- Skills
- 86
- 仓库
- 2
- 职业覆盖
- 10
- 场景覆盖
- 7
- Stars
- ★ 19w
AutoGPT 的 Skills 86
market-size-estimation
Estimate market size using TAM, SAM, and SOM with top-down and bottom-up approaches. Use when sizing a market opportunity, estimating addressable market, preparing for investor pitches, or evaluating market entry.
lifecycle-email-marketing
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. For cold outreach emails, see cold-email. For in-app onboarding, see onboarding.
legal-response-drafting
Generate a response to a common legal inquiry using configured templates, with built-in escalation checks for situations that shouldn't use a templated reply. Use when responding to data subject requests, litigation hold notices, vendor legal questions, NDA requests from business teams, or subpoenas.
legal-meeting-briefing
Prepare structured briefings for meetings with legal relevance and track resulting action items. Use when preparing for contract negotiations, board meetings, compliance reviews, or any meeting where legal context, background research, or action tracking is needed.
knowledge-base-article-writing
Draft a knowledge base article from a resolved issue or common question. Use when a ticket resolution is worth documenting for self-service, the same question keeps coming up, a workaround needs to be published, or a known issue should be communicated to customers.
jobs-to-be-done
Discover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or "functional vs emotional jobs". Also trigger when investigating why users choose competitors, designing features around real customer needs, or reframing a value proposition. Covers JTBD interviews, competition analysis, and jobs-oriented roadmaps. For product positioning, see obviously-awesome. For rapid validation, see design-sprint. For non-leading interview technique, see mom-test.
go-to-market-strategy
Create a go-to-market strategy covering marketing channels, messaging, success metrics, and launch timeline. Use when planning a product launch, creating a GTM plan from scratch, or defining a launch strategy for a new market.
financial-statement-preparation
Generate financial statements (income statement, balance sheet, cash flow) with period-over-period comparison and variance analysis. Use when preparing a monthly or quarterly P&L, closing the books and need to flag material variances, comparing actuals to budget, building a financial summary for leadership review, or looking up GAAP presentation requirements and period-end adjustments.
employment-offer-drafting
Draft an offer letter with comp details and terms. Use when a candidate is ready for an offer, assembling a total comp package (base, equity, signing bonus), writing the offer letter text itself, or prepping negotiation guidance for the hiring manager.
employee-performance-review
Structure a performance review with self-assessment, manager template, and calibration prep. Use when review season kicks off and you need a self-assessment template, writing a manager review for a direct report, prepping rating distributions and promotion cases for calibration, or turning vague feedback into specific behavioral examples.
employee-onboarding-planning
Generate an onboarding checklist and first-week plan for a new hire. Use when someone has a start date coming up, building the pre-start task list (accounts, equipment, buddy), scheduling Day 1 and Week 1, or setting 30/60/90-day goals for a new team member.
dataset-exploration
Profile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.
data-visualization
Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.
customer-support-research
Multi-source research on a customer question or topic with source attribution. Use when a customer asks something you need to look up, investigating whether a bug has been reported before, checking what was previously told to a specific account, or gathering background before drafting a response.
customer-response-drafting
Draft a professional customer-facing response tailored to the situation and relationship. Use when answering a product question, responding to an escalation or outage, delivering bad news like a delay or won't-fix, declining a feature request, or replying to a billing issue.
customer-insight-research
When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.
customer-escalation
Package an escalation for engineering, product, or leadership with full context. Use when a bug needs engineering attention beyond normal support, multiple customers report the same issue, a customer is threatening to churn, or an issue has sat unresolved past its SLA.
conversion-rate-optimization
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.