「fill」の検索結果

Use on Day 1 of an AIS-OS install, when someone says "set me up", "onboard me", "let's get started", "fill in my AIOS", or has just cloned the kit. Combined wizard — runs the 7-question intake AND scaffolds the Day-1 file set at the end. Idempotent — re-run any time after editing aios-intake.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。

Go-to-market engineering for the Yupcha portfolio (OmniVoice-Studio, the Clay-alternative in this repo, ResuBird). A closed set of executable verbs — research, audit, draft, measure, prepare, publish, escalate — each with a typed contract, required sources, and a risk tier. Use when: (1) researching ICP/competitors/channels/prior art, (2) auditing our own properties for what's actually broken (dead pricing pages, 404ing clone URLs, unfilled demos, licence detection, watermark coverage), (3) drafting docs/comparison pages/release notes/launch copy, (4) measuring real numbers against GOAL.md, (5) preparing a Show HN or a listing up to the send button, (6) any question about whether a GTM action is allowed. Triggers: 'gtm', 'go to market', 'launch', 'show hn', 'growth', 'marketing', 'positioning', 'icp', 'competitors', 'outreach', 'cold email', 'audit our', 'is it ok to', 'can we post', 'promote'.

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。

Enforces decisive execution without confirmation requests; suppresses redundant explanations and prioritizes direct action.

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 or fills gaps in project documentation (README, AGENTS.md, /docs, inline comments).

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。

AI-PLCのスキル（/04-operation 等）を通さずに済ませた作業を、あとから対象 Layer に記録する。どの Layer の作業かを決め、会話にしか無い中間生成物を Documents/ に書き起こし、backlog に ad-hoc タスクとして足し、04-operation の Phase 5.5〜7（検証・ステータス更新・Propagation）を通す。書き込み前に必ず承認を取る。「Propagationして」「さっきの作業を記録して」「Layerに残して」「backlogに後追いで入れて」で使う。

AI-PLCのスキルを通さずに済ませた作業を、あとから対象Layerに記録する（書き起こし・backlogへad-hocで追加・04-operation Phase 5.5〜7で検証後にcompleted）。書き込み前に承認を取る。

Bring Mycelium into a project that already has code. Detects that the repo predates the framework, asks before touching anything, then reads the codebase to draft what it CAN establish (delivery, solution shape) and — the actual point — names what it cannot (purpose, strategy, real user evidence). The output is a discovery backlog with a head start, never a filled canvas.

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。

Remove the AI tells readers react to in a Threads post: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity. Also --mode audit (500-char fit, hook, hashtag cap), --mode profile (learns how you write) and --mode interview (fills your Story Bank: the numbers, turning points and stories posts are made of). Not for writing from scratch (use threads-post-writer). Keywords: humanize, de-AI Threads post, interview me, audit before posting.

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 for analytics and data pipelines. Triggers: ETL, ELT, data quality, SQL optimization, schema drift, backfill, 데이터 파이프라인, 데이터 품질, 백필.

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 verifying that a model in the imp inference engine produces coherent output without repetition loops, token-stuck states, or state corruption across turns or streams. Triggers on "degenerates", "check degeneration", "repetition loop", "own own own", "stuck token", "empty content", "multi-turn regression", "does it still work", "NIAH", and after enabling CUDA graphs / changing forward pass / MoE routing / KV cache or KV dtype / GDN state or scan / sparse attention / PDL / speculation (MTP, n-gram) / ragged prefill / batched-decode kernels (smallm, producer quantize) / FA2 softmax.

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 benchmarking, profiling, or A/B-testing CUDA kernels or end-to-end perf in the imp inference engine on RTX 5090 (sm_120), including refreshing tests/perf_baseline.json or publishing numbers to docs/BENCHMARKS.md and the README. Triggers on "benchmark kernel", "profile cuda", "ncu", "nsys", "kernel timing", "kernel sum", "occupancy", "bandwidth bound", "compute bound", "roofline", "perf baseline", "is this regression real", "decode dropped", "aggregate throughput", "two-image A/B", "prefill kernel A/B". Do NOT use for writing/optimizing kernel code (sm120-cuda-expert) or output-quality checks (check-degeneration).

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 imp outputs differ between two paths that should agree - chunk sizes, prefill vs decode, prefix-cache resend, two engines (imp vs llama.cpp vs HF), two builds or kernels - "output changes with chunk size", "first token differs", "logprobs moved", "which layer diverges", "who is right, imp or llama.cpp", "near-tie". Do NOT use for repetition loops or garbage output (check-degeneration), a new arch that loads wrong (add-model-arch), or perf (benchmark-cuda).

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。

Evaluates alternative trading systems with fill rate analysis, information leakage assessment, and venue toxicity measurement. Use when analyzing dark pools, evaluating ATS venues, or assessing execution venue quality.

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。

AI browser automation via CDP. Use when you need to control a browser, navigate pages, click elements, fill forms, extract content, or take screenshots.

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。

Structured debug log analysis for Claude Code sessions — auto-discovers most recent log, runs reducer, extracts error patterns, correlates with full log, produces observability report. Fills 5 identified gaps: hook error body capture, agent identity, file path tracking, stall correlation, success visibility.

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。

Programmatic web automation using Playwright Python — data extraction, form filling, multi-step workflows, auth session management, screenshot/PDF capture, and anti-detection patterns. Use for scripted automation tasks, not interactive MCP-based browser control.

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。

End-to-end international trip planning: turns "I want to go to X for N days" into a verified, bookable plan — route skeleton across cities, flight price scans (international + domestic legs), train-vs-fly decisions, hour-by-hour daily timelines with opening hours, dwell times, holiday collisions and tappable turn-by-turn map links (小时级行程+地图导航+离线KML), hotel shortlists by neighborhood, budget rollup, and a booking checklist with deep links. Use this whenever the user asks to plan a trip, vacation, itinerary or honeymoon, compare flight dates/prices, pick between cities or routes, schedule a travel day hour by hour, fill a spare block of time ("I'm near X with 2 free hours"), turn a finished plan into a designed page (eight themed renders: illustrated / clay / noir / glass / journal / zine / splash / portal — 插画/黏土/夜航/玻璃/手账/Zine/闪屏/穿越版), or asks 旅行规划/行程安排/机票比价/去某国玩N天怎么安排/现在有空档干嘛/把行程做成好看的网页 — even if they only mention one piece (just flights, just hotels, or just navigation), the playbook and verification rules here still apply.

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。

Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges everything into the template that already contains Intro + Related Work from Step 3. TRIGGER when the orchestrator delegates Step 4 or when the user asks to "write the methodology and experiments sections" or "fill in the rest of the paper".

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。

Review public site content for editorial quality, source support, prompt residue, duplicate blocks, translation drift, hidden filler, and human usefulness before SEO or LLM-friendly publication. Use this skill when the user asks to quality-gate news briefs, longform explainers, blog posts, topic pages, project pages, translated content, or generated article drafts without changing the live publishing 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。

Adopt govctl in an existing project. Discovers undocumented decisions, backfills ADRs/RFCs, annotates source code. Use when: (1) Project has no governance yet, (2) User mentions migrate, adopt, onboard, or brownfield

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。

Drive a real web browser: navigate, read, find, click, fill, screenshot

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。

Interactively gather parameters for `python -m cli.inference.text_generate`, generate a concrete text generation simulation command, explain assumptions, ask for execution confirmation, then run the command and summarize performance metrics. Use when the user wants to validate a specific model, hardware profile, batch/query size, prefill or decode scenario, TP/DP/EP/MOE parallel strategy, profiling database, chrome trace, empirical metrics export, or a best row produced by throughput_optimizer.

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。

Plan safe Convex schema and data migrations. Use for widen-migrate-narrow rollouts, backfills, breaking field changes, table splits, or failed schema deploys.

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 a local talking-head / 口播 video into metadata, transcript, and an AI-composed card-based video where the agent composes cards by cloning styled templates and filling them (designing bespoke only when content needs it), then renders to MP4. Ships with the Interflow AI club sign-off ("Interflow AI 出品"). Use when the user asks for interflow-video-cut, 口播成片, talking-head repurposing, video takeaways, transcript cleanup, or turning a spoken video into a captioned card video.

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。