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概要と使いどころ
Review someone else's PR through an architectural/strategic lens — does it shift design, raise complexity, or quietly change precedent? Drives a brief reflective discussion with the user, then posts a concise review comment via `gh`. Defers line-level and bug-hunting concerns to AI review bots and the PR author.
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Router and protocol for reading and extracting web content. Decides first WHAT is needed (main text vs. structure vs. screenshot) and then WHICH tool available on the system delivers it. If nothing suitable is present, it recommends installing the web-scraper module.
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。
Builds a personal voice profile from roughly 90 days of the user's own sent messages and meeting speech, then drafts emails and documents that match how the user actually writes, returning the profile and every draft as Markdown for the user to keep, paste or send themselves. Use when the user asks to "write this like me", "match my voice", "draft this in my tone", "build my voice profile" or "refresh my voice profile". Do not use for an announcement in the organisation's voice, use announcement-drafter instead, nor for a weekly status email, use weekly-status-update-writer instead. Drafts for human review; never approves, authorises or signs off.
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。
Turns an actuals-versus-budget extract (spreadsheet, export or pasted table) into a DRAFT variance table with absolute and percentage variances, favourable or adverse marking and a ranking by size, then drafts plain-language driver hypotheses for each material variance as questions to verify with a named owner, never as asserted causes. Use when the user asks to "explain these variances", "why are we over budget on this line", "write the variance commentary for the management pack", "actuals versus budget analysis" or "which lines drive the variance". Do not use for a dataset with no budget or comparison column, use dataset-insight-pack instead; for weekly operational figures against last week, use kpi-weekly-report-writer. Drafts for human review; never approves, authorises or signs off.
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。
Checks an extracted PFD register as a process model and returns findings and unknowns only: connectivity closure, stream numbering, presence of design conditions, equipment duty text, phase and service labels, package and off-sheet scope, boundaries, operating cases, and agreement between the drawing and attached process documents, then holds at gate G2. Creates no design values. Use when the user asks to "check the process model", "verify connectivity" or "is the PFD ready for enrichment" after gate G1 and before enrichment. Do not use for extraction from the drawing, use pfd-intake-and-extraction instead; do not use to propose lines or instruments, use piping-enrichment. Drafts for human review; never approves, authorises or signs off.
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。
Reads a process flow diagram (image, PDF or native export) with its job header and returns a provenance-tagged extraction register: equipment, streams, tags, connectivity, instruments already shown, notes and legends, connectivity findings and an explicit UNKNOWN list, then holds at gate G1. Extracts and records only; never enriches, tags or proposes. Use when the user asks to "start a PFD to P&ID job", "read in the attached PFD", "extract the equipment and streams from this PFD" or "read this PFD into a register". Do not use for checking the model, use process-model-check instead; do not use to propose lines, instruments or tags, use piping-enrichment or instrumentation-and-control-enrichment after gate G2. Drafts for human review; never approves, authorises or signs off.
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。
Prepare and launch LoRA, LoKr, or T-LoRA training through lora-scripts-next (SD-Trainer), Anima-first. Use when the user asks to train a character, style, or concept LoRA, choose parameters or repeats and epochs, start a run, or monitor training on Anima, SD1.5, SDXL, or Flux. Organize and caption the dataset, run dataset-doctor, choose a documented starting preset from image count and VRAM, show one confirmation card, then call the mikazuki API and monitor its log.
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。
Pre-launch security audit for web apps. Runs OWASP checks via shell scripts, then AI analyzes findings. Covers rate limiting, hosting bypass, data exposure, headers, session security, AI risks. Complements /security-review.
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。
Quality gate immediately after building: prove that what was just built actually works, while the context is still hot. Six steps: scope what changed, run live on real data, break it on purpose, show a counter or log proving it ran, root-cause any failure and re-run, then a verdict with evidence. Only a green verdict earns the word done. Supports an external multi-vendor review panel as a mid-step. Triggers: "/tt", "/test", "prove it works", "test what we built".
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。
Stop a Google Takeout export from expiring undownloaded: detect the ready-to-download mails with a deterministic zero-token scan, report the live links with days remaining, then drive the download and vault import. Triggers: "/takeout-pull", "is my takeout ready", "pull my takeout".
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。
Find live third-party GitHub issues and discussions on topics where you have real hands-on experience and artifacts, then reply with that experience to build reputation. Use when asked to answer people about your work, find threads matching your expertise, or reply with evidence from your own setup.
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。
Turn any hypothesis, however fringe, into an argument map rather than a verdict: five independent lenses (consensus, skeptic, frontier, historian, experimental design), then a synthesis of for and against, evidence quality, a confidence tier and the cheapest decisive experiment. Triggers: "/research-swarm <hypothesis>", "map the arguments on X".
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。
Introduce two or more people from the owner's network: resolve and confirm both identities, DM each side for consent before any group exists, then create the group and introduce both sides inside it. Requires the owner's approval first. Triggers: "/intro", "introduce X and Y", "connect X with Y".
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。
Mine any Telegram channel or chat for signal in one command: incremental zero-token scrape, deterministic detector shortlist, LLM judge for what is genuinely valuable to this owner, then linked vault notes, a database row, a map-of-content entry and reindex. Triggers: "/mine-channel <@channel|id>", "alpha from <channel>".
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。
- Enumerate a username across hundreds of platforms with sherlock, maigret and WhatsMyName, then correlate and confirm which accounts genuinely belong to the same person.
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。
Pick up and continue a serialized build-in-public book: read the current state (which days are written in which languages, what is uncommitted, where the gaps are), then keep writing through the established pipeline. Triggers: "/journey", "the book", "continue the journey".
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。
Send one research question to as many independent LLMs as possible at once, each in its strongest reasoning mode with proof of that mode, then synthesize. Floor of 3 models, quorum of 4; late answers are collected later. Use for high-stakes questions where one model's view is not enough. Triggers: /hyper, hyper research, ask every LLM, max fan-out research.
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。
- Verify whether an image or video is authentic, original and correctly captioned — provenance checks, error level analysis, noise and JPEG compression analysis, clone and copy-move detection, lighting and shadow consistency, C2PA… Use when fact-checking a photo or video, checking for a deepfake or AI-generated image, spotting manipulation, or testing whether footage is recycled or miscaptioned
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。
Fan one deep-research prompt out to several external LLMs at once through a logged-in browser, then collect the reports, archive the originals and synthesize a consensus. Use at the final stage of a research protocol, instead of hand-pasting one prompt into N sites. Triggers: "/dr-fanout", "fan out the DR", "distribute the research prompt".
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。
Write the follow-up after a call in the owner's own voice instead of a bot template: recall the transcript, person card and full correspondence, extract agreements with an owner and due date, draft short and personal, show before/after against the old template, then send through the approval gate and file the result to the person card. Triggers: "/fa", "follow-up", "what should I write to <name> after the call", or a fresh call transcript landing in the vault.
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。
Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.
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。
Sell layer: raise the framing of an artifact to the scale it actually deserves without touching a single number. Use before anything goes outbound (post, pitch, README, CV, PR comment, landing page, application, DM) or before showing a finished artifact. Triggers: /fake-it, /fi, sell it, make it louder, strengthen the frame.
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。
Cut background heat and noise on this machine: audit scheduled tasks by runs per hour, autostart entries, GPU holders, power plan and top CPU, then propose disable or stretch candidates, decide line by line with the operator and apply only approved lines. Triggers: /deflate, fan is loud, laptop runs hot, what can I turn off, machine slow from background load.
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。
Pull fresh call recordings and transcripts from Fireflies.ai into an Obsidian vault over the official GraphQL API, then distill action items and commitments and reindex. Incremental and idempotent by transcript id. Triggers: "/fireflies-sync", "pull fireflies", "sync call recordings".
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。