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WILLOSCAR
Profil créateur GitHub

WILLOSCAR

Vue par dépôt de 116 skills collectés dans 2 dépôts GitHub.

skills collectés
116
dépôts
2
mis à jour
2026-07-10
explorateur de dépôts

Dépôts et skills représentatifs

appendix-table-writer
Enseignants postsecondaires, autres

Curate reader-facing survey tables for the Appendix (clean layout + high information density), using only in-scope evidence and existing citation keys. **Trigger**: appendix tables, publishable tables, survey tables, reader tables, 附录表格, 可发表表格, 综述表格. **Use when**: you have C4 artifacts (evidence packs + anchor sheet + citations) and want tables that look like a real survey (not internal logs). **Skip if**: `outline/tables_appendix.md` already exists and is refined (>=2 tables; citation-backed; no placeholders; not index-y). **Network**: none. **Guardrail**: no invented facts; no pipeline jargon; no paragraph cells; use only keys present in `citations/ref.bib`.

2026-07-01
citation-injector
Enseignants postsecondaires, autres

Apply a `citation-diversifier` budget report by injecting *in-scope* citations into an existing draft (NO NEW FACTS), so the run passes the global unique-citation gate without citation dumps. **Trigger**: citation injector, apply citation budget, inject citations, add citations safely, 引用注入, 按预算加引用, 引用增密. **Use when**: `output/CITATION_BUDGET_REPORT.md` exists and you need to raise *global* unique citations (or reduce over-reuse) before `draft-polisher` / `pipeline-auditor`. **Skip if**: you need more papers/citations upstream (fix C1/C2 mapping first), or `citations/ref.bib` is missing. **Network**: none. **Guardrail**: NO NEW FACTS; do not invent citations; only inject keys present in `citations/ref.bib`; keep injected citations within each H3’s allowed scope (via the budget report); avoid citation-dump paragraphs (embed cites per work).

2026-07-01
agent-survey-corpus
Enseignants postsecondaires, autres

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
Enseignants postsecondaires, autres

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
Enseignants postsecondaires, 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 logiciels

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
Affichage des 8 principaux skills collectés sur 109 dans ce dépôt.
bundle-algorithm-context
Développeurs de logiciels

Build a compact, immutable GPT Pro evidence bundle from repository code, configs, docs, logs, Codex notes, and recent bridge events. Use before algorithm review, paper brainstorm, experiment analysis, implementation consistency review, or any GPT Pro round that needs local evidence.

2026-07-10
gpt-pro-algorithm-pipeline
Développeurs de logiciels

Run the end-to-end Codex to GPT Pro to Codex loop for algorithm, research, experiment, or implementation-consistency work. Use when the user wants scoped evidence bundling, deep external review, local verification, experiments, and safe implementation connected through one reproducible task thread.

2026-07-10
gpt-pro-question-window
Développeurs de logiciels

Bridge Codex to a signed-in ChatGPT/GPT Pro conversation, including scoped file upload, conversation reuse, raw answer capture, and later Codex verification. Use for normal GPT Pro questions and as the browser/persistence foundation for other Codex Pro Bridge skills; do not use for local tasks that need no external reasoning.

2026-07-10
experiment-plan-generator
Développeurs de logiciels

Convert an algorithm review or research idea into a prioritized experiment matrix with baselines, ablations, metrics, success/failure criteria, commands, logging requirements, and decision rules. Use after GPT Pro review or before implementing experiments.

2026-07-10
gpt-pro-paper-brainstormer
Enseignants postsecondaires, autres

Use GPT Pro for research-paper brainstorming, claim sharpening, novelty analysis, related-work positioning, reviewer objections, and experiment story design. Best for algorithm/research ideas where Codex alone is too implementation-biased.

2026-07-10
gpt-pro-research-algorithm-reviewer
Développeurs de logiciels

Deep GPT Pro algorithm/research/pipeline review. Use for RL, reward modeling, OPD, agentic workflows, search/QA, training/eval pipelines, or algorithm proposals where Codex needs stronger hypothesis, experiment, ablation, data leakage, novelty, and go/no-go analysis.

2026-07-10
implementation-consistency-checker
Développeurs de logiciels

Verify that an algorithm proposal, GPT Pro review, code implementation, configs, data splits, eval scripts, logs, and experiment commands are mutually consistent. Use before trusting results or after Codex implements an algorithm/pipeline change.

2026-07-10
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