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Agent Skill · 研究检索

writer-selfloop(作家自循环)

writer-selfloop 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。

writer-selfloop 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,权限为只读;许可证为 MIT,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 45,877。

总安装 823周安装 35GitHub Stars 422下载 288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
MIT

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:writer-selfloop(作家自循环)
来源仓库:https://github.com/willoscar/research-units-pipeline-skills
仓库路径:skills/writer-selfloop
安装命令:
npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill writer-selfloop
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill writer-selfloop

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。

writer-selfloop 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。适用于研究检索类任务,可结合来源仓库、安装命令和原始 README 继续核验具体用法。

通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和维护状态。安装前建议确认是否会触发联网、命令执行或文件读写,避免误操作生产数据。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/writer-selfloop

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/willoscar/research-units-pipeline-skills --ski…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

writer-selfloop 怎么安装?

在终端执行 npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill writer-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

writer-selfloop 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。

writer-selfloop 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

writer-selfloop 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

writer-selfloop 用的人多吗?

公开数据是累计安装 823 次,近一周安装 35 次,下载 288 次,GitHub 422 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。

writer-selfloop 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 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

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
writer-selfloop

作家自循环 · 本页

823422只读MIT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

Writer Self-loop (fix only what fails)

Purpose: make writing converge without rewriting the whole paper.

This is the writing self-healing loop:

Default mode: semantic triage (LLM-first)

Treat the gate as a router, not as a reason to rewrite everything.

  • First, classify each failure as: evidence substrate vs writing execution vs voice contamination vs citation hygiene.
  • Then, fix the earliest responsible artifact (often not the merged draft).
  • Rewrite only the failing files; do not churn working sections.

If you do not run the helper script, you can still execute this skill by reading sections/*.md + packs and writing output/WRITER_SELFLOOP_TODO.md manually in the same PASS/FAIL style.

Role cards (use explicitly)

Writing Manager (triage + convergence)

Mission: make the draft converge by fixing only failing units and routing issues upstream when needed.

Do:

  • Rewrite only files flagged by the gate (one at a time).
  • If evidence is thin, route upstream instead of padding prose.
  • Keep citation keys and scope stable during rewrites.

Avoid:

  • Global rewrites that churn working sections.
  • Rewriting around evidence gaps with generic filler.

Router (earliest responsible artifact)

Mission: connect a visible writing failure to the earliest upstream fix.

Do:

  • Template voice -> local rewrite (subsection-polisher / front-matter-writer / chapter-lead-writer).
  • Thin evidence -> evidence-selfloop (notes/bindings/packs).

Avoid:

  • Repeatedly rewriting the same section when the pack cannot support it.

Role prompt: Writing Manager (triage + convergence)

You are the writing manager for a survey draft.

Your job is to make the draft converge by fixing only what fails, and by routing issues to the earliest responsible artifact.

Rules:
- If a section fails because the evidence is thin or out-of-scope pressure is high, do NOT pad prose.
  Route upstream to evidence-selfloop (notes/bindings/packs) and unblock the substrate.
- If a section fails because the prose is templated (narration openers, slide navigation, repeated disclaimer spam), rewrite locally.
- Never change citation keys during rewrites; keep scope local.

Working style:
- small, auditable edits
- one failing file at a time
- every fix either (a) improves argument moves, or (b) restores paper voice
  • the gate is deterministic (it inspects sections/ + sections/sections_manifest.jsonl)
  • the fixes are semantic (rewrite prose to execute argument moves and restore paper voice)

Inputs

  • sections/sections_manifest.jsonl (expected files + allowed citations)
  • sections/*.md (the actual prose units)
  • outline/writer_context_packs.jsonl (preferred per-H3 pack)
  • outline/evidence_bindings.jsonl
  • citations/ref.bib

Optional routing context:

  • output/EVIDENCE_SELFLOOP_TODO.md (if evidence gaps are already known)
  • outline/subsection_briefs.jsonl, outline/chapter_briefs.jsonl

Output

  • output/WRITER_SELFLOOP_TODO.md (report-class; always written)

Workflow

  1. Run the gate
  • Run the writer self-loop script (see Script section below). It reads sections/sections_manifest.jsonl and the actual sections/*.md files.
  1. Read the TODO report
  • Open output/WRITER_SELFLOOP_TODO.md and identify the failing file paths.
  • For each failing H3, load its pack from outline/writer_context_packs.jsonl.
  • If a pack is missing or you need scope reminders, consult outline/subsection_briefs.jsonl; for chapter-level context (leads/throughlines), consult outline/chapter_briefs.jsonl.
  1. Triage (writing vs evidence)

Route upstream (run evidence-selfloop) when:

  • output/EVIDENCE_SELFLOOP_TODO.md already indicates missing anchors/comparisons for the same subsection
  • the pack in outline/writer_context_packs.jsonl is too thin to satisfy argument moves without guessing
  • you keep wanting out-of-scope citations outside outline/evidence_bindings.jsonl

Rewrite locally when:

  • the pack is rich enough, but prose is template-y (narration openers, slide navigation, repeated discourse stems)
  • the section has content but lacks a thesis, contrasts, evaluation anchoring, or limitations
  1. Use the right playbook for the failing file type
  • Front matter (sections/abstract.md, sections/S<sec_id>.md for Intro/Related Work, sections/discussion.md, sections/conclusion.md): use front-matter-writer.
  • Chapter leads (sections/S<sec_id>_lead.md): use chapter-lead-writer.
  • H3 bodies (sections/S<sub_id>.md): use subsection-writer (draft) or subsection-polisher (local fix).
  1. Keep scope + citations stable
  • Keep citation keys unchanged and validate them against citations/ref.bib.
  • Stay in scope per outline/evidence_bindings.jsonl (prefer subsection-first).
  1. Rerun the gate until PASS

After PASS (merge-aware voice safety):

  • Proceed to section-logic-polisher -> argument-selfloop -> paragraph-curator -> style-harmonizer -> opener-variator -> evaluation-anchor-checker -> transition-weaver -> section-merger -> post-merge-voice-gate.
  • If post-merge-voice-gate FAILs with source: transitions, fix outline/transitions.md via transition-weaver and re-merge (do not patch the merged draft).

After PASS (mandatory style hygiene for survey/deep):

  • Open output/WRITER_SELFLOOP_TODO.md and read ## Style Smells.
  • If it flags opener cadence / overview narration, run opener-variator on the listed files.
  • If it flags count-based limitation slots (e.g., Two limitations...), run limitation-weaver on the listed files.
  • Otherwise (or after micro-fixes), run style-harmonizer on the listed sections/*.md files.
  • Before merge, run evaluation-anchor-checker on the settled H3 files so any remaining numeric claims keep same-sentence task/metric/constraint context. Treat this as the last section-level sweep, not as a post-audit patch.
  • Keep meaning + citations fixed; treat this as surface-level rewrite, not new content.

How to fix a failing H3 (semantic recipe)

  • Use tension_statement + thesis from the pack to rewrite paragraph 1 (end with the thesis).
  • Use comparison_cards to write explicit A-vs-B contrast sentences.
  • Use evaluation_anchor_minimal / protocol snippets to add task/metric/constraint context.
  • Use limitation hooks to add a real caveat (not boilerplate).

Paper voice repairs (high-impact, low-risk)

Narration opener -> content claim:

  • Bad: This subsection surveys...
  • Better: start with a tension/decision/lens sentence, then end paragraph 1 with the thesis.

Slide navigation -> argument bridge:

  • Bad: Next, we move from X to Y.
  • Better: Having established X, we can now examine how Y changes the trade-offs under comparable protocols.

Meta "survey should" -> literature-facing observation:

  • Bad: Therefore, survey comparisons should...
  • Better: Across reported protocols,... varies, which makes... fragile unless...

Disclaimer spam -> one policy paragraph + local caveat only when needed:

  • Keep evidence policy once in front matter; delete repeated "abstract-only" boilerplate inside H3.

Stop conditions (when rewriting is the wrong move)

Stop and route upstream if:

  • you cannot write a contrast or evaluation anchor without guessing
  • the pack lacks benchmarks/metrics/protocol details needed for the subsection\x27s core claim
  • fixing one H3 keeps forcing out-of-scope citations

Failure codes -> routing (how to read the gate)

The writer gate emits short issue codes. Treat them as routers and stop trying to pad prose around missing evidence.

First classify failures:

  • Evidence substrate: packs/anchors/comparisons are too thin to execute argument moves without guessing. Route upstream (evidence-selfloop).
  • Writing execution: packs are rich enough, but the section did not execute moves (thesis/contrast/eval/limitation). Rewrite locally.
  • Voice contamination: narration/slide/pipeline voice. Rewrite locally (opener + bridges), do not touch citations.
  • Citation hygiene: undefined keys / out-of-scope pressure. Fix citations/bindings or rewrite to in-scope; do not add new keys.

Quick map (common codes):

  • missing_sections_manifest, empty_sections_manifest, sections_missing_files: run subsection-writer (create missing files + refresh manifest).
  • sections_h3_has_headings: remove headings; H3 bodies are body-only.
  • sections_intro_*, sections_related_work_*: rewrite front matter via front-matter-writer (dense positioning + one methodology note).
  • sections_h3_too_few_paragraphs, sections_h3_too_short: if the pack is rich, expand by executing contrasts + eval anchor + limitation; if the pack is thin, route to evidence-selfloop.
  • sections_h3_missing_contrast: add explicit A-vs-B using comparison_cards; if cards are missing, route to evidence-selfloop (briefs/packs).
  • sections_h3_missing_eval_anchor, sections_h3_missing_cited_numeric: add minimal protocol context (task/metric/constraint) in the same paragraph; if unknown, route upstream or weaken the claim.
  • sections_h3_missing_limitation: add a subsection-specific limitation; if none exists in the pack, route upstream.
  • sections_h3_narration_template_opener, sections_h3_slide_narration, sections_contains_pipeline_voice: rewrite openers/bridges to paper voice (no navigation commentary).
  • sections_h3_evidence_policy_disclaimer_spam: delete repeats; keep evidence policy once in front matter.
  • sections_cites_missing_in_bib: rerun citation-verifier (do not invent keys).
  • sections_cites_outside_mapping: rewrite to in-scope OR fix mapping/bindings (C2/C4) and rebuild packs; do not patch in the merged draft.
  • sections_h3_sparse_citations: if scope allows, plan adds via citation-diversifier then apply via citation-injector; if scope is too tight, expand mapping/bindings upstream.

Script (optional; deterministic gate)

Quick Start

  • python.codex/skills/writer-selfloop/scripts/run.py --workspace workspaces/<ws>

All Options

  • --workspace <dir>
  • --unit-id <U###>
  • --inputs <semicolon-separated>
  • --outputs <semicolon-separated>
  • --checkpoint <C#>

Examples

  • Generate an actionable TODO list for failing sections/*.md:

- python.codex/skills/writer-selfloop/scripts/run.py --workspace workspaces/<ws>

平台分布

Claude Code

30.32%
按下载量换算87

Gemini CLI

23.73%
按下载量换算68

Cursor

18.78%
按下载量换算54

Codex

11.41%
按下载量换算33

OpenCode

8.14%
按下载量换算23

Antigravity

3.73%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

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