「founder」の検索結果

Write personalized cold outreach emails to hiring managers and founders — specific, human, not a pitch deck

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。

Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-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。

Install and manage Python packages using uv pip. Use when a Python import fails with ModuleNotFoundError, user asks to install a package, or a script requires a missing dependency.

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。

Opinionated startup-PR strategist that helps founders figure out audience, positioning, news pegs, and drumbeat before any tactical PR. Refuses outlet-naming-before-audience, mass blasts, vanity metrics, and premature agency spend.

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 adversarial due-diligence on a benchmark the user envies — a founder, KOL, company, or product whose success looks inflated — splitting marketing bubble from real signal, then mapping the validated playbook onto the user's own resources. Use for 尽调/对标/拆解 a competitor, 抄/偷师 their playbook, or suspecting 水分/泡沫 in claims. Prefer over deep-research when debunking inflated claims, not a neutral briefing.

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。

Explain a cap table, dilution, SAFEs, option pools, and round mechanics in plain English with the actual math. Use when asked to explain dilution, model a SAFE or priced round, size an option pool, understand a term sheet's economics, or figure out who owns what after a raise. Produces a worked ownership breakdown before/after the round, the dilution math step by step, and the traps founders miss. Not legal or financial advice.

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。

Help users navigate the psychological burdens of leadership by cultivating emotional awareness, reframing failure, and building sustainable mental health practices.

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。

Help users recruit compatible co-founders, sequence early leadership hires to fill capability gaps, and manage the evolution of the executive team as the company scales.

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。

Help users identify, attract, and hire exceptional product managers and engineers by shifting from passive HR processes to a founder-led, high-intensity recruitment strategy.

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。

Help users build a robust enterprise sales engine by mastering founder-led discovery, navigating complex procurement cycles, and designing products that meet organizational governance needs.

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。

Help users master the art of proactive communication and alignment with their managers and founders to unlock autonomy, secure resources, and drive business impact.

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。

Install Codex themes and Codex skin packs with npx skills. Use this skill when a user wants Codex to find, download, validate, apply, switch, remix, or restore Codex desktop themes such as caishen-readable, caishen-lite, mythic-guardian-noir, global-founder-bright, export-night, or caishen-max. It stages verified public-safe theme packs from ChannelerH/codex-skin-packs, checks theme.json/background.png, preserves the native Codex layout, avoids private workspace screenshots, and provides restore guidance.

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 personalized demo assets for top prospects using the founder's product API/MCP/SDK. Researches prospect, proposes demo concepts, builds working prototype, tests it, and generates comparison report with live demo link.

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。

Scrape recent posts from LinkedIn profiles using Apify. Use when you need to monitor what specific people are posting on LinkedIn, track founder/exec activity, or gather LinkedIn content for competitive intelligence.

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。

Analyze a creator, influencer, founder, competitor, or brand social account to explain its positioning, content pillars, winning posts, hooks, formats, series, calls to action, and audience response. Use when the user wants to understand why an account works and what patterns to test without copying it.

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。

Scan support tickets, Slack channels, NPS scores, and usage patterns to flag accounts showing early churn indicators. Produces a weekly risk scorecard with severity tiers, root cause hypotheses, and suggested save plays per account. Designed for seed/Series A teams where the founder or a single CSM manages all accounts manually.

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-sales-call intelligence composite. Deep dives on the person AND their company before a sales call, then maps findings to your product to generate talking points, objection prep, and a call strategy. Goes beyond generic attendee research — this is sales-specific intelligence that helps SDRs, AEs, and founders walk into calls with a plan. Tool-agnostic — works with any CRM, research source, and calendar.

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。

Track what key opinion leaders (KOLs) in your space are posting on LinkedIn and Twitter/X. Surfaces trending narratives, high-engagement topics, and early signals of emerging conversations before they peak. Chains linkedin-profile-post-scraper and twitter-mention-tracker. Use when a marketing team wants to ride trends rather than create them from scratch, or when a founder wants to know which topics are resonating with their audience.

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。

Generate a complete marketing campaign brief from a launch goal, ICP, and product context. Pure reasoning skill. Outputs channel plan, messaging angles, content types, timeline, and success metrics. Designed for seed/Series A founders and small GTM teams who aren't professional marketers but need to run focused campaigns. No scripts — pure reasoning.

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。

For founders who don't know where to start with paid ads. Analyzes ICP, competitor ad presence, budget constraints, and product type to recommend which 1-2 paid channels to start with and provides a 90-day ramp plan. Prevents the common mistake of spreading a small budget across too many platforms.

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。

Comprehensive GTM analysis of any target company. Researches what a company is currently doing across all go-to-market dimensions — content/blog, founder LinkedIn activity, SEO/traffic, hiring signals, social/community presence, customer acquisition channels, podcast appearances, review sites, competitive positioning, and partnerships. Produces a structured report identifying what's working, what's missing, and where white space exists for new strategies. Use before designing GTM strategies for a client or prospect.

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。

Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.

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。

Identify differentially bound regions across CLIP-seq conditions (knockdown vs control, treatment vs vehicle, disease vs healthy) using DEWSeq (sliding-window DESeq2), Flipper (Skipper-downstream), ASpeak, edgeR, or limma-voom. Use when computing condition-level changes in RBP binding intensity, choosing peak-level vs window-level vs crosslink-level testing, designing replicate experiments, or distinguishing biological binding shifts from technical confounders.

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。

Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS, CAUSE, LHC-MR, LCV, MR-Clust, MR-Mix, and contamination-mixture methods. Use when validating an MR causal claim, running the STROBE-MR sensitivity battery, suspecting a shared heritable confounder, working under weak-instrument or polygenic-exposure regimes, or reconciling discordant estimates across robust methods.

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。