Each skill is a packaged GTM capability that reads your context layer through the RevSure MCP Server and does one job well — inside Claude, ChatGPT, Glean, or an agent you built yourself. When the task outgrows one skill, it hands off to a full RevSure agent.
Reads Prediction, Signals, Intelligence & Data — ships through Action
A skill is not a prompt — it is a set of instructions wired to real MCP tools. It reads the same governed context every agent reads, does its one job, and only escalates when the task is bigger than a single skill.
Claude, ChatGPT, Glean, Cursor, Windsurf — or any client that speaks MCP.
Token auth, RBAC scopes, PII redaction. Every call hits the same governed truth.
Reads the context, applies judgment, drafts the output — inline, in your chat.
Chains into a full RevSure agent for the multi-step play. Proposed, approved, reversible.
Reads the context · Does the job · Escalates when needed · Reversible
Every skill below is built on the same RevSure MCP tools your agents already use. Filter by function, or scroll the whole library.
Runs full account research, maps the buying group, and drafts an action plan with prospects to add — chains into deeper agent research when the account is bigger than one pass.
Finds closed-lost opportunities worth re-engaging, checks for job changes and account signals, and drafts outreach that addresses the real reason the deal died.
Ranks leads across every account by real conversion probability, drafts the outreach, and routes the shortlist to the team.
Builds a one-page brief before every call — deal history, stakeholder roles, sentiment from past meetings, and suggested talking points.
A full account brief on request: org structure, tech stack, recent news, and suggested entry points into the buying committee.
Pulls the most common objections and the responses that actually won, for a given persona, segment, or competitor.
Finds leads gone quiet for 60 to 90 days, checks what changed at their company, and drafts an email worth opening.
Scans open opportunities for fading engagement and risk signals, and surfaces the next-best action for each rep.
Finds champions who changed jobs on open and recently won accounts, flags the deals losing their internal advocate mid-cycle, and drafts both a reconnect email to the mover and a continuity brief for whoever inherits the account.
Checks whether the next step agreed in each recent meeting actually happened, cross-referenced against journey activity, and drafts a nudge for every next step that went stale.
Measures persona coverage on an active deal against the full buying group, flags the ones missing an economic buyer or champion entirely, and drafts multi-thread outreach to the personas that aren't there yet.
Scans engagement and chat signals for named-competitor mentions, cross-references that competitor's own web signals — layoffs, leadership churn, negative press — and drafts a displacement angle for the accounts already citing them.
Ranks open opportunities by real stall risk — quiet activity against a near close date, negative engagement, objections still unanswered — and drafts a save play that answers each deal's specific objection instead of a generic check-in.
An interactive touchpoint explorer for any set of accounts or opportunities — filterable by person, title, role, channel, or campaign type, with campaign-member-level export.
An ad-hoc journey deep dive on whichever opportunities you name — pulls their live touchpoint and channel data and compares the paths side by side.
The same deep dive, pre-loaded for the five most recent RevSure primary-tenant opportunities — AlayaCare, Mastercard, TeamViewer, Mosaic, and Inhabit — so there is nothing to name first.
Scores open pipeline against the patterns behind past wins — which engagement types and journey shapes actually correlate with closing, and which deals match them.
Models where budget should move for the best ROI lift, with the attribution data to back the recommendation.
Surfaces accounts showing in-market behavior on G2, intent platforms, and third-party signals before they ever hit the CRM.
When an account shows buying intent, enriches it and drafts a coordinated outreach plan across the whole buying group.
Ranks every channel and source by performance this period, and formats it as a share-ready summary.
Drafts the enrichment and sequencing plan for attendees after a webinar or field event, scored by engagement.
Checks whether your LinkedIn ad audiences match the current ICP and funnel-stage segments, and flags where they've drifted.
Builds a fresh account target list three ways — a query-built ICP filter, a pasted list, or a signal-driven scan — then tiers it by real engagement so only the highest-signal accounts earn full research and prospecting.
Compares email engagement states — delivered, opened, clicked — across closed-won and closed-lost opportunities, to test whether email nurture correlates with winning at all.
Isolates which touchpoints actually lift win rates — the closed-won versus closed-lost touchpoint gap, and exposed versus unexposed conversion side by side.
Builds an interactive forecast dashboard — projected pipeline, win rate, and segment breakdown, past and future quarters, in one artifact.
A digest of conversion rates, stage velocity, and drop-off anomalies versus the prior period, formatted for Slack or email.
Compares pipeline commit to historical conversion rates and flags exactly which deals are at risk of slipping before close.
Scans open opportunities for stale deals, missing fields, or wrong-stage progression, and nudges the owning AE.
Shows why a lead scored the way it did — which signals fired, which are missing, and what would move the score.
Finds gaps in firmographics and technographics across the contact and account database, ready for enrichment.
Fits response curves per channel — S-curve, Weibull, Michaelis-Menten — and separates cumulative from marginal ROI.
The full lead-to-close funnel in one artifact — quarterly trends, conversion heatmaps, stage velocity, and anomaly detection from first visit through booked meeting.
Adds a self-contained methodology tab to any data-backed artifact, so every chart, table, and KPI documents the exact tools, filters, metrics, and date windows behind it.
The pre-read every session starts with — the MCP startup sequence, tool-routing rules, memory workflow, and response format, so stage names, filters, and tenant config are never guessed.
Flags accounts showing churn signals — declining usage, a departing champion — with a severity score and a save play.
Monitors product usage and account engagement to surface customers ready for upsell or cross-sell, with the context to open the conversation.
Summarizes account journey, engagement trend, and sentiment from recent calls into a single pre-QBR brief.
For accounts nearing renewal, weighs deal health, MEDDPICC gaps, blockers, and named upsell targets against renewal benchmarks, calls each one renewal-risk or expansion-ready, and drafts the QBR talking points to match.
The library keeps growing. Add to it yourself, or ask the RevSure team to build the one you need.
Already have a SKILL.md or a tool wrapper? Upload it and it runs across every environment on the list, governed by the same MCP gateway as everything else.
Upload a skillStart from a template — a single MCP tool, a chained sequence, or a full play like Account Expansion — and we scaffold the rest.
Start buildingTell us the job. A RevSure GTM engineer scopes, builds, and publishes it to your library — fast, for anything close to an existing pattern.
Request a skillA GTM skill is a packaged, single-purpose capability — like scoring a lead or prepping a meeting brief — that reads your context layer through the RevSure MCP Server and runs inside the AI environment you already use, such as Claude, ChatGPT, or Glean.
A skill runs on demand inside your chat and does one job when you ask for it. An agent runs autonomously on a schedule or trigger and can chain multiple steps together. Skills can escalate to a full agent automatically when a task needs that extra depth.
RevSure skills run in Claude, ChatGPT, Glean, Cursor, Windsurf, and any client that speaks the Model Context Protocol (MCP), since every skill is built on the RevSure MCP Server.
Every skill call goes through the RevSure MCP Server, which enforces scoped token authentication, role-based access control, field-level PII redaction, and an immutable audit ledger — the same gateway every RevSure agent uses.
Yes. If you already have a SKILL.md file or a tool wrapper, upload it from the Skills Hub and it becomes usable across every supported environment, governed by the same MCP gateway as the rest of the library.
Yes. Submit the job through the form on this page and a RevSure GTM engineer will scope, build, and publish the skill to your library.
A skill drafts the output for you to review. When it escalates to a full RevSure agent for a multi-step play, that agent's actions still follow RevSure's propose, approve, commit, rollback pattern, so nothing ships without approval and every action stays reversible.
Yes. Every read, write, and decision made through a skill lands in the same immutable, append-only audit ledger used by every RevSure agent.
Governed by the same RBAC and audit ledger as every RevSure agent.
See the library running against your own context layer.