single-pass /review-paper).
Runtime: ~3–5 min wall-clock.
For cheaper alternatives:
  - Single-pass: /review-paper
  - Iterative: /review-paper --adversarial

When to use this skill

  • Before first submission to a top journal.
  • After a major revision when you want to catch drift.
  • R&R when referees disagree — surfaces contradictions your revision must navigate.

When NOT to use

  • Early drafts (use /review-paper single-pass first).
  • Short notes, comments, or replies (overkill).
  • When you've already run this in the last 7 days and nothing substantive changed.

Cross-references

  • .claude/skills/review-paper/SKILL.md — the single-pass and --adversarial modes (cheaper, faster).
  • .claude/skills/validate-bib/SKILL.md — invoked by Lens 7.
  • .claude/skills/audit-reproducibility/SKILL.md — complementary; numeric-claims side of the audit.
  • Workflow guide, Pattern 15 — the narrative explanation of why seven lenses.

Exit behavior

  • Exits 0 always (review is informational). The synthesis report's "Executive verdict" is the gate.
  • Any CRITICAL at the top of the synthesis should block submission until resolved.

What this skill does NOT do

  • Re-run seven lenses if the manuscript hasn't changed — check git diff against last run date in _SYNTHESIS.md, skip unchanged lenses if requested via --incremental (future).
  • Auto-apply fixes — that's /review-paper --adversarial's job.
  • Replace human judgment. A reviewer who knows your subfield still beats seven LLMs.

平台分布

Codex

33.57%
按下载量换算22

Claude

28.6%
按下载量换算19

Cursor

18.48%
按下载量换算12

Gemini CLI

9.38%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill seven-pass-review 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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