Revops
AvdLee/RocketSimApp
When the user wants help with revenue operations, lead lifecycle management, or marketing-to-sales handoff processes.
Build a scalable outbound B2B sales machine with specialized roles (SDR, AE, CSM).
$ npx skills add wondelai/skills --skill predictable-revenue -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wondelai/skills predictable-revenue --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/predictable-revenue .claude/skills/predictable-revenue && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "predictable-revenue" agent skill from https://github.com/wondelai/skills/tree/main/predictable-revenue into .claude/skills/predictable-revenue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "predictable-revenue", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/wondelai/skills/tree/main/predictable-revenueType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add wondelai/skills --skill predictable-revenue -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wondelai/skills predictable-revenue --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/predictable-revenue .agents/skills/predictable-revenue && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "predictable-revenue" agent skill from https://github.com/wondelai/skills/tree/main/predictable-revenue into .agents/skills/predictable-revenue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "predictable-revenue", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wondelai/skills --skill predictable-revenue -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wondelai/skills predictable-revenue --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/predictable-revenue .cursor/skills/predictable-revenue && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "predictable-revenue" agent skill from https://github.com/wondelai/skills/tree/main/predictable-revenue into .cursor/skills/predictable-revenue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "predictable-revenue", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/wondelai/skills.git --path predictable-revenue--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add wondelai/skills --skill predictable-revenue -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wondelai/skills predictable-revenue --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/predictable-revenue .gemini/skills/predictable-revenue && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "predictable-revenue" agent skill from https://github.com/wondelai/skills/tree/main/predictable-revenue into .gemini/skills/predictable-revenue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "predictable-revenue", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install wondelai/skills predictable-revenueInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add wondelai/skills --skill predictable-revenue -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/predictable-revenue .github/skills/predictable-revenue && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "predictable-revenue" agent skill from https://github.com/wondelai/skills/tree/main/predictable-revenue into .github/skills/predictable-revenue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "predictable-revenue", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wondelai/skills --skill predictable-revenue -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wondelai/skills predictable-revenue --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/predictable-revenue .opencode/skills/predictable-revenue && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "predictable-revenue" agent skill from https://github.com/wondelai/skills/tree/main/predictable-revenue into .opencode/skills/predictable-revenue/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "predictable-revenue", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
predictable-revenueBuild a scalable outbound B2B sales machine with specialized roles (SDR, AE, CSM).
Predictable Revenue is an agent skill from wondelai/skills. Build a scalable outbound B2B sales machine with specialized roles (SDR, AE, CSM). Use when the user mentions "outbound sales", "Cold Calling 2.0", "cold email sequences", "sales pipeline", "SDR process", "sales development", "build an outbound sales team", or "fill my pipeline". Also trigger when setting up a B2B SaaS sales team from scratch or building a lead-qualification framework to improve close rates. Covers the three lead types (seeds/nets/spears), role specialization, the referral-email method, ANUM…
Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/case-studies.md`, `references/cold-calling-2.md` and `references/lead-types.md`).
It sits in Sales & Support, covering Cold outreach, CRM management and Multi-tenancy. The repository describes itself as: Wondel.ai Agent Skills — Business, Marketing, UX & Coding Frameworks from Bestselling Books. 50 skills + 12 guided journeys for Claude Code, Codex, Cursor & other agentskills.io… The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit c172996. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
amazon.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Predictable Revenue loads about 3.1k tokens when it runs, and up to ~29k if it reads all its reference files. Until then it costs about 166 tokens; SKILL.md has 1,402 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from wondelai/skills at commit c172996, republished under its MIT licence (© wondelai). 1,402 words, ~3,076 tokens.
.claude/skills/predictable-revenue/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.A systematic approach to building a scalable, predictable B2B sales machine — the outbound prospecting system that helped Salesforce add $100M in recurring revenue.
Predictable lead generation drives predictable revenue. The biggest mistake in sales is having the same people prospect AND close — specialization creates a repeatable, scalable machine. Traditional cold calling is dead; Cold Calling 2.0 (mass, personalized cold emails that generate referrals to the right person) is the new outbound.
Goal: 10/10. Score a sales process 0-10 by awarding 2 points for each of the five Quick Diagnostic rows it satisfies (prospecting/closing separated, defined outbound process, 3-month pipeline predictability, known lead-type mix, standardized SDR→AE handoff). Bands: 9-10 = role separation plus a repeatable process that predicts pipeline; 5-6 = some specialization but ad-hoc prospecting or unpredictable pipeline; ≤3 = one person prospects and closes, revenue depends on heroics. Always give the current score and the specific diagnostic rows blocking 10/10.
Not all leads are equal — treat them differently.
| Type | Source | Conversion | Cost | Example |
|---|---|---|---|---|
| Seeds | Word of mouth, referrals, organic | Highest | Lowest (takes time) | Customer referral, NPS-driven |
| Nets | Marketing campaigns, inbound | Medium | Medium | Content, SEO, webinars |
| Spears | Outbound prospecting | Lower but predictable | Higher (people-intensive) | Cold Calling 2.0 |
Key insight: Most companies over-invest in nets and under-invest in spears; seeds are the best but can't be manufactured quickly. Invest accordingly — customer success and referral programs (seeds), content and paid acquisition (nets), SDR team (spears).
See references/lead-types.md when deciding where to invest — it sizes the seeds/nets/spears budget split by company stage.
The #1 principle: separate prospecting from closing. When AEs prospect and close, they hate prospecting and pipeline becomes feast-or-famine.
| Role | Focus | Metrics |
|---|---|---|
| SDR (Sales Development Rep) | Outbound prospecting → qualified opportunities | Qualified meetings/month |
| MDR (Market Development Rep) | Inbound lead qualification | Qualified leads/month |
| AE (Account Executive) | Close deals | Revenue closed, win rate |
| CSM (Customer Success Manager) | Retain and grow accounts | Retention, expansion revenue |
Generate qualified pipeline: research target accounts, send Cold Calling 2.0 emails, get referred to the right person, qualify with ANUM, pass to AEs. Not their job: closing, inbound leads, or existing customers. One SDR typically generates 10-20 qualified opportunities per month — measure opportunities, response rate, meetings booked, and pipeline value.
Close deals from qualified pipeline: run discovery, demo, negotiate, close, hand off to CSM. Not their job: prospecting (SDR), inbound qualification (MDR), or post-sale management (CSM). Measure revenue closed, win rate, average deal size, and sales cycle length.
Retain and grow accounts: onboard, drive adoption, surface expansion opportunities, prevent churn. Measure net revenue retention, churn rate, expansion revenue, and NPS/CSAT.
The virtuous cycle: SDR generates pipeline → AE closes → CSM retains/grows → happy customer refers (Seeds).
See references/roles.md when defining a new role or org chart — it has full charters, career paths, and hiring profiles for each role.
Outbound prospecting that replaces traditional cold calling, which fails on every front: 1-3% connection rate, gatekeepers, brand damage, no scalability.
1. Build list → 2. Send mass email → 3. Get referral → 4. Call the referral → 5. QualifyDefine your Ideal Customer Profile (company size, industry, tech stack, geography, pain points), then build the list via LinkedIn Sales Navigator, ZoomInfo/Apollo/Clearbit, or industry directories. Target 200-500 accounts per SDR per quarter.
The core innovation: don't email the decision maker — email above them and ask for a referral down. Senior people forward emails, and referrals get 3-5x higher response because the introduction comes from inside the company. The email asks one thing — "who is the right person?" — under 100 words, no pitch, no attachments, no links, easy to forward. Response rate: 9-15% vs. 1-3% for traditional cold emails. For the verbatim template, subject-line open-rate table, and the full Day 1/3/7/14/30 sequence bodies, open references/cold-calling-2.md.
| Day | Action |
|---|---|
| 1 | Send referral email |
| 3 | Follow up if no response |
| 7 | Second follow-up (different angle) |
| 14 | Break-up email ("Should I close your file?") |
| 30 | Re-engage (new trigger event or content) |
The break-up email on Day 14 often draws the highest response in the sequence — people respond to losing the opportunity (scarcity).
| Criteria | Question | Strong Signal | Weak Signal |
|---|---|---|---|
| Authority | Can this person decide? | Decision maker or strong influencer | No buying power |
| Need | Do they have the problem you solve? | Active pain, seeking solutions | "Nice to have" |
| Urgency | When must they solve it? | This quarter, budget allocated | "Someday" |
| Money | Can they afford it? | Budget exists, within range | No budget, too expensive |
Call structure: rapport (2 min) → set agenda ("understand your situation, see if there's a fit") → discovery questions with ANUM built in (10-15 min) → next steps (if qualified, schedule AE demo).
Include account background and ICP match, contact details and role, pain points, ANUM notes, agreed next steps, and competitive intel. SDR introduces AE on a brief 3-way call or email, then drops off.
Ethical boundary: Comply with spam laws (CAN-SPAM, GDPR) and honor opt-outs immediately — including removing a hostile "stop emailing me" from the sequence on the spot, not at the next scheduled touch.
See references/qualification.md when running the ANUM discovery call — it has the full discovery question bank per criterion.
Work backward from the revenue goal:
Revenue Goal ÷ Average Deal Size = Deals Needed
Deals Needed ÷ Win Rate = Opportunities Needed
Opportunities Needed ÷ SDR Conversion = Prospects Needed
Prospects Needed ÷ Response Rate = Emails NeededExample: $1M ARR ÷ $20K deals = 50 deals; ÷ 25% win rate = 200 opportunities; at 10% response rate and 10% response-to-qualified conversion = 20,000 emails ≈ 2-3 SDRs (each sends 300-500/month).
| Metric | Benchmark |
|---|---|
| Emails per SDR per day | 50-100 |
| Response rate | 9-15% |
| Qualified opportunities per SDR per month | 10-20 |
| AE demo-to-close rate | 20-30% |
| Average sales cycle | 30-90 days |
See references/pipeline-math.md when sizing the SDR team to a revenue target — it has the full capacity-planning and revenue-modeling templates.
See references/case-studies.md when you want a worked precedent for standing up or scaling the machine — it walks through Salesforce, HubSpot, and other implementations with starting state, results, and failure modes.
Hire for coachability (the most important trait), curiosity, strong writing, resilience, and organization — experience is optional. Source recent graduates, career changers, and internal transfers. Career path: SDR (6-18 months) → Senior SDR → AE or SDR Manager.
| Phase | Timeline | Expectations |
|---|---|---|
| Training | Weeks 1-2 | Product knowledge, tools, process |
| Shadowing | Weeks 3-4 | Observe experienced SDRs, practice |
| Ramping | Months 2-3 | 50% of quota |
| Full quota | Month 4+ | 100% of quota |
Expect 3-4 months to full productivity.
Base + variable, typically 60/40 or 70/30. Pay variable per qualified opportunity generated, with bonuses for opportunities that close and for exceeding quota.
See references/team-building.md when hiring or building the comp plan — it has interview scorecards, the onboarding curriculum, and detailed compensation structures.
Emails sent per SDR per day, response rate, meetings booked per week, qualified opportunities per month, pipeline value generated.
Revenue closed, win rate, average deal size, sales cycle length, customer acquisition cost (CAC).
Cost per qualified opportunity, SDR:AE ratio (typically 2-3 SDRs per AE), LTV:CAC (target >3:1), payback period.
Cadence: daily activity metrics → weekly pipeline → monthly revenue → quarterly efficiency.
See references/metrics.md when building the sales dashboard — it has KPI definitions, formulas, and dashboard layouts by cadence.
| Mistake | Why It Fails | Fix |
|---|---|---|
| AEs prospecting | Feast-or-famine pipeline | Hire dedicated SDRs |
| Long, pitchy emails | Low response rate | Short, referral-focused emails |
| No ICP definition | Effort wasted on wrong accounts | Define ICP before hiring SDRs |
| Too few SDRs | Not enough pipeline | Work backward from revenue goal |
| No hand-off process | Leads fall through cracks | Standardize SDR→AE handoff |
| Measuring activity, not results | Busy but not productive | Track qualified opportunities, not emails |
Audit any B2B sales process:
| Question | If No | Action |
|---|---|---|
| Are prospecting and closing separated? | SDRs doing both = bottleneck | Create dedicated SDR role |
| Is there a defined outbound process? | Ad-hoc prospecting | Implement Cold Calling 2.0 |
| Can you predict pipeline 3 months out? | Revenue is unpredictable | Build pipeline math model |
| Do you know your lead type mix? | Over-reliance on one source | Balance seeds, nets, spears |
| Is SDR→AE handoff standardized? | Leads lost in transition | Create handoff checklist |
For the complete system:
Aaron Ross built the outbound sales process at Salesforce.com that added $100M+ in recurring revenue, and co-founded Predictable Revenue Inc. His book Predictable Revenue — known as "The Bible of Outbound Sales" — made Cold Calling 2.0 the standard for B2B outbound prospecting.
© wondelai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 8 other files (references) in predictable-revenue of wondelai/skills.
Open the folder on GitHubat commit c172996
Predictable Revenue next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Predictable Revenue this skillwondelai/skills | 2.4k | — | ~3.1k | Automated safety check: Pass | MIT | |
| RevopsAvdLee/RocketSimApp | 806 | 6 repos | ~3.7k | Automated safety check: Pass | Custom licence | |
| Cold EmailLeoYeAI/openclaw-marketing-skills | 1k | 4 repos | ~1.8k | Automated safety check: Pass | Custom licence | |
| B2B Lead Generationminhnv0807/ai-business-skills | 609 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Cold Emailalirezarezvani/claude-skills | 28k | 1 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Cold Email Templates 34swan-gtm/gtm-skills | 172 | — | ~581 | Automated safety check: Pass | MIT |
AvdLee/RocketSimApp
When the user wants help with revenue operations, lead lifecycle management, or marketing-to-sales handoff processes.
LeoYeAI/openclaw-marketing-skills
Write B2B cold emails and follow-up sequences that get replies.
minhnv0807/ai-business-skills
Plans B2B pipeline work from ICP definition and prospecting through lead scoring, outbound sequences, sales assets and MQL to SQL handoff, aiming at qualified pipeline.
alirezarezvani/claude-skills
When the user wants to write, improve, or build a sequence of B2B cold outreach emails to prospects who haven't asked to hear from them.
swan-gtm/gtm-skills
A skill your agent uses when building email campaigns, looking for proven cold email templates, or expanding an outreach playbook.
ericrisco/rsc-harness
A skill your agent uses when writing a cold email or LinkedIn DM to a stranger and its cadence: first-touch copy under a word ceiling, 4-7 step bump sequences, per-inbox volume and warm-up limits…
wondelai/skills
Navigate the technology adoption lifecycle from early adopters to mainstream market.
wondelai/skills
Apply foundational design principles: affordances, signifiers, constraints, feedback, and conceptual models.
wondelai/skills
Run a structured 5-day process to prototype, test, and validate product ideas with real users.
wondelai/skills
Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment).
wondelai/skills
Diagnose and fix retention problems using behavior design (B=MAP).
wondelai/skills
Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation".
Categories
Build a scalable outbound B2B sales machine with specialized roles (SDR, AE, CSM). Predictable Revenue is an agent skill from wondelai/skills. Build a scalable outbound B2B sales machine with specialized roles (SDR, AE, CSM).
Predictable Revenue fits situations like: the user mentions outbound sales; cold Calling 2.0; cold email sequences; sales development.
Run `npx skills add wondelai/skills --skill predictable-revenue -a claude-code`. Or copy the skill folder (predictable-revenue in wondelai/skills) into .claude/skills/predictable-revenue in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wondelai/skills --skill predictable-revenue -a codex`. Or copy the skill folder (predictable-revenue in wondelai/skills) into .agents/skills/predictable-revenue in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wondelai/skills --skill predictable-revenue -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/predictable-revenue, .gemini/skills/predictable-revenue, .github/skills/predictable-revenue and .opencode/skills/predictable-revenue in your project.
SKILL.md names no scripts, command-line tools or credentials: Predictable Revenue is instructions for the agent only.
SKILL.md names 1 domain. As links in the text: amazon.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Predictable Revenue is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.1k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 26k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Predictable Revenue: Revops (AvdLee/RocketSimApp, 806 stars), Cold Email (LeoYeAI/openclaw-marketing-skills, 1k stars), B2B Lead Generation (minhnv0807/ai-business-skills, 609 stars) and Cold Email (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wondelai (a GitHub organization) maintains it in wondelai/skills, which has 2,371 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on September 10, 2026.
Source: wondelai/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.