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preview-verdicts

Generate the interactive keep/drop verdict preview (HTML page with per-row feedback controls) whenever a prune sweep, batch entry edit, or restructure needs maintainer review before touching README.md — and process the feedback JSON the maintainer pastes back.

DeepseekModel Curated skill ★ Featured Quality Excellent · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=vinta-awesome-python-claude-skills-preview-verdicts-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name preview-verdicts description Generate the interactive keep/drop verdict preview (HTML page with per-row feedback controls) whenever a prune sweep, batch entry edit, or restructure needs maintainer review before touching README.md — and process the feedback JSON the maintainer pastes back. Verdict preview Maintainer review happens through an interactive HTML page: one row per entry with your seeded verdict and reason, a Keep/Drop toggle and a reason field for the maintainer, and a Copy feedback button that exports only changed or commented rows as JSON. Generate the page, wait for the pasted JSON, then apply it. Entry changes land in README.md only after the review — and only on an explicit go. Generate the preview Build the DATA array. A group is [section, subcategory, rows] ; a row is [entry, url, downloads, verdict, reason] . subcategory may carry a note after — (rendered muted): use it for proposed splits, re-homes, or anything the maintainer should weigh for the whole group. downloads is PyPI last-month as a comma-formatted string; use — when no signal exists (e.g. agent skill packs), stdlib for standard-library modules, fetch failed when the lookup failed. State the fetch date in the sub-header. verdict is keep or drop , seeded from the current adjudication or dry-run. reason is plain language the maintainer reads cold — no invented shorthand. When fresh evidence contradicts the seeded verdict (a big download count on a drop, a dead repo on a keep), say so in that row's reason instead of silently changing the seed. Copy template.html (sibling of this file) and replace the placeholders: __TITLE__ (page title), __SUB__ (sub-header: scope, seed provenance, fetch date, and the standing instruction to flip/comment then Copy feedback), __KEY__ (localStorage key), __DATA__ (the array). __KEY__ must be unique per review — slug plus date, e.g. awesome-python-science-2026-09-01 — because saved state under a reused key bleeds a previous review's flips into rows with the same section and entry name. Write the page to tmp/awesome-python-<slug>-preview.html in the repo root (git-ignored; create the directory if needed), open it, and tell the maintainer the path and the return path: flip or comment rows (they highlight yellow), press Copy feedback , paste the JSON into the chat. Done when the page is open and the return path is stated. Process the pasted feedback Each JSON row is {section, subcategory, entry, my_verdict, your_verdict, reason} . The maintainer's verdict is final — apply it, never re-argue it. An empty reason means the verdict stands unexplained; that is enough. Before executing, surface anything the flips imply that the maintainer has not decided: a use case pushed past its cap, an entry left homeless by a proposed split, a request that is already satisfied (a no-op). Ask, then execute on their go. Done when every pasted row is either applied or surfaced back — none silently dropped.
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The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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