tailor-to-venue

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English

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Chinese

Tailor to Venue

适配目标会议/期刊

Diff a draft against a target venue's requirements and produce a concrete tailoring plan: what to reposition, what to cut, what to reformat, and what to anonymize — before any edit is made. This skill plans; the user (or a follow-up request) executes the edits.

将草稿与目标会议/期刊的要求进行对比，生成一份具体的 适配计划：需要重新定位哪些内容、删减哪些内容、重新格式化哪些内容，以及需要匿名化哪些内容——在进行任何编辑前完成规划。本技能仅负责制定计划；用户（或后续请求）负责执行编辑操作。

When to use

使用场景

Retargeting a paper (new submission, rejection, or venue switch) to a different conference, journal, track, or page limit.
Converting between template families (acmart / IEEEtran / NeurIPS-style / llncs) or between blind levels (single ↔ double ↔ triple).
Deciding which track at one venue fits the work best.

Related skills:

parse-cfp

(build a missing venue profile),

select-venue

(choose the venue first),

preflight-check

(final desk-reject lint before submission),

prepare-camera-ready

(after acceptance).

将论文重新定位至不同会议、期刊、赛道或页数限制（新提交、被拒后改投或更换会议/期刊）。
在模板系列（acmart / IEEEtran / NeurIPS-style / llncs）之间转换，或在盲审级别（单盲 ↔ 双盲 ↔ 三盲）之间切换。
确定目标会议的哪个赛道最适合当前研究工作。

Inputs

输入项

The draft: main
```
.tex
```
file (the scripts resolve
```
\input
```
/
```
\include
```
); optionally the compiled PDF and
```
.bib
```
files.
Target venue profile:
```
venues/conferences/<venue-id>.yml
```
(schema:
```
venues/schema.yml
```
; family defaults merge automatically from
```
venues/families/
```
).
Target track name, if the user has chosen one.

论文草稿：主
```
.tex
```
文件（脚本会解析
```
\input
```
/
```
\include
```
命令）；可选提供编译后的PDF文件和
```
.bib
```
文件。
目标会议/期刊配置文件：
```
venues/conferences/<venue-id>.yml
```
（ schema:
```
venues/schema.yml
```
；系列默认配置会自动从
```
venues/families/
```
合并）。
目标赛道名称（若用户已选定）。

Process

流程

1. Resolve the venue profile

1. 解析会议/期刊配置文件

Find the profile in

venues/conferences/

. If none exists, do NOT invent requirements — run the

parse-cfp

skill against the venue's CFP URL to create one, or proceed with only facts quoted live from the CFP.

在

venues/conferences/

中查找配置文件。若不存在，请勿自行编造要求——针对会议/期刊的CFP URL运行

parse-cfp

技能来创建配置文件，或仅依据CFP中的实时事实进行操作。

2. Re-verify against the live CFP (mandatory)

2. 对照实时CFP重新验证（必填）

Profiles go stale and a wrong page limit causes a desk reject. Fetch the profile's

cfp_url

and re-verify before relying on anything: page limits and exclusions for the chosen track, deadlines and timezone, blind level, template/documentclass invocation, and required sections. Note in the plan what was verified and when; if the live CFP contradicts the profile, the CFP wins — flag the profile for update. If the CFP cannot be fetched, mark every profile-derived fact "UNVERIFIED — confirm on CFP" in the plan.

配置文件可能过时，错误的页数限制会导致初审被拒。获取配置文件中的

cfp_url

，在依赖任何信息前重新验证：所选赛道的页数限制与排除项、截止日期及时区、盲审级别、模板/documentclass调用方式，以及必填章节。在计划中记录验证内容和时间；若实时CFP与配置文件存在冲突，以CFP为准——标记配置文件需更新。若无法获取CFP，在计划中将所有来自配置文件的事实标记为“未验证——请确认CFP”。

3. Pick the track with the user

3. 与用户确认赛道选择

List the profile's tracks with their page limits (the venue diff report includes this table). If the user has not chosen, recommend one based on the work's strongest claim — see references/contribution-reframing.md for what each track rewards — and confirm before planning.

列出配置文件中的所有赛道及其页数限制（会议差异报告包含此表格）。若用户未选定赛道，根据研究工作的核心主张推荐最适合的赛道——参考 references/contribution-reframing.md了解各赛道偏好的内容——并在制定计划前征得用户确认。

4. Run the deterministic diff

4. 运行确定性对比

Run from the repo root (or pass absolute paths):

python3 skills/tailor-to-venue/scripts/venue_diff.py <main.tex> --venue venues/conferences/<id>.yml --track <Track>

This reports template/option gaps, required-section gaps, abstract length, author-block vs blind level, page-limit context, and the venue facts (submission system, deadlines, LLM policy) to carry into the plan.

Then size the page budget:

python3 skills/tailor-to-venue/scripts/page_budget.py <main.tex> --venue venues/conferences/<id>.yml --track <Track>

And scan anonymization at the venue's blind level (add

--pdf <paper.pdf>

and

--bib <refs.bib>

when available):

python3 skills/tailor-to-venue/scripts/anon_sweep.py <main.tex> --venue venues/conferences/<id>.yml

All three print Markdown and exit 2 with a clear message on bad input. Treat script outputs as signals: the compiled PDF and the live CFP are ground truth.

从仓库根目录运行（或传入绝对路径）：

python3 skills/tailor-to-venue/scripts/venue_diff.py <main.tex> --venue venues/conferences/<id>.yml --track <Track>

该脚本会报告模板/选项差异、必填章节缺失情况、摘要长度、作者信息块与盲审级别匹配情况、页数限制背景，以及需纳入计划的会议/期刊相关信息（提交系统、截止日期、LLM政策）。

然后计算页数预算：

python3 skills/tailor-to-venue/scripts/page_budget.py <main.tex> --venue venues/conferences/<id>.yml --track <Track>

并根据会议/期刊的盲审级别扫描匿名化情况（若有可用文件，添加

--pdf <paper.pdf>

和

--bib <refs.bib>

参数）：

python3 skills/tailor-to-venue/scripts/anon_sweep.py <main.tex> --venue venues/conferences/<id>.yml

这三个脚本均会输出Markdown格式内容，若输入有误则以状态码2退出并给出清晰提示。将脚本输出作为参考信号：编译后的PDF和实时CFP为最终依据。

5. Build the four-part plan

5. 构建四部分计划

Turn the script reports into prose plans using the references:

Contribution reframing — retitle, re-abstract, rewrite contribution bullets and evaluation emphasis for the chosen track: references/contribution-reframing.md
Page-budget cutting plan — ordered ladder from structural exports to line-level compression, with estimated savings per step and the forbidden moves listed: references/page-budget-cutting.md
Template switch plan — only if venue_diff reports a class/option gap; per-direction breakage list and bibliography mapping: references/template-switching.md
Anonymization sweep plan — fix strategy per leak category, plus the beyond-the-PDF checklist and a
```
camera-ready-restore.md
```
for removed content: references/anonymization-sweep.md

If the draft needs new citations from the target community, route every one through the

verify-citations

skill — never add an unverified reference.

结合参考文档将脚本报告转换为书面计划：

贡献重构——针对所选赛道重新拟定标题、摘要、贡献要点并重写评估重点： references/contribution-reframing.md
页数预算缩减计划——从结构性删减到逐行压缩的有序步骤，列出每一步的预估缩减量及禁止操作：references/page-budget-cutting.md
模板转换计划——仅当venue_diff报告存在类/选项差异时执行；列出双向转换的问题清单及参考文献映射规则： references/template-switching.md
匿名化检查计划——针对每类信息泄露问题制定修复策略，附加PDF之外的检查清单及用于恢复删除内容的
```
camera-ready-restore.md
```
：references/anonymization-sweep.md

若草稿需要添加目标领域的新参考文献，需通过

verify-citations

技能处理——绝不添加未验证的参考文献。

6. Deliver the plan

6. 交付计划

Write

tailoring-plan-<venue-id>-<track>.md

next to the draft with sections:

Verification record — what was checked against the live CFP, when, and any profile contradictions found.
Track fit and contribution reframing (with rewritten title/abstract/ contribution-bullet drafts marked as proposals).
Page-budget cutting plan (current estimate → target, ordered cuts with estimated savings, restore list).
Template switch plan (or "no switch needed").
Anonymization sweep plan (findings with fixes, beyond-the-PDF checklist).
Submission logistics — system, URL, deadlines with timezone, rebuttal format, LLM-policy disclosure needs.

Offer to execute the plan step by step; after edits, recommend

preflight-check

as the final gate.

在草稿旁生成

tailoring-plan-<venue-id>-<track>.md

文件，包含以下章节：

验证记录——对照实时CFP检查的内容、时间，以及发现的配置文件冲突。
赛道适配性与贡献重构（包含拟定的新标题/摘要/贡献要点草案）。
页数预算缩减计划（当前预估页数 → 目标页数，有序删减步骤及预估缩减量，恢复清单）。
模板转换计划（或标注“无需转换”）。
匿名化检查计划（问题发现及修复方案，PDF之外的检查清单）。
提交流程细节——提交系统、URL、带时区的截止日期、反驳格式、LLM政策披露要求。

可主动提出分步执行计划；编辑完成后，建议使用

preflight-check

作为最终检查环节。

Worked example

示例案例

A double-blind KDD draft was rejected; the user wants to retarget it to SIGSPATIAL's Research track. Both venues use

acmart

sigconf, so this case exercises three of the four plan parts (no template switch) and shows the de-anonymization direction.

python3 skills/tailor-to-venue/scripts/venue_diff.py paper/main.tex \
    --venue venues/conferences/sigspatial-2026.yml --track Research

Reading the reports against the live SIGSPATIAL CFP, the plan comes out:

Verification. SIGSPATIAL Research is single-blind, 10 pages excl. references + appendix (KDD was double-blind, 8 pages) — both confirmed on the live CFP on the date of the diff.
Track fit / reframing. Same Research track, so light reframing: re-aim vocabulary and baselines at the spatial-data community and add the community-standard baseline KDD reviewers did not expect (references/contribution-reframing.md, "Cross-venue repositioning").
Page budget. The limit grew 8→10 pages, so this is a de-compression, not a cut: restore the ablation moved to the appendix for KDD and the examples trimmed for space.
```
page_budget.py
```
confirms headroom.
Template switch. None —
```
venue_diff
```
reports the class matches.
Anonymization (reverse sweep). The hard part. The draft is anonymized; SIGSPATIAL requires author names. Run
```
anon_sweep.py paper/main.tex --venue venues/conferences/sigspatial-2026.yml
```
— at single-blind it flags the leftover "Anonymous Author(s)" placeholder. Restore the real
```
\author
```
/
```
\affiliation
```
/
```
\email
```
block, drop the
```
anonymous
```
/
```
review
```
class options, re-link the real repository, and restore first-person framing. Keep funding out until camera-ready unless the CFP asks for it (references/anonymization-sweep.md, "De-anonymizing").

The deliverable is

tailoring-plan-sigspatial-2026-Research.md

; no draft file is touched until the user asks to execute a step.

一篇双盲评审的KDD论文被拒；用户希望将其重新定位至SIGSPATIAL的研究赛道。两个会议均使用

acmart

sigconf模板，因此本案例涵盖计划的三部分内容（无需模板转换），并展示了解匿名化的流程。

python3 skills/tailor-to-venue/scripts/venue_diff.py paper/main.tex \
    --venue venues/conferences/sigspatial-2026.yml --track Research

结合实时SIGSPATIAL CFP解读报告后，生成的计划如下：

验证结果：SIGSPATIAL研究赛道为单盲评审，10页正文（不含参考文献+附录）（KDD为双盲评审，8页正文）——两项信息均在对比当日通过实时CFP确认。
赛道适配性/重构：同属研究赛道，仅需轻度重构：调整术语和基准模型以适配空间数据领域，添加KDD评审未要求但该领域通用的基准模型（参考references/contribution-reframing.md中的“跨会议重新定位”部分）。
页数预算：页数限制从8页增至10页，因此无需缩减，反而可扩展内容：恢复为适配KDD而移至附录的消融实验内容，以及因篇幅限制删减的示例。
```
page_budget.py
```
确认存在剩余空间。
模板转换：无需转换——
```
venue_diff
```
报告显示模板类匹配。
匿名化（反向检查）：核心环节。当前草稿已匿名化，但SIGSPATIAL要求显示作者姓名。运行
```
anon_sweep.py paper/main.tex --venue venues/conferences/sigspatial-2026.yml
```
——在单盲评审模式下，脚本会标记残留的“Anonymous Author(s)”占位符。恢复真实的
```
\author
```
/
```
\affiliation
```
/
```
\email
```
块，移除
```
anonymous
```
/
```
review
```
类选项，重新链接真实代码仓库，并恢复第一人称表述。除非CFP要求，否则在终稿阶段再添加资助信息（参考references/anonymization-sweep.md中的“解匿名化”部分）。

最终交付文件为

tailoring-plan-sigspatial-2026-Research.md

；在用户要求执行具体步骤前，不会修改任何草稿文件。

Output

输出结果

A reviewed, verification-stamped

tailoring-plan-<venue-id>-<track>.md

, plus the three raw script reports on request. No draft files are modified by this skill unless the user asks for execution of specific plan items.

一份经过审核、带有验证标记的

tailoring-plan-<venue-id>-<track>.md

文件，若用户要求可提供三份原始脚本报告。除非用户要求执行计划中的特定项，否则本技能不会修改任何草稿文件。

Guardrails

约束规则

Never submit to any submission system on the user's behalf; stop at the plan.
Never state venue requirements from memory — profile + live-CFP verification only; unverifiable facts are labeled UNVERIFIED.
Never fabricate or hand-type citations; new references go through
```
verify-citations
```
.
Never plan template tampering (negative
```
\vspace
```
, margin/font tricks) to meet a page limit — these are desk-reject triggers.
Do not paste text from other authors' papers into the draft; exemplar study happens transiently via the
```
study-exemplars
```
skill.

绝不代表用户提交至任何提交系统；仅制定计划。
绝不凭记忆陈述会议/期刊要求；仅依据配置文件+实时CFP验证的信息；无法验证的事实需标记为“未验证”。
绝不编造或手动输入参考文献；新参考文献需通过
```
verify-citations
```
技能处理。
绝不制定通过篡改模板（如负
```
\vspace
```
、修改边距/字体）来满足页数限制的计划——此类操作会导致初审被拒。
不得将其他作者论文中的文本粘贴至草稿；如需参考范例，需通过
```
study-exemplars
```
技能临时处理。