Owns the revenue engine end to end: sales, monetization, pricing, customer success, retention, and partnerships. Use this for pricing and packaging decisions, sales strategy and coverage, forecast and pipeline health, churn and expansion, partner and channel strategy, or when marketing-sourced demand is not converting. Also use to decide which segments to pursue and which to decline.
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。
cbrock84/headcount☆ 2,0502026年9月18日 更新
Finds, qualifies, and reaches prospects through cold outreach — list building, qualification criteria, cold email and multi-channel sequences, and the follow-up that actually gets replies. Use this to build a prospect list, write cold outreach, fix a sequence that is not getting responses, define qualification criteria, or decide whether a segment is worth pursuing.
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。
cbrock84/headcount☆ 2,0502026年9月18日 更新
Establishes whether the business makes money on each customer or unit — contribution margin, acquisition cost, payback period, lifetime value, and the cohort behavior underneath. Use this to assess whether growth is profitable, evaluate a channel or segment, support a pricing decision, judge how fast the business can afford to grow, or diagnose why revenue growth is not producing profit.
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。
cbrock84/headcount☆ 2,0502026年9月18日 更新
Establishes what a product is understood to be, for whom, and instead of what — then turns that into the messaging every other surface inherits. Use this when messaging is inconsistent across channels, when prospects misunderstand what the product does, when entering a new segment, when competitors are being compared against you unfavorably, or before any campaign, launch, or site rewrite.
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。
cbrock84/headcount☆ 2,0502026年9月18日 更新
Runs the ongoing relationship with accounts after the sale — segmenting coverage against account value, building a health score that predicts rather than describes, running reviews customers find worth attending, forecasting renewals honestly, and finding expansion that follows usage instead of quota. Use this to design a customer success motion, decide who gets a named contact, work out why renewals surprise you, or fix a health score everyone ignores.
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。
cbrock84/headcount☆ 2,0502026年9月18日 更新
Designs automated email and SMS programs — welcome and onboarding sequences, nurture, re-engagement, transactional messaging, and the timing and segmentation behind them. Use this to build or fix an email sequence, plan lifecycle automation, improve open or click performance, set up SMS flows, or decide what messages a customer should receive and when.
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。
cbrock84/headcount☆ 2,0502026年9月18日 更新
Decides whether and how to enter a new market — sizing demand from the bottom up rather than from a market report, testing whether your advantage transfers, choosing between organic entry, partnership and acquisition, sequencing the operational and regulatory work that entry actually requires, and setting the criteria that would tell you to stop. Use this to evaluate a new geography, segment or vertical, pressure-test an entry plan, or work out why a launched market never reached scale.
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。
cbrock84/headcount☆ 2,0502026年9月18日 更新
Detect copy number variations from whole genome sequencing data and generate publication-quality genome-wide CNV plots. Supports CNV calling, segmentation, and visualization for cancer genomics and rare disease analysis.
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。
aipoch/medical-research-skills☆ 1,9492026年9月17日 更新
Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests f...
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。
aipoch/medical-research-skills☆ 1,9492026年9月17日 更新
Detect initial silence segments in audio/video using energy-based analysis. Use when you need to find low-energy periods at the start of recordings (title slides, setup time, pre-roll silence).
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。
benchflow-ai/skillsbench☆ 1,8432026年10月13日 更新
Generate compression reports for video processing. Use when you need to create structured JSON reports with duration statistics, compression ratios, and segment details after video processing.
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。
benchflow-ai/skillsbench☆ 1,8432026年10月13日 更新
This skill should be considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.
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。
benchflow-ai/skillsbench☆ 1,8432026年10月13日 更新
Use this skill when converting natural language flight commands into waypoints and timing for a drone simulator. Covers parsing commands like "Take off to X m height in Y seconds", "Hover at X m height for Y seconds", "Fly from (x,y,z) to (x',y',z') in T seconds", and "Land from X m height in Y seconds" into structured (4×n) waypoint arrays and segment mode lists.
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。
benchflow-ai/skillsbench☆ 1,8432026年10月13日 更新
Use this skill when implementing the outer control loop for a quadrotor — position PID control (position/velocity error → thrust and desired acceleration) and trajectory planning from flight-plan waypoints (takeoff, hover, fly, land segments → smooth 15-row state matrix).
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。
benchflow-ai/skillsbench☆ 1,8432026年10月13日 更新
Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub.
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。
benchflow-ai/skillsbench☆ 1,8432026年10月13日 更新
How to capture new reusable patterns into ktx's semantic layer - when a measure, segment, or join belongs in the catalog and how to write it generically so it stays small and useful over time. Loaded by the post-turn memory-agent only. The research agent does not write to the SL.
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。
Kaelio/ktx☆ 1,6162026年9月11日 更新
ktx's semantic layer - a structured catalog of sources (tables/views), measures, joins, and segments expressed as YAML. Covers the schema and how to query it via `sl_query`. Use when the task involves querying pre-defined metrics (ARR, churn, retention, LTV, MAU) or reading SL source YAML to understand the catalog. Capture is handled by the `sl_capture` skill (memory-agent only).
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。
Kaelio/ktx☆ 1,6162026年9月11日 更新
Transcribes audio or video to speaker-labeled, timestamped text, locally with MLX on Apple Silicon or remotely. Use for 转录 / 录音转文字 / 说话人分离 / 字幕, and also for preparing audio for ASR without transcribing: 转格式, 降采样到 16kHz, merging recorder segments, or compressing and speeding up audio before 飞书妙记 — even when it looks like a one-line ffmpeg job.
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。
daymade/claude-code-skills☆ 1,4582026年10月13日 更新
Structure a cohort analysis for retention, LTV, or behavioural patterns. Use when asked to run a cohort analysis, analyse retention by cohort, segment users by behaviour over time, or calculate lifetime value by acquisition period. Produces a complete cohort analysis framework with methodology, cohort definitions, retention curves, and prioritised interventions.
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。
mohitagw15856/pm-claude-skills☆ 1,4502026年10月13日 更新
Analyse a finished A/B test and write the readout — the result, whether it's statistically and practically significant, what it means, and the ship/no-ship call. Use when asked to analyse experiment results, write an A/B test readout, interpret test data, or decide whether to ship a variant. Produces a clear verdict with the lift and confidence, segment cuts, the risks (peeking, novelty, sample), and a recommendation. Distinct from planning a test — this reads results.
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。
mohitagw15856/pm-claude-skills☆ 1,4502026年10月13日 更新
Build an all-hands that lands with everyone from intern to VP — the mixed-altitude structure (the story for all, the numbers for some), the wins-with-names section done right, the hard-news slide handled straight, and the Q&A design that gets real questions. Use when asked build the all-hands deck, make the monthly town hall not boring, how do we share the numbers with everyone, or announce this change at all-hands. Produces the segment structure, the altitude-mixed content rules, the hard-news handling, and the Q&A mechanics.
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。
mohitagw15856/pm-claude-skills☆ 1,4502026年10月13日 更新
Help users define the strategic context for their product by identifying the right competitive alternatives, unique value drivers, and target segments to win a market category.
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。
RefoundAI/lenny-skills☆ 1,3912026年7月17日 更新
Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings, and trim a source into named clips at exact windows (trim_clips.py). Ships montage.py, a free montage assembler (python3 + ffmpeg, no keys). It takes a JSON EDL of clips and stills, normalizes them and hard-cuts them in order, burns captions from an SRT, a cue list or word timings, and lays a VO over a music bed that ducks under it, mastered to -14 LUFS.
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。
gooseworks-ai/goose-skills☆ 1,2472026年10月14日 更新
Research a company's ideal customer profiles and build detailed synthetic buyer personas. Identifies 4-6 distinct buyer segments through web research, then creates rich, realistic personas with demographics, motivations, skepticism profiles, decision criteria, and language patterns. Use when you need to understand who your buyers are at a deep level — their motivations, objections, and how they evaluate solutions.
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。
gooseworks-ai/goose-skills☆ 1,2472026年10月14日 更新