一键导入
data-prep
Internal Harness instruction source for data-prep. Route through visible Harness aliases or hook contracts instead of invoking directly.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Internal Harness instruction source for data-prep. Route through visible Harness aliases or hook contracts instead of invoking directly.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Internal Harness instruction source for auto-iterate-goal. Route through visible Harness aliases or hook contracts instead of invoking directly.
Internal Harness instruction source for auto-paper. Route through visible Harness aliases or hook contracts instead of invoking directly.
Internal Harness instruction source for evaluate. Route through visible Harness aliases or hook contracts instead of invoking directly.
Internal Harness instruction source for iterate. Route through visible Harness aliases or hook contracts instead of invoking directly.
Internal Harness instruction source for orchestrator. Route through visible Harness aliases or hook contracts instead of invoking directly.
Visible Harness write entry. Use for manuscript writing, citation-supported paper work, final documentation, README hardening, and GitHub Pages preparation.
| name | data-prep |
| description | Internal Harness instruction source for data-prep. Route through visible Harness aliases or hook contracts instead of invoking directly. |
Use this Skill for WF4 dataset analysis, subset design, and data-pipeline preparation.
../../../.agents/references/./references/dataset-stats.mdPROJECT_STATE.json, CLAUDE.md, AGENTS.md when presentdocs/Refined_Idea.mddocs/20_facts/Execution_Contract.md when presentdocs/30_evidence/Dataset_Table.md when presentdocs/90_legacy/<YYYY-MM-DD>/; record
archive_existing_data_docs_or_NOT_RUN.docs/Refined_Idea.md, execution contract, existing Dataset Table, and the
user request.docs/Dataset_Stats.md and concise
docs/30_evidence/Dataset_Table.md as Conclusion Evidence.PROJECT_STATE.json,
CLAUDE.md dataset paths, and stable AGENTS.md pointer when appropriate.Do not stop at “dataset missing” as the first response. First perform Remote Repository Selection, then ask for only the missing decision: download/mount choice and target directory, target archive/slice, network/disk approval, or existing local path.
If target path and approval are already unambiguous, proceed without another
question. Otherwise ask before large transfers or writing data outside the
repo. Record dataset_acquisition_decision_request_or_NOT_RUN.
Gate Evidence must include source URL, target path, command, result, observed
bytes/checksum when available, extraction path, and stats follow-up. With
multiple Grill/supervisor candidates, try the next executable candidate
after logging failures; skip rejected, deferred, or requires_approval
unless separately approved.
Inspect source-native listings before download: API, repository tree,
manifest, README, HTTP metadata, or file-list command. For Hugging Face, check
dataset API and relevant tree/main/... listings.
Build a small candidate matrix with remote path/archive, content role
(smoke, dehaze, clean reference, depth, COLMAP, point cloud, metadata),
resolution/layout, size/checksum when known, required/optional/excluded status,
and selection rationale. Do not silently fall back to full data or unrelated
conditions.
./references/dataset-stats.md.Dataset_Table.md source-artifact oriented; do not hand-edit
.evidence/**.CLAUDE.md is required WF4 output.AGENTS.md should point to CLAUDE.md, not duplicate volatile paths.dataset_acquisition_or_NOT_RUN.$docs-site or report
docs_site_boundary_report.After stable Markdown is finalized, invoke $docs-site or report
docs_site_boundary_report / docs_site_render_or_NOT_RUN. Do not render for
temporary drafts.