3,377 件 ・ 関連度順
概要と使いどころ
Cowork-style cleanup of a messy folder or shared drive -- classifies every file, proposes a target structure, renames to a consistent convention, deduplicates, and writes an index. Use on Downloads, Desktop, client folders, or team shared drives.
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。
Merges, appends, joins, and deduplicates multiple CSV, TSV, and Excel files (including multi-sheet workbooks) with pandas - mapping mismatched column names to one schema, normalizing keys, resolving conflicting values, tracking which file each row came from, and verifying the row math. Use when the user wants to combine spreadsheets or exports, stack monthly files, consolidate contact or lead lists, VLOOKUP-style join two sheets on an ID or email, or dedupe records across sources, even if they only say "put these together" or "clean up these lists into one".
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。
Runs small and midsize business bookkeeping operations - categorizes bank and card transactions to a chart of accounts, reconciles a bank or card statement against the ledger, works a month-end close checklist, and produces a close package for the accountant. Works from QuickBooks Online, Xero, bank CSV/OFX, or Mercury exports, and from the Xero, QuickBooks, or Mercury connectors when present. Use it whenever the user says "reconcile", "bank rec", "categorize transactions", "month end close", "close the books", "books don't match the bank", "reconciliation is off by", "uncategorized expenses", or shares a QuickBooks or Xero export or a bank statement CSV, even if they do not name the task. Never plugs a difference; every unreconciled dollar is explained or listed.
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。
March Madness, playoff brackets, tournament picks. Upset potential, chalk vs contrarian strategies, historical trends, confidence levels.
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。
Search and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from multiple sources and provides enriched contact details. Use when users need to find contact information, build prospect lists, or enrich existing contact 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。
Generates full consulting proposals from a brief. Input client name, problem description, and rough scope. Outputs proposal.md with executive summary, problem statement, proposed approach, timeline, team, pricing tiers, and terms. Researches client company for personalization. Multiple pricing models. Professional formatting matching consulting standards.
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。
1行の説明文
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Renamed to /model-selection in v6 (removed in v7).
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 each author needs an ICMJE Conflict of Interest disclosure form (coi_disclosure.docx) for submission. Clones a pre-filled synthetic seed with every item marked None and replaces only date, name and manuscript title, so most authors just confirm or amend.
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Renamed to /imaging-data in v6 (removed in v7).
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 turning a folder of research PDFs into Obsidian notes, even if Obsidian is not named. Writes one templated literature note per paper and extracts cross-linked atomic concept notes, never overwriting existing ones. A .bib or Zotero library is /lit-sync.
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。
Renamed to /imaging-data in v6 (removed in v7).
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Renamed to /model-selection in v6 (removed in v7).
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。
Searches the code knowledge graph by function, class, or type using FTS5 full-text search. Use when locating code entities by name or qualified path.
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 the einops Python package for readable tensor rearrangement, reductions, repetition, named-axis einsum, packing, framework layers, and repository maintenance workflows.
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。
Routes CS230 code-example requests to the correct PyTorch or TensorFlow vision and NLP workflows for SIGNS image classification and named-entity recognition.
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。
Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools required.
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。
File upload attack hunting - extension/content-type/magic-byte bypass to web-shell RCE, path traversal in filename, SVG/XML XSS, zip slip, and pixel-flood DoS. Wiki-first, FIND schema output.
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。
Autonomous sub-agent hand-off for a fiddly, fully-specified exploit-compile / escalation RUN - the main agent stays on strategy and the board while a cheap sub-agent runs an exact copy-paste checklist behind a false-root/hostname guardrail. Use for "delegate", "offload", "hand this to a sub-agent", "spin a haiku", or the moment a foothold plus a working escalation vector is identified. Main agent dispatches, waits (no parallel duplicate), integrates the result.
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。
This skill should be used when the user asks to "create a location", "add a location", "magic system", "political system", "build the world", "add culture", "world history", "technology system", "religion", "economy", "map", "travel times", "routes", "calendar", "moons", "seasons", "naming language", "conlang names", "trade routes", "supply lines", "magic cost", "add a glossary term", "glossary", "invented word", or wants to develop any aspect of a story's world and setting. NOT for a glossary for translators (use adaptation).
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。