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WILLOSCAR
GitHub creator profile

WILLOSCAR

Repository-level view of 108 collected skills across 1 GitHub repositories, including approximate occupation coverage.

skills collected
108
repositories
1
occupation fields
3
updated
2026-05-30
repository explorer

Repositories and representative skills

#001
research-units-pipeline-skills
108 skills44931updated 2026-05-30
100% of creator
agent-survey-corpus
Rédacteurs techniques

Download a small corpus of open-access arXiv survey/review PDFs about agentic systems and extract text for style learning. **Trigger**: agent survey corpus, ref corpus, download surveys, 学习综述写法, 下载 survey. **Use when**: you want to study how real agent surveys structure sections (6–8 H2), size subsections, and write evidence-backed comparisons. **Skip if**: you cannot download PDFs (no network) or you don't want local PDF files. **Network**: required. **Guardrail**: only download arXiv PDFs; store under `ref/` and keep large files out of git.

2026-05-30
global-reviewer
Rédacteurs en chef

Global consistency review for survey drafts: terminology, cross-section coherence, and scope/citation hygiene. Writes `output/GLOBAL_REVIEW.md` and (optionally) applies safe edits to `output/DRAFT.md`. **Trigger**: global review, consistency check, coherence audit, 术语一致性, 全局回看, 章节呼应, 拷打 writer. **Use when**: Draft exists and you want a final evidence-first coherence pass before LaTeX/PDF. **Skip if**: You are still changing the outline/mapping/notes (do those first), or prose writing is not approved. **Network**: none. **Guardrail**: Do not invent facts or citations; do not add new citation keys; treat missing evidence as a failure signal.

2026-05-30
literature-engineer
Biologistes, autres

Multi-route literature expansion + metadata normalization for evidence-first surveys. Produces a large candidate pool (`papers/papers_raw.jsonl`, target ≥1200) with stable IDs and provenance, ready for dedupe/rank + citation generation. **Trigger**: evidence collector, literature engineer, 文献扩充, 多路召回, snowballing, cited by, references, 元信息增强, provenance. **Use when**: 需要把候选文献扩充到 ≥1200 篇并补齐可追溯 meta(survey pipeline 的 Stage C1,写作前置 evidence)。 **Skip if**: 已经有高质量 `papers/papers_raw.jsonl`(≥1200 且每条都有稳定标识+来源记录)。 **Network**: 可离线(靠 imports);雪崩/在线检索需要网络。 **Guardrail**: 不允许编造论文;每条记录必须带稳定标识(arXiv id / DOI / 可信 URL)和 provenance;不写 output/ prose。

2026-05-30
pdf-text-extractor
Développeurs de logicielsTravailleurs du bureau et du soutien administratif, autres

Download PDFs (when available) and extract plain text to support full-text evidence, writing `papers/fulltext_index.jsonl` and `papers/fulltext/*.txt`. **Trigger**: PDF download, fulltext, extract text, papers/pdfs, 全文抽取, 下载PDF. **Use when**: `queries.md` 设置 `evidence_mode: fulltext`(或你明确需要全文证据)并希望为 paper notes/claims 提供更强 evidence。 **Skip if**: `evidence_mode: abstract`(默认);或你不希望进行下载/抽取(成本/权限/时间)。 **Network**: fulltext 下载通常需要网络(除非你手工提供 PDF 缓存在 `papers/pdfs/`)。 **Guardrail**: 缓存下载到 `papers/pdfs/`;默认不覆盖已有抽取文本(除非显式要求重抽)。

2026-05-30
prose-writer
Rédacteurs techniques

Write `output/DRAFT.md` (or `output/SNAPSHOT.md`) from an approved outline and evidence packs, using only verified citation keys from `citations/ref.bib`. **Trigger**: write draft, prose writer, snapshot, survey writing, 写综述, 生成草稿, section-by-section drafting. **Use when**: structure is approved (`DECISIONS.md` has `Approve C2`) and evidence packs exist (`outline/subsection_briefs.jsonl`, `outline/evidence_drafts.jsonl`). **Skip if**: approvals are missing, or evidence packs are incomplete / scaffolded (missing-fields, TODO markers). **Network**: none. **Guardrail**: do not invent facts or citations; only cite keys present in `citations/ref.bib`; avoid pipeline-jargon leakage in final prose.

2026-05-30
schema-normalizer
Développeurs de logiciels

Normalize cross-skill JSONL interfaces (ids + titles + citation key formats) so downstream skills do not rely on best-effort joins. **Trigger**: schema normalize, jsonl contract, interface drift, join drift, 字段不一致, schema 规范化. **Use when**: you have generated C2-C4 JSONL artifacts (outline/briefs/bindings/packs/anchors) and want deterministic, stable fields before self-loops/writing. **Skip if**: you are not using the survey pipelines, or the workspace already has a fresh PASS `output/SCHEMA_NORMALIZATION_REPORT.md` for the current artifacts. **Network**: none. **Guardrail**: NO PROSE; deterministic transforms only; do not invent evidence/claims; only fill missing ids/titles from `outline/outline.yml`.

2026-05-30
writer-selfloop
Rédacteurs en chef

Writing self-loop for surveys: run the strict section-quality gate, then rewrite only the failing `sections/*.md` files until the report is PASS. **Trigger**: writer self-loop, writing loop, quality gate loop, rewrite failing sections, 自循环, 反复改到 PASS. **Use when**: per-section files exist but C5 is FAIL/BLOCKED (thin sections, missing leads/front matter, citation-scope violations, generator voice). **Skip if**: you are still pre-C2 (NO PROSE), or evidence packs are incomplete (fix C3/C4 first). **Network**: none. **Guardrail**: do not invent facts; only use citation keys present in `citations/ref.bib`; keep citations in-scope per `outline/evidence_bindings.jsonl`; do not add/remove citation keys during rewrites.

2026-05-30
chapter-skeleton
Rédacteurs techniques

Build a retrieval-informed chapter skeleton (`outline/chapter_skeleton.yml`) from taxonomy/core scope before stable H3 decomposition. **Trigger**: chapter skeleton, chapter-level outline, H2 skeleton, section-first survey, 章节骨架, 章级骨架. **Use when**: survey structure should stabilize chapter-level intent before subsection mapping and writing cards. **Skip if**: `outline/chapter_skeleton.yml` already exists and is refined. **Network**: none. **Guardrail**: NO PROSE; do not invent papers; keep output chapter-level only.

2026-05-27
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