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pi-prompting
Internal guidance for composing prompts that Pi runs (DeepSeek by default) handle reliably for coding, review, diagnosis, and research tasks
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。
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Internal guidance for composing prompts that Pi runs (DeepSeek by default) handle reliably for coding, review, diagnosis, and research tasks
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
| name | pi-prompting |
| description | Internal guidance for composing prompts that Pi runs (DeepSeek by default) handle reliably for coding, review, diagnosis, and research tasks |
| user-invocable | false |
Use this skill when pi:pi-rescue needs to ask Pi for help on a non-trivial coding or investigation task.
Pi runs whatever model the user has configured. By default this plugin targets DeepSeek V4 (Pro for review, Flash for everyday tasks). The guidance below assumes the prompt may run on either a non-reasoning model (Flash) or a reasoning model (Pro). Bias toward concrete, numbered checklists rather than abstract instructions — both model classes follow those reliably.
Core rules:
Default prompt recipe:
<task>: the concrete job and the relevant repository or failure context. Include file paths.<output_contract> (or <structured_output_contract> for JSON): exact shape, ordering, and brevity requirements.<grounding_rules>: required for review, research, or anything that could drift into unsupported claims.<action_safety>: required for write-capable tasks — name the directories and file kinds Pi may touch.When to add extra blocks:
<completeness_contract> listing what counts as "done" (tests pass, lint clean, files touched).prompts/adversarial-review.md and prompts/review.md. Do not hand-craft another review prompt.<sources> block listing what Pi is allowed to consult.How to choose prompt shape:
/pi:review or /pi:adversarial-review commands when the job is reviewing local git changes. Those prompts already carry the review contract.task when the job is diagnosis, planning, research, or implementation and you need to control the prompt more directly.task --resume-last for follow-up instructions on the same Pi session. Send only the delta instruction instead of restating the whole prompt unless the direction changed materially.Working rules:
--effort high) by default — DeepSeek Flash will not benefit, and DeepSeek Pro takes longer. Tighten the prompt before escalating effort.Prompt assembly checklist:
<task>.<grounding_rules> and <action_safety> only where the task needs them.Use when the user gives a topic and wants an automated topic-driven narrated explainer, podcast, or knowledge-summary video (Bilibili / YouTube / Xiaohongshu / Douyin / WeChat Channels), or asks to learn visual design patterns from a reference video/image. Trigger when the user mentions creating a knowledge video, narrated explainer, video podcast, or talking-head topic video from a topic — even if they don't say "video podcast" explicitly. Also trigger when the user wants to regenerate, re-render, rebuild, update, or iterate on a narrated video this skill already produced — e.g. they edited the script/prompt, changed the visuals, or swapped the background music and want the final video remade (reuse the existing videos/{name}/ directory, never start a new project). Do NOT trigger for generic video editing, trimming, format conversion, color grading, or non-narrative video tasks. Produces 4K video via research → script → TTS → Remotion → MP4 + BGM.
Multi-platform Chinese & multilingual TTS text-to-speech via Edge/Doubao/CosyVoice/Azure/Tencent/Baidu/MiniMax/Xunfei plus ElevenLabs/OpenAI/Google — 11 backends, word-level timestamps, [PAUSE:x] pause markers, pinyin pronunciation overrides
Use when looking up journal impact factors (JCR IF), checking a journal's impact factor by name, comparing IF across journals, or answering questions about "影响因子" / "impact factor" / "IF". Triggers on "impact factor", "journal IF", "影响因子", "JCR", "IF score", "journal rank", "which journal has higher IF", "what is the IF of". PROACTIVELY USE when user mentions journal prestige, publication venue quality, or manuscript submission target evaluation.
Use when looking up journal or magazine name abbreviations, converting between full names and ISO 4/MEDLINE abbreviations, processing BibTeX files for journal name standardization, or answering questions about 期刊缩写/杂志缩写. Triggers on "journal abbreviation", "abbreviate journal", "journal name", "期刊缩写", "杂志缩写", "ISO 4", "LTWA", "BibTeX journal". PROACTIVELY USE when user mentions citation formatting, reference list preparation, or manuscript submission to specific journals.
File new notes into the right folder and audit/reorganize folder structure in the user's Obsidian vault, using the `obsidian` CLI and a single source-of-truth map note (`00_Index/Folder_Map.md`) that lives inside the vault. Use this whenever a note needs to be placed, filed, sorted, or moved into the vault; whenever the user asks where a note "belongs" or "should go"; and whenever they want to clean up, reorganize, deduplicate, audit, or restructure vault folders (e.g. orphaned notes, dead-end notes, near-duplicate titles, overlapping folders). Trigger even when the user just says "add this to my vault", "put this somewhere sensible", or "tidy up the cellchat notes" without naming a folder. Requires the Obsidian desktop app to be running.
Use when designing, reviewing, or refactoring a CLI that must serve AI agents alongside humans, or when converting an API or SDK into an agent-usable CLI interface.