创作者 · LocalSymmetry
最近更新 · 2026年8月24日
lofn-daily
Run the Lofn daily pipeline backed by Codex — fetch real-world facts, then generate the day's music (24 songs) and images (24→top 6) through the full Lofn pipeline with the daily rules (tri-source method, dual 3+3 constraint, emotional duality, library-only selection). Use for "d
Do not auto-install
安装目标
Codex 安装提示词
Install the "lofn-daily" agent skill from https://github.com/LocalSymmetry/lofn/tree/main/.agents/skills/lofn-daily. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Run the Lofn daily pipeline backed by Codex — fetch real-world facts, then generate the day's music (24 songs) and images (24→top 6) through the full Lofn pipeline with the daily rules (tri-source method, dual 3+3 constraint, emotional duality, library-only selection). Use for "daily run", "today's dailies", "run the daily pipeline", "do the daily drop", or a scheduled creative drop. Down-scalable for a quick test. Do NOT use for a single one-off competition piece (use `lofn`) or QA-only audits. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"localsymmetry-lofn-daily","task":"Install lofn-daily","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.供给资产档案
编程与开发 Agent
代码审查、仓库分析、测试、CI、GitHub、DevOps 与开发工作流 Skill。
场景
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
适配 Agent
Claude Code + OpenAI Agents + CLI
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add LocalSymmetry/lofn --skill lofn-daily
维护状态
新鲜
今天有推送
风险
需审查
许可证不清晰
GitHub 质量
22
55/100 质量 · 57/100 信任
覆盖标签
审查说明
许可证不清晰 · Dependency or permission surface needs review
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
有潜力有用的候选项,但采用前应与替代方案比较。
信任
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
仅限沙盒
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
22 个 GitHub Stars
仓库活跃度
22 个 Star,1 个 Fork
维护状态
今天有推送
许可证
未知
安装
npx skills add LocalSymmetry/lofn --skill lofn-daily
安装安全性
标准软件包或运行时安装路径
权限范围
shell or command execution, filesystem or document access
Agent 结果
暂未有 Agent 结果数据
文档
Usable metadata, review docs
风险摘要
需要高强度审查
- Repository license is unknown; SKILL.md does not include license or attribution information.
- 许可证不清晰
- Low GitHub adoption signal
- Quality score needs review
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 许可证不清晰
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
View technical data+
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- 研究 Agent 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- 检索来源
适用 Agent
安装决策
- 命令
- npx skills add LocalSymmetry/lofn --skill lofn-daily
- 策略
- 审查
- 人工审查
- 是
信任与风险
- 信任
- 45/100
- 审计
- 68/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- Low GitHub adoption signal
- Repository license is unknown; SKILL.md does not include license or attribution information.
- 暂未有 OpenAgentSkill 使用反馈数据
Agent 安全 v2
36/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
Browser automation
Skill may drive a browser or interact with web pages.
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
- 高风险权限提示:Shell 或命令执行
- 许可证不清晰
Agent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20lofn-daily%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20lofn-daily%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/localsymmetry-lofn-daily/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use lofn-daily in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lofn-daily%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/localsymmetry-lofn-daily/install
Install command: npx skills add LocalSymmetry/lofn --skill lofn-daily
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/localsymmetry-lofn-daily/install
LLM 文本格式
/api/skills/localsymmetry-lofn-daily/install?format=text
寻找替代方案
/api/skills/search?q=lofn-daily&limit=3
Agent 提示词
Use lofn-daily for this task. Review https://www.openagentskill.com/api/skills/localsymmetry-lofn-daily/install, then install with: npx skills add LocalSymmetry/lofn --skill lofn-dailyRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Agent 决策面板
Needs validation for Research agents
在将它加入 Agent 工作流前先人工审查仓库。
栈中角色
需要验证
主要匹配
研究 Agent
信任标签
需要人工审查
安装路径
命令已就绪
适用场景
- 研究 Agent 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 55/100 质量档案
先审查
- Low GitHub adoption signal
- Repository license is unknown; SKILL.md does not include license or attribution information.
- 暂未有 OpenAgentSkill 使用反馈数据
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次研究 Agent任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub 采用度
修复22 个 GitHub Stars
Star/Fork 活跃度
修复22 个 Star,1 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过今天有推送
许可证清晰度
检查未知
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- Repository license is unknown; SKILL.md does not include license or attribution information.
- 许可证不清晰
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 22 GitHub stars
- Stars/forks activity: 22 stars, 1 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Dependency/runtime risk: command execution surface, external package install surface
- Permission surface: shell or command execution, filesystem or document access
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
Choose a stronger alternative or inspect the source manually before any install attempt.
质量档案
有潜力 适用于 Agent 工作流的候选
有用的候选项,但采用前应与替代方案比较。
工作流匹配
在这些场景使用此 Skill
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
工作流匹配
加入完整工作流
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Scrape, clean, and reuse web data
Web data pipeline
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
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概览
--- name: lofn-daily description: Run the Lofn daily pipeline backed by Codex — fetch real-world facts, then generate the day's music (24 songs) and images (24→top 6) through the full Lofn pipeline with the daily rules (tri-source method, dual 3+3 constraint, emotional duality, library-only selection). Use for "daily run", "today's dailies", "run the daily pipeline", "do the daily drop", or a scheduled creative drop. Down-scalable for a quick test. Do NOT use for a single one-off competition piece (use `lofn`) or QA-only audits. ---
# Lofn Daily — Codex-backed daily run
The canonical recurring Lofn drop, ported to Codex. Faithful to `vault/DAILY_PIPELINE.md`. Where the original fired from an OpenClaw cron at 22:25 ET and delivered to Telegram, **you (Codex) run it on demand and present results in chat + save to disk.** The research is done by **this session itself with real fetches — never hallucinated, never delegated to a research subagent.**
``` PHASE 1 Research — fetch 20–25 verified real-world facts → 00_research_brief.md (you, inline) PHASE 2 Generate (in parallel): MUSIC → lofn pipeline → 6 pairs × 4 = 24 songs → best 6 IMAGE → lofn pipeline → 24 prompts → top 12 → top 6 PHASE 3 QA (lofn-qa) → save under output/daily/YYYY-MM-DD/ → present the drop ```
---
## 0. Run scope (confirm before a big run) The full daily run is **two complete pipelines** (24 songs + 24 images) — large. Pick a scope: - **Full daily** — music (24→6) **and** image (24→12→6). The real thing. - **Single modality** — just music **or** just image (still full cardinality). - **Test slice** — 1 modality, **2 pairs × 2 variations**, library personality/panel, skip render-ranking. Proves the wiring fast and cheap. *(Good default when the user says "test the daily run".)*
State the chosen scope in the brief and in the run INDEX so QA knows the intended cardinality. Down-scaling is explicit, not silent.
---
## PHASE 1 — Research brief (you, inline, real fetches) Use **WebFetch / WebSearch** (the Codex equivalents of the legacy `web_fetch`). Follow `skills/lofn-core/steps/00_music_research.md` (25-fact music research) and, when the image lane is in scope, the NightCafe-themed research in `skills/lofn-core/steps/00_research.md`. Fetch from the daily source table (`vault/DAILY_PIPELINE.md`) — at minimum:
**OpenClaw ledger standard:** this is a dispatch summary, not the saved brief format. `00_research_brief.md` MUST expand the full `vault/DAILY_PIPELINE.md` ledger into one row each for `F01` through `F25`. Do not collapse ranges such as `F1-F3` or `F21-F25`; use `OK`, `NO DATA`, `UNAVAILABLE`, or `SCOPE-SKIPPED` per row.
| Code | Source | Extract | |------|--------|---------| | F1–F3 | NightCafe daily challenge (`nightcafe.studio/pages/daily-challenge`) | challenge #, theme, what wins (image lane) | | F4–F5 | USGS quakes (`earthquake.usgs.gov/.../significant_day.geojson`) | magnitude, place, depth | | F6–F7 | NASA APOD (`api.nasa.gov/planetary/apod?api_key=DEMO_KEY`) | title, first sentence, color/light, **image structure** | | F8 | Poetry Foundation poem of the day | poet, most physical line | | F9–F10 | Bandcamp Daily (`daily.bandcamp.com`) | album, genre tags, **exact sonic-texture quote** | | F11 | Protein Data Bank molecule of the month | molecule, structural descriptor | | F13 | Color API (`thecolorapi.com/id?hex=MMDD`) | hex, name, emotional association | | F17 | Oblique Strategies (`stoney.sb.org/eno/oblique.html`) | exact phrase verbatim | | F18 | Space weather (`services.swpc.noaa.gov/products/summary/solar-wind-speed.json`) | solar wind speed, Kp | | F19 | Hacker News (`news.ycombinator.com`) | top 3 titles — what builders discuss | | F20 | BBC World RSS (`feeds.bbci.co.uk/news/world/rss.xml`) | top 3 headlines — world's emotional temperature | | F21–F25 | Public Domain Review, Almanac moon, NOAA buoy 46059 | esoteric visual detail, moon folklore, wave data |
Mark any JS-gated/unavailable source `UNAVAILABLE` and continue. Add 3–5 obscure theme-specific facts (not the obvious Wikipedia entry). Also write the 5 **EXISTENCE** prompts (interior-life questions songs can answer) from `00_music_research.md`.
**Save** `output/daily/YYYY-MM-DD/00_research_brief.md` with the Tri-Source Summary + the 3+3 seeded split (see below). Today's date is available in context — use it for the directory.
> ⛔ **One controller per directory — take the lock BEFORE the research brief.** This paragraph used to be advice, and on 2026-07-24 a second controller wrote into a live run's directory and destroyed eleven hours of it. Advice does not interlock. The first action of the run, before this step writes anything: > > ```bash > python3 scripts/run_lock.py acquire output/daily/YYYY-MM-DD --run-slug <run-slug> --engine codex > ``` > > **Exit 3 means STOP** — another run holds that directory. Do not inspect it and decide for yourself; give this run its own directory (`output/daily/YYYY-MM-DD-<run-slug>/`), or resume the other run by its exact slug, or ask The Scientist. See `EXECUTION.md` §5.1. Then `heartbeat` at every wave and `release` after the INDEX. If the lock says the same run is already under way, **resume** it from the RUN_STATE manifest (§ "Run-state manifest & resume") rather than re-running passed pairs.
### Advisory learnings note (dispatch brief only — NEVER the ICB) Before dispatching either modality, **tag-walk `vault/COMPETITION_LEARNINGS.md`** (and `vault/LESSONS_INDEX.md` if it exists) for the **3–5 entries that intersect THIS run's theme/venue/modality** — e.g. a container/object theme pulls the Container Test, a NightCafe image lane pulls the warm-palette/anti-austerity lessons, a portrait theme pulls the portrait shifts. Surface them **as ADVISORY NOTES in the dispatch brief / Phase-0 reasoning ONLY.** Hard rules: - **NEVER injected into the ICB / `CREATIVE_CONTEXT.md`.** The ICB stays read-only and lesson-free. These notes live in the brief the coordinator reasons over, not in the verbatim block every subagent receives. - Each note carries its **confidence %** (from the entry) and is run through the mandatory **"would this have hurt our best past entry?"** gate before it is allowed to influence anything. A lesson that would have hurt a past win is dropped, not applied. - **Venue/modality-scoped:** an image-venue lesson must NOT leak into the music lane; a NightCafe-voting lesson must NOT leak into non-competition runs. - **Advisory, never a hard constraint.** A note can inform the pair brief's framing; it can never auto-reject a candidate or become a gate. Promotion to a hard constraint is a **human** decision. - **Triggered-INDIGNATION is EXEMPT from suppression.** A lesson such as "INDIGNATION underperforms on NightCafe" may inform image-venue *selection* advice, but it must NEVER suppress an INDIGNATION piece the panel deliberately chose, and never touches the music lane or the ≥1-INDIGNATION duality rule.
State in the brief: "Advisory learnings consulted: <N entries, tags>; INDIGNATION exempt; advisory-only." If zero entries intersect, say so. Write-back of one curated entry per shipped/selected piece happens in `lofn-qa` / Phase 3 — not here.
---
## PHASE 2 — Generate (daily rules layered on the `lofn` pipeline) For each in-scope modality, run the **`lofn`** pipeline (Phase 0 Golden Seed → Phase 1 3-panel orchestrator → modality steps → QA) using the research brief as `{input}`, **plus these daily-only rules:**
### Tri-Source Methodology (declare BEFORE writing any artifact) Every daily piece integrates three sources; state them explicitly in the metaprompt and each pair brief: - **Source 1 — CONTENT / emotional stakes:** today's world facts (quakes, APOD, F19 HN, F20 BBC, moon, solar weather). Songs/images are *resonance*, not reportage. **⛔ One-fact rule (music):** the tri-source method feeds the THEME and FORM — it is not a lyric quota. **At most ONE numeric fact is sung per song**, at the emotional hinge, responded to rather than recited (`lofn-music` Golden Move rule 2; `gates.yaml → max_sung_numeric_facts`). A verse reciting the day's sunspot number, solar-wind speed, moon percentage, AND quake depth is a weather report in meter — a repair. The other facts inform the pair briefs and stay there. - **Source 2 — SONIC/AESTHETIC VOCABULARY:** the exact Bandcamp review language (F9–F10) imported into prompts — grounds the sound/look in something specific and real, not generic genre labels. - **Source 3 — MATERIAL STRUCTURE:** the NASA APOD image structure (or a PDR artifact) translated into a **mandatory form rule** — e.g. "comet with long tail" → long trailing fade-out outro; "3×1 tile panel with meanders" → 3-section form with transitional bridges; "bilateral wing venation" → mirrored call-and-response.
### Dual 3+3 Constraint (set at pair-assignment time, Phase 1 step 5) - **Axis A — ACCESSIBLE vs AMBITIOUS:** pairs 1–3 ACCESSIBLE, pairs 4–6 AMBITIOUS. Final top 6 = best 3 from each arm; rank **within each arm only** (never 5+1 or 6+0 by global score). - **Axis B — NEWS vs EXISTENCE:** **max 3** pairs anchored to today's research/news; **min 3** pairs explore existence/interior-life/universal experience. All 6 on one theme = a lecture, not a record.
### Emotional Duality & diversity - **≥1 AWE song and ≥1 INDIGNATION song** in the set. - 6 different verse architectures / camera grammars across the 6 pairs (the standing distinctiveness rule). Vary stanza lengths intentionally. - **Variation angles are per-pair, never a shared template set.** A global "V4 = glitch chapel for everyone" scheme is how the 2026-06-26 daily produced two pairs singing the same song with nouns swapped; each pair derives its own 4 angles from its own concept (`EXECUTION.md` §3 item 3). - **Daily music pair isolation is mandatory.** Steps 05–11 must run as isolated pair runs; a central all-pairs helper may not author lyrics, section maps, stanza scaffolds, hook grammar, rhyme logic, or production arcs for multiple pairs. Shared validators and file writers are OK. If the pairs sound like the same song with nouns swapped, rerun each affected pair from Step 05. - **AWE stays terror-adjacent.** The daily's comfort gravity is real (kitchens, cups, reassurance) — every AWE song still answers the two pre-draft questions (*where is the body standing / what could hurt it here*) and carries a clean fear (`lofn-music` Golden Move rules 1 & 4).
### Library-only selection For daily runs, **always select personality + panel from the existing libraries** (`personalities_index.md` / `panels_index.md`) — **no generation.** Freshly generated personalities over-fit the day's theme and lose the battle-tested DNA. (Generation is reserved for competition/Scientist-special runs.)
### Modality specifics - **MUSIC** (`lofn-music`): 24 songs (6×4); each ≤1000-char two-field Suno prompt, female vocals default, EMO headers, 70–120 lines; `06_audio_handoff.md` carries 2 Golden Songs. Run music in parallel with image. - **IMAGE** (`lofn-image`): 24 prompts → rank → **top 12 → top 6**; figurative legible primary subject (thumbnail test); noun-first present-tense ≥80 words; warm palette leads on NightCafe-style venues (INDIGNATION underperforms there — see `vault/COMPETITION_WORKFLOW.md`); aspect 3:4 for upload challenges else 9:16. Apply the **Container Test** (`COMPETITION_WORKFLOW.md`) and **Action-Verb rule** (action theme → cinematic wide, not portrait).
Run the two modalities concurrently (independent `lofn` runs writing to `music/` and `images/` subdirs). Each fans its 6 pairs out as parallel subagents per `.agents/skills/lofn/EXECUTION.md`.
> ### ⚙️ Concurrency: cap-and-stagger (do NOT run all 12 chains at once) > The full daily is **two pipelines × 6 pairs = 12 concurrent chains** — enough to blow the tool/context budget if fired together. **Cap and stagger, don't serialize:** > - **Cap the in-flight pair-subagents** (default ~6 at a time, not all 12). Launch one modality's 6-pair wave, t
技术详情
- 版本
- 1.0.0
- 许可证
- Unknown
- 最近更新
- 2026年8月24日
- 发布时间
- 2026年8月24日
决策摘要
需要验证
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 lofn-daily 准备的场景化草稿,可手动发布到 X。
lofn-daily: Run the Lofn daily pipeline backed by Codex — fetch real-world facts, then generate the day's... 22 stars https://www.openagentskill.com/skills/localsymmetry-lofn-daily?ref=x
可选:带安装命令的回复
Listing + install path for lofn-daily: https://www.openagentskill.com/skills/localsymmetry-lofn-daily?ref=x Install: npx skills add LocalSymmetry/lofn --skill lofn-daily
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归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 LocalSymmetry,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/localsymmetry-lofn-daily)
[](https://www.openagentskill.com/skills/localsymmetry-lofn-daily)
[](https://www.openagentskill.com/skills/localsymmetry-lofn-daily/audit)
[](https://www.openagentskill.com/skills/localsymmetry-lofn-daily)作者
LocalSymmetry
@localsymmetry
健康信号
- GitHub Stars
- 22
- 质量评分
- 32/100
- 最近 GitHub 推送
- 2026年8月24日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 0
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
Do not auto-install
- GitHub 采用度22 个 GitHub Stars修复
- Star/Fork 活跃度22 个 Star,1 个 Fork; 当前元数据中没有议题活跃度信息修复
- 近期维护今天有推送通过
- 许可证清晰度未知检查
- README/SKILL.md 完整度公开元数据需要更完整的 README/SKILL.md 上下文信息
- 依赖与运行时风险command execution surface, external package install surface检查
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