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Internal Harness instruction source for auto-paper-layout. Route through visible Harness aliases instead of invoking directly.

日本語の概要は準備中です。原文の説明を表示しています。

Internal Harness instruction source for auto-paper-patch. Route through visible Harness aliases instead of invoking directly.

日本語の概要は準備中です。原文の説明を表示しています。

Internal Harness instruction source for auto-paper-citation. Route through visible Harness aliases instead of invoking directly.

日本語の概要は準備中です。原文の説明を表示しています。

Acquire and verify finite environment, data, weight, and baseline inputs.

日本語の概要は準備中です。原文の説明を表示しています。

Internal Harness instruction source for auto-paper-intake. Route through visible Harness aliases instead of invoking directly.

日本語の概要は準備中です。原文の説明を表示しています。

Internal Harness instruction source for auto-paper. Route through visible Harness aliases instead of invoking directly.

日本語の概要は準備中です。原文の説明を表示しています。

Create marketing assets and execute launch strategy. Use when crafting landing copy, social banners, SEO meta, blog posts, or video scripts — coordinates with launch (deploy + announce) and the @rune-pro/growth pack (research / content / CRO).

日本語の概要は準備中です。原文の説明を表示しています。

Developer reference for building applications, tools, and agents on the Pi Durable agent harness (@earendil-works/pi-durable) and the pi-ai model layer. Use when writing or debugging code that imports @earendil-works/pi-durable or pi-ai: assembling a Harness over memory/SQLite/JSONL/Durable Object storage, submitting input and waiting for answers, defining tools with TypeBox schemas and structured output, calling tools from tools, hooks and guards, durable tasks with checkpoints and ownership, subagents and child tasks, documents and migrations, code mode, tool search, per-conversation environments, compaction, recovery after a crash, storage and environment conformance tests, or choosing models and providers. Also use when a durable/agent-runtime behavior question comes up: what survives a restart, why an input stayed queued, why a task is blocked or orphaned, how abort cascades, or what the Pico5 specification requires.

日本語の概要は準備中です。原文の説明を表示しています。

Fetch and export public X (Twitter) data with a self-contained Python CLI (twikit; no API keys, uses the user's own login cookies): profiles, a user's tweets/replies/likes, threads, search, followers, timelines, JSON/JSONL/CSV/SQLite output, resumable pagination. Use to scrape, archive, monitor, or analyze tweets or accounts.

日本語の概要は準備中です。原文の説明を表示しています。

Developing with Zotero: Web API v3 (read/write, file upload, sync, OAuth, item types/fields), the desktop client's JS API, plugin development (7-10), translators (web/import/export/search), and CSL/citeproc-js styles. Use when scripting Zotero or building or debugging a plugin, translator, or citation style.

日本語の概要は準備中です。原文の説明を表示しています。

Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE pipeline.

日本語の概要は準備中です。原文の説明を表示しています。

Use when interpreting research findings, evaluating scientific evidence, analyzing mechanisms, comparing competing hypotheses, designing experiments, or constructing scientific arguments.

日本語の概要は準備中です。原文の説明を表示しています。

Use when interpreting biological research findings, evaluating life science evidence, analyzing molecular or cellular mechanisms, comparing competing biological hypotheses, designing or critiquing experiments in biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, or any life science domain. Triggers on questions about gene function, pathways, phenotypes, GWAS hits, single-cell data, animal models, clinical translation, evolutionary arguments, or any biology/life science reasoning task.

日本語の概要は準備中です。原文の説明を表示しています。

Internal guidance for composing prompts that Pi runs (DeepSeek by default) handle reliably for coding, review, diagnosis, and research tasks

日本語の概要は準備中です。原文の説明を表示しています。

Use when evaluating grant ideas, diagnosing proposal logic, framing fundable projects, strengthening reviewer-aware arguments, or preparing to write any section of a research proposal.

日本語の概要は準備中です。原文の説明を表示しています。

Use whenever the user wants to interact with Figshare - searching public datasets/articles, downloading Figshare files, listing their own articles/collections/projects, creating or updating articles, or uploading files (including large multi-part uploads) via the Figshare v2 REST API. Trigger on mentions of "figshare", figshare DOIs (10.6084/m9.figshare.*), figshare.com URLs, or phrases like "upload my dataset to figshare", "publish to figshare", "get figshare article".

日本語の概要は準備中です。原文の説明を表示しています。

Query the Semantic Scholar academic corpus through AI2's Asta MCP server: keyword or title search with venue and date filters, who-cited-a-paper traversal, author profiles and publications, DOI/arXiv/PMID lookup, and ~500-word full-text snippets for evidence, with citation counts and h-index. Use when the user asks for papers on a topic, who cited a paper, an author's work, recent literature since a date, or a venue-scoped paper list. Requires the Asta MCP server.

日本語の概要は準備中です。原文の説明を表示しています。

Build, critique, and refine academic posters from a paper, LaTeX project, reference draft image, HTML/CSS source, PPT/PDF outputs, or local figure assets. Use when Codex is asked to create or improve a research poster, convert a poster design to HTML/PDF/PPTX, fix poster layout/typography/overflow/blank-space issues, or preserve paper figures and result semantics in a poster.

日本語の概要は準備中です。原文の説明を表示しています。

Create GEDCOM 5.5.1 compliant genealogy files from natural language, JSON, or markdown table input. Use when the user wants to generate a family tree interchange file from research data.

日本語の概要は準備中です。原文の説明を表示しています。

竞品深度扫描与早期付费客户证据研究；输出行业画像假设和可验收需求交接。批量抓取对手落地页（title/h1/intro/pricing）、定价页、博客 top 10、 变更历史（Wayback）。底层调 actionbook（并发 30 tab + 省 90% token）。 当用户说"分析对手"、"看看竞品在做啥"、"找对标"、"扫一下 top 10"时调用。

日本語の概要は準備中です。原文の説明を表示しています。

Reconstruct an open-source project's growth channels, key content, and stage-by-stage attribution from GitHub history and public web evidence. Use this skill when asked to research GitHub star growth, identify launch and amplification channels, explain viral milestones, find representative posts or videos, compare Product Hunt/Show HN/Reddit/KOL impact, or produce an evidence-backed OSS growth attribution report.

日本語の概要は準備中です。原文の説明を表示しています。

Design and execute a 14-day GitHub repository growth sprint using README conversion, competitor-window research, Reddit, Hacker News, launch directories, community activation, and contributor loops. Use when launching an open-source repository, diagnosing weak star conversion, or building sustained GitHub discovery without buying stars.

日本語の概要は準備中です。原文の説明を表示しています。

Systematic backlink building for indie founders. Covers 5 channel types ranked by GEO + SEO ROI: Wikipedia (entities), authoritative media (PR), industry reviews (G2/Capterra/Product Hunt), Reddit/Quora discussions, and HARO/Featured.com expert quotes. Designed for 0→1 sites where domain authority is the bottleneck. Aligns with 2026 Google/Bing GEO guidance: backlinks are the strongest brand-authority signal AI search engines use to decide citations. Defaults to dev/B2B link sources; for 2C products (education, consumer apps) authority links differ — see gingiris-seo-geo/references/2c-adaptation.md.

日本語の概要は準備中です。原文の説明を表示しています。

React Router v7 best practices for data-driven routing. Use when implementing routes, loaders, actions, Form components, fetchers, navigation guards, protected routes, or URL search params. Triggers on createBrowserRouter, RouterProvider, useLoaderData, useActionData, useFetcher, NavLink, Outlet.

日本語の概要は準備中です。原文の説明を表示しています。