Agent skill
survey-visuals
Draft non-prose visuals artifacts (timeline, figure specs) for a survey, grounded in evidence and using citation keys from `citations/ref.bib`. **Trigger**: survey visuals, timeline, figures, visuals, 图表, 时间线, figure spec. **Use when**: survey 的 C4(NO PROSE),已有 outline + claim/evidence + citations,需要先把时间线/图规格落盘。 **Skip if**: 你只关心正文(可跳过);或缺少 `citations/ref.bib`。 **Network**: none. **Guardrail**: NO PROSE;产物必须具体且可核对(含 citations),禁止遗留 TODO/SCAFFOLD。
Install this agent skill to your Project
npx add-skill https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/survey-visuals
SKILL.md
Survey Visuals (timeline + figure specs; NO PROSE)
This skill creates non-prose artifacts that make the writing stage less template-y:
- timeline / evolution bullets
- figure specs (what to draw, why it matters, what papers support it)
Load Order
Always read:
references/overview.mdreferences/figure_archetypes.md
Read by task:
references/timeline_patterns.mdwhen building timeline milestones
Machine-readable assets:
assets/figure_templates.yaml— figure archetype specifications (extensible without code changes)
Script Boundary
Use scripts/run.py only for:
- deterministic assembly of timeline bullets from paper_notes + bibkeys
- table generation from outline + mapping
- figure spec skeleton generation using
assets/figure_templates.yaml
Do not treat run.py as the place for:
- hardcoded figure descriptions or narratives
- milestone selection heuristics that should be inspectable from references
Tables are handled by dedicated table skills:
table-schema->outline/table_schema.mdtable-filler->outline/tables_index.md(internal index)appendix-table-writer->outline/tables_appendix.md(reader-facing Appendix tables)
Inputs
outline/outline.ymloutline/claim_evidence_matrix.mdpapers/paper_notes.jsonlcitations/ref.bib
Outputs
outline/timeline.mdoutline/figures.md
Workflow inputs (explicit)
- Use
outline/outline.yml+outline/claim_evidence_matrix.mdto decide what to visualize. - Use
papers/paper_notes.jsonlfor year/milestone candidates. - Use only citation keys from
citations/ref.bib.
Workflow (heuristic)
- Read the outline + claim-evidence matrix and pick recurring comparison axes.
- Timeline (
outline/timeline.md):- Write year -> key milestone bullets (aim for breadth and citations).
- Figures (
outline/figures.md):- Write 2-4 figure specs that a human could draw:
- purpose (what insight this figure communicates)
- required elements (boxes/arrows/axes)
- what papers support each element (cite keys)
- Write 2-4 figure specs that a human could draw:
- Use only citation keys present in
citations/ref.bib.
Quality checklist
- No
TODOand no<!-- SCAFFOLD ... -->markers remain in the outputs. -
outline/timeline.mdcontains >=8 year bullets and each bullet has >=1 citation marker[@...]. -
outline/figures.mdcontains >=2 figure specs and each mentions at least one supporting citation.
Helper script (optional)
Quick Start
python .codex/skills/survey-visuals/scripts/run.py --helppython .codex/skills/survey-visuals/scripts/run.py --workspace <workspace_dir>
All Options
--workspace <workspace_dir>(required)--unit-id <id>(optional; used only for runner bookkeeping)--inputs <a;b;c>(optional; defaults to the four Inputs listed above)--outputs <timeline_rel;figures_rel>(optional; defaults tooutline/timeline.md;outline/figures.md)--checkpoint <C#>(optional; ignored by the helper)
Examples
-
Generate timeline + figures with defaults:
python .codex/skills/survey-visuals/scripts/run.py --workspace workspaces/<ws> -
Generate to custom output paths:
python .codex/skills/survey-visuals/scripts/run.py --workspace workspaces/<ws> --outputs outline/timeline.md;outline/figures.md
Notes
- The helper is intentionally minimal and never overwrites non-placeholder artifacts.
- In strict mode it blocks only if placeholder markers remain (and if minimum timeline/figure requirements are not met).
Troubleshooting
Issue: timeline is thin or citation-free
Fix:
- Prefer fewer, higher-signal milestones, but ensure each bullet has >=1
[@...]. - Route upstream if notes are thin: strengthen
paper-notes/evidence-draftrather than padding.
Issue: figure specs read like prose
Fix:
- Keep specs as draw-instructions: purpose + elements + what each element is supported by (cite keys).
- Move narrative explanation into the main text; this file should stay non-prose.
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
thesis-compile-review
对中文毕业论文进行编译、warning 分级、模板模式检查、数据与引用复查,并把问题回写成可继续迭代的 review checklist。 **Trigger**: 毕业论文编译检查, thesis compile review, warning 分级, 终稿复查, main.pdf 检查. **Use when**: 论文已经回写到 TeX 交付层,需要确认是否真正达到“可提交”的质量,而不是只做到能编译。 **Skip if**: 还处于中间层重构阶段,`chapters/*.tex` 尚未形成稳定交付稿。 **Network**: none. **Guardrail**: 不在这里重构章节主线;如果发现结构问题,明确回退到上游修复。
front-matter-writer
Write the survey's front matter files (Abstract, Introduction, Related Work, Discussion, Conclusion) in paper voice, with high citation density and a single evidence-policy paragraph. **Trigger**: front matter writer, introduction writer, related work writer, abstract writer, discussion writer, conclusion writer, 引言, 相关工作, 摘要, 讨论, 结论. **Use when**: you are in C5 (prose allowed) and need the paper-like shell to stop the draft reading like stitched subsections. **Skip if**: `Approve C2` is missing in `DECISIONS.md`, or `citations/ref.bib` is missing. **Network**: none. **Guardrail**: no invented facts/citations; no pipeline jargon in final prose; no repeated evidence disclaimers; only use keys present in `citations/ref.bib`.
thesis-question-list
维护中文毕业论文的 `codex_md/question_list.md`:把本轮问题、边界、优先级、协作方案和验收口径结构化,作为整条 thesis pipeline 的控制面。 **Trigger**: 毕业论文问题清单, thesis question list, 论文修改清单, 本轮目标, 结构问题梳理, review问题整理. **Use when**: 你已经有一批材料或上一轮 review 结果,需要明确这一轮到底修什么、不修什么,并给后续重构与编译复查提供统一入口。 **Skip if**: 当前只是在做一次性局部措辞修改,且没有形成新一轮结构/证据/编译问题。 **Network**: none. **Guardrail**: 不在这里写正文;不把问题单写成长篇散文;每条问题必须可执行、可验收。
novelty-matrix
Create a novelty/prior-work matrix comparing the submission’s contributions against related work (overlaps vs deltas). **Trigger**: novelty matrix, prior-work matrix, overlap/delta, 相关工作对比, 新颖性矩阵. **Use when**: peer review 中评估 novelty/positioning,需要把贡献与相关工作逐项对齐并写出差异点证据。 **Skip if**: 缺少 claims(先跑 `claims-extractor`)或你不打算做新颖性定位分析。 **Network**: none (retrieval of additional related work is out-of-scope unless provided). **Guardrail**: 明确 overlap 与 delta;尽量给出可追溯证据来源(来自稿件/引用/作者陈述)。
protocol-writer
Write a systematic review protocol into `output/PROTOCOL.md` (databases, queries, inclusion/exclusion, time window, extraction fields). **Trigger**: protocol, PRISMA, systematic review, inclusion/exclusion, 检索式, 纳入排除. **Use when**: systematic review pipeline 的起点(C1),需要先锁定 protocol 再开始 screening/extraction。 **Skip if**: 不是做 systematic review(或 protocol 已经锁定且不允许修改)。 **Network**: none. **Guardrail**: protocol 必须包含可执行的检索与筛选规则;需要 HUMAN 签字后才能进入 screening。
rubric-writer
Write a rubric-based peer review report (`output/REVIEW.md`) using extracted claims and evidence gaps (novelty/soundness/clarity/impact). **Trigger**: rubric review, referee report, peer review write-up, 审稿报告, REVIEW.md. **Use when**: peer-review pipeline 的最后阶段(C3),已有 `output/CLAIMS.md` + `output/MISSING_EVIDENCE.md`(以及可选 novelty matrix)。 **Skip if**: 上游产物未就绪(claims/evidence gaps 缺失)或你不打算输出完整审稿报告。 **Network**: none. **Guardrail**: 给可执行建议(actionable feedback),并覆盖 novelty/soundness/clarity/impact;避免泛泛而谈。
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