drpy-node-source-workflow

A retired workflow guide for repairing, testing, and evaluating drpy-node video sources. A source is the set of rules that finds and plays content from a website.

In plain words
What is it for?
Use it only as historical guidance for diagnosing source failures, planning repairs, checking results, and deciding whether a source is ready for upload.
Why use it?
It explains how to distinguish broken searches, details, or playback and how to choose the right follow-up workflow, but it has been replaced by drpy-node-coder.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/hjdhnx/drpy-node-skill/drpy-node-source-workflow
Any agent
npx skills add hjdhnx/drpy-node-skill --skill drpy-node-source-workflow
Clone the repo
git clone --depth 1 https://github.com/hjdhnx/drpy-node-skill

Made for: Claude Code, Codex.

Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,493 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00117 $0.06493
Opus 5 $0.00059 $0.03247
Sonnet 5 $0.00023 $0.01299
Haiku 4.5 $0.00012 $0.00649

Measured 2d ago against content hash d2ea5959a5b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

drpy-node-source-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

drpy-node-source-workflow/SKILL.md · 491 lines

How it starts

The opening of the file, as written. The whole thing — 491 lines — stays where its author put it; the contents beside it link to each section on GitHub.

⚠️ 已归档(2026-07-17):本 skill 已被 drpy-node-coder 取代。coder 融合了 4 个旧 skill(workflow/create/play-debug/repo-upload)的全部工作流,并自带 scripts/cli.js CLI 替代 drpy-node-mcp 服务——一个 skill、无需安装 MCP。本文件保留仅供历史参考,新工作请直接用 drpy-node-coder。

drpy-node Source Workflow

快速索引

输入/问题 诊断目标 分流
已有源评估低分 判断 A 规则不通 / B 串联断 / C 播放链 本 skill 修复或转 play-debug
只有网址 判断新建还是修复 转 source-create
URL + 自动做源/修到100/上传 alive check → 建源 → evaluate → 修复 → 上传 本 skill 总控编排
detail 正常但 play 异常 播放链专项 转 play-debug
用户要求上传/替换/改标签 发布守门 转 repo-upload

执行契约

  • 输入:源名/源文件/URL/评估结果/用户目标。
  • 输出:证据链分级诊断、分流路线、修复后验证结果、上传建议。
  • 原则:先评估 → 再分流 → 再修复 → 再验证 → 最后给上传建议/结束。

模式闸门:先判断是否允许写入

用户模式 允许动作 禁止动作
只读 / 规划 / dry-run / 不要改文件 / 不要上传 读取、诊断、拆证据链、给修复计划和验证命令 drpy_edit_filedrpy_write_file、仓库上传/替换/改标签
需要确认后再改 读取、诊断、输出拟改字段和验证计划 未确认前禁止改源或仓库元数据
明确要求执行 按 L1/L2/L3 证据链最小修复 不跳过大改确认点,不直接做仓库 mutation
自主全流程 alive check、分流建源、低风险修复、播放专项、L3=100 后转上传 坏站硬写、未达目标冒充完成、仓库目标不明时上传

如果用户说“只诊断 / 不要改 / dry-run”,本 skill 输出证据链、根因判断、拟改字段和验证计划后停止。

Reference Map

任务 首读 reference
总控分流 / 评估失败 triage references/references-workflow-triage.md
模板摘要与 * 继承 references/references-template-summary.md
引擎调度 / evaluate 串联机制 references/references-framework-internals.md
搜索异常 references/references-search-strategies.md
async / API / detail 字典细节 ../drpy-node-source-create/references/...

调度优先级

当本地环境已安装本 Skill 时:

  • 本地 Skill 优先级 高于 drpy-node MCP 的通用 prompts
  • 当用户只给网址、不给文件名时,总控层应主动分析站点并推导源名

强约束

如果本地 Skill 已覆盖场景,不允许让 MCP 通用 prompt 抢占主流程。

自主全流程模式

当用户明确说“自动完成”“修到100”“满分后上传”“不要中途问我”“给网址做源并上传”时,本 skill 作为总控编排器,使用 packet 贯穿子 skill:

URL → alive check → source-create → L1/L2/L3 → 按丢分最小修复 → play-debug → L3=100 → repo-upload → info核验

执行规则:

  1. 先识别 autonomous=truetarget_score=100upload_preauthorized=true/falsetagsis_public
  2. 先做 alive check;broken_sitehard_anti_botmissing_credentials 直接停止,不建源、不上传。
  3. 站点可用时转 source-create 建源;source-create 返回源路径、站型、五接口结果和 L3 分数。
  4. L3 未满 100 时按丢分接口拆 L2:home/category/detail/search 在 workflow/source-create 修;play 带真实 ids/play_url/flagplay-debug
  5. 回收 play-debugautonomous_nextcontinue_evaluate 继续 L3;stop_for_user 停止并报告 blocker。
  6. L3=100 且上传已预授权时,带本地路径、A/B/C、L1/L2/L3、tags/is_public 转 repo-upload
  7. 自主模式下普通检查点只记录证据不中断;遇到 high_risk_change、仓库目标歧义、凭据缺失时必须停手确认。

Read the full file on GitHub · 491 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 491 lines · 117 tokens per session scan A d2ea5959a5b7

Subscribe to this mod's changes

drpy-node-source-workflow is a skill published in the GitHub repository hjdhnx/drpy-node-skill (48 stars, last pushed 1mo ago), licensed MIT. It adds 117 tokens to every session and 6,493 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

microsoft/vscode · 56 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens