‹ 首页

multi-program-manager

@affitor · 收录于 2 天前 · 上游提交 1 个月前

Manage and compare multiple affiliate programs as a portfolio. Triggers on: "manage my affiliate programs", "compare my programs", "portfolio overview", "which program should I focus on", "diversify my affiliate income", "program switching", "affiliate portfolio", "program comparison", "revenue allocation", "which programs to drop", "add new programs", "affiliate program strategy".

适合你,如果运营多个联盟赚钱项目,需要统一管理和优化

/ 通过 npx 安装 校验哈希
npx oh-my-skill add affitor/affiliate-skills/multi-program-manager
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- affitor/affiliate-skills/multi-program-manager
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify affitor/affiliate-skills/multi-program-manager
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
576GitHub stars
~1.8K最小装载
~1.8K含声明引用
~2K文本包总量
索引托管

怎么用

商店整理自技能原文 · 版本 ed17ef3 · 表述以原文为准
它做什么

装上后,Claude 会将你的多个联盟营销计划视为投资组合进行管理和比较,生成包含概览、绩效、多元化策略和每周行动计划的仪表板,并给出每个计划是加大投入、维持、优化还是放弃的建议。

什么时候触发

当你说出“manage my affiliate programs”“compare my programs”“portfolio overview”等关键词,或询问该专注于哪个计划、是否放弃某个计划时触发。

装好后可以这样说
Claude会创建组合仪表板并给出建议。
Claude会对比各计划的EPC、收入占比等指标。
Claude根据绩效和风险分析推荐应加大投入的计划。
技能原文 SKILL.md作者撰写 · MIT · ed17ef3

Multi-Program Manager

Manage and compare multiple affiliate programs as a portfolio — overview, performance comparison, diversification strategy, program switching decisions, and revenue allocation. Output is a portfolio dashboard with strategic recommendations and a weekly action plan.

Stage

S7: Automation — Most affiliates either promote too few programs (concentration risk) or too many (effort dilution). This skill applies portfolio thinking to affiliate marketing: analyze your programs like investments, identify which to double down on, maintain, or drop, and allocate your limited time for maximum ROI.

When to Use
  • User manages multiple affiliate programs and wants a strategic overview
  • User asks "which program should I focus on?" or "should I drop this program?"
  • User wants to diversify their affiliate income
  • User says "compare my programs", "portfolio review", "program strategy"
  • User is deciding whether to add or remove programs
  • Chaining from S6.3 (performance-report): take performance data and make strategic decisions
Input Schema
programs:
  - name: string               # REQUIRED — program name
    affiliate_url: string      # OPTIONAL — affiliate link
    reward_value: string       # OPTIONAL — commission (e.g., "30% recurring")
    reward_type: string        # OPTIONAL — "cps_recurring" | "cps_one_time" | "cpl" | "cpc"
    monthly_revenue: number    # OPTIONAL — avg monthly revenue ($)
    monthly_clicks: number     # OPTIONAL — avg monthly clicks
    niche: string              # OPTIONAL — product category
    status: string             # OPTIONAL — "active" | "paused" | "new" | "considering"

goal: string                   # OPTIONAL — "maximize_revenue" | "diversify"
                               # | "reduce_risk" | "find_gaps"
                               # Default: "maximize_revenue"

budget_hours: number           # OPTIONAL — weekly hours available for content
                               # Default: 10

Chaining context: If S1 program research or S6.3 performance data exists in conversation, pull program details and metrics automatically.

Workflow
Step 1: Build Portfolio Overview

Compile all programs into a dashboard:

  • Program name, niche, commission type, commission value
  • Monthly revenue, clicks, EPC
  • Status (active/paused/new)
  • Revenue share (% of total)
Step 2: Calculate Per-Program Metrics

For each program with data:

  • EPC: revenue / clicks
  • Revenue Share: program revenue / total revenue × 100
  • Effort-to-Revenue Ratio: estimated hours spent / revenue generated
  • Commission Quality Score: recurring > one-time > per-lead > per-click
Step 3: Apply Portfolio Analysis

Concentration Risk:

  • If top program > 50% of revenue → HIGH RISK
  • If top 2 programs > 80% → MODERATE RISK
  • If no program > 30% → WELL DIVERSIFIED

Niche Overlap:

  • Multiple programs in same niche → competing for same audience
  • Different niches → healthy diversification

Revenue Stability:

  • Recurring commissions → stable
  • One-time commissions → volatile (need constant new traffic)
Step 4: Generate Recommendations

For each program, assign an action:

  • Double Down: High EPC, room to grow → create more content, scale traffic
  • Maintain: Solid performer, no changes needed → keep existing content fresh
  • Optimize: High traffic but low conversion → improve CTAs, landing pages, test variants
  • Phase Out: Low EPC, low growth potential → redirect effort to better programs
  • Add: Gap identified → research new programs with S1
Step 5: Create Action Plan

Based on budget_hours, allocate weekly time:

  • Double-down programs get 50% of time
  • Maintain programs get 20%
  • Optimize programs get 20%
  • New program research gets 10%

Provide specific weekly tasks tied to Affitor skills.

Step 6: Self-Validation

Before presenting output, verify:

  • [ ] Revenue share percentages sum to ~100%
  • [ ] EPC calculations correct (revenue ÷ clicks per program)
  • [ ] Concentration risk accurate (flag if top program >50% of revenue)
  • [ ] Actions match performance: double_down (Star), maintain (Cash Cow), optimize (Question Mark), phase_out (Dog)
  • [ ] Weekly time allocation sums to user's stated hours budget

If any check fails, fix the output before delivering. Do not flag the checklist to the user — just ensure the output passes.

Output Schema
output_schema_version: "1.0.0"  # Semver — bump major on breaking changes
portfolio:
  total_programs: number
  active_programs: number
  total_monthly_revenue: number
  concentration_risk: string   # "high" | "moderate" | "low"
  niche_diversification: string # "good" | "overlapping" | "single_niche"
  revenue_stability: string    # "stable" | "moderate" | "volatile"

programs:
  - name: string
    niche: string
    reward_type: string
    monthly_revenue: number
    epc: number
    revenue_share: number
    action: string             # "double_down" | "maintain" | "optimize" | "phase_out"
    reason: string

recommendations:
  - action: string
    program: string
    skill: string              # which Affitor skill to use
    task: string               # specific task
    priority: number           # 1 = highest

weekly_plan:
  total_hours: number
  allocation:
    - program: string
      hours: number
      tasks: string[]
Output Format
  1. Portfolio Dashboard — table with all programs, revenue, EPC, revenue share
  2. Portfolio Health — concentration risk, diversification, stability assessment
  3. Program Scorecards — per-program action (double down / maintain / optimize / phase out) with reason
  4. Strategic Recommendations — prioritized list of actions with Affitor skill references
  5. Weekly Action Plan — hour-by-hour allocation with specific tasks
Error Handling
  • Only one program: "You have a single program. That's 100% concentration risk. I'll analyze it and recommend 2-3 complementary programs using S1 (affiliate-program-search)."
  • No revenue data: "Without revenue data, I'll analyze based on commission structure and niche overlap. For deeper analysis, run S6.3 (performance-report) first to get your numbers."
  • All programs in same niche: "All your programs are in [niche]. You're diversified by product but not by market. If [niche] declines, all your income is at risk. Consider adding programs in adjacent niches."
Examples
Example 1: Portfolio with clear winner

User: "I promote HeyGen ($450/mo), Semrush ($320/mo), Notion ($125/mo), Canva ($80/mo). Which should I focus on?" Action: HeyGen is the star (46% revenue, likely highest EPC). Recommend: Double down on HeyGen (more blog content, S7 content-repurposer). Maintain Semrush. Optimize Notion (high conversion rate potential). Evaluate Canva (low revenue, is it worth the effort?). Weekly plan: 5h HeyGen, 2h Semrush, 2h Notion, 1h research.

Example 2: Diversification analysis

User: "I make $2K/month from 3 SaaS tools. How do I reduce risk?" Action: All income from one niche (SaaS) = moderate risk. Recommend: Add 1-2 programs in adjacent niches (e.g., online courses, hosting). Check commission types — if all one-time, recommend adding recurring programs. Use S1 to research programs in new niches.

Example 3: Program switching decision

User: "Should I drop Canva ($80/mo, 500 clicks) and replace it with Jasper?" Action: Canva EPC = $0.16 (low). Calculate opportunity cost: 500 clicks redirected to a $0.50+ EPC program = $250/mo potential. Research Jasper commission (likely $100+ per sale). Recommend: Yes, switch. Use S1 to evaluate Jasper, then S3 for a comparison blog post.

References
  • shared/references/affiliate-glossary.md — Portfolio and commission terminology. Referenced in Step 2.
  • shared/references/flywheel-connections.md — master flywheel connection map
Flywheel Connections
Feeds Into
  • commission-calculator (S1) — managed programs for portfolio calculation
  • funnel-planner (S8) — portfolio data for funnel planning
Fed By
  • affiliate-program-search (S1) — new programs to add to portfolio
  • conversion-tracker (S6) — performance data per program
  • performance-report (S6) — portfolio performance trends
Feedback Loop
  • performance-report (S6) reveals underperforming programs → recommend swaps or investment reallocation
chain_metadata:
  skill_slug: "multi-program-manager"
  stage: "automation"
  timestamp: string
  suggested_next:
    - "commission-calculator"
    - "performance-report"
    - "affiliate-program-search"
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

评论

登录即可评论;带「已验证安装」的,是发布者名下有本店的安装或持有记录。