🎁 Get the FREE AI Skills Starter GuideSubscribe →
BytesAgainBytesAgain
🦀 ClawHub

ConvoYield

by @jcools1977

Conversational Yield Optimization Engine — treats every bot conversation as a yield-bearing financial instrument. Five zero-cost engines detect sentiment arb...

Versionv1.0.0
Downloads697
TERMINAL
clawhub install opencrawl

📖 About This Skill


name: convoyield description: > Conversational Yield Optimization Engine — treats every bot conversation as a yield-bearing financial instrument. Five zero-cost engines detect sentiment arbitrage, micro-conversions, engagement momentum, dollar-value yield forecasts, and optimal strategic plays in real-time. No external APIs. No dependencies. Pure behavioral economics applied to conversations. version: 1.0.0 author: J. DeVere Cooley homepage: https://github.com/jcools1977/Opencrawl metadata: openclaw: emoji: "📈" requires: bins: - python os: ["macos", "linux", "windows"] tags: - revenue - optimization - behavioral-economics - zero-cost - sentiment - conversion platforms: ["discord", "telegram", "whatsapp", "slack", "webchat"] cost: free requires_api: false

ConvoYield — Conversational Yield Optimization Engine

> "Every conversation is a financial instrument. ConvoYield tells you what it's worth."

What It Does

ConvoYield gives any bot a real-time revenue intelligence layer. On every user message, five engines run in parallel and produce:

  • Sentiment Arbitrage — Detects emotional gaps that create revenue opportunities
  • (frustration capture, competitor displacement, excitement amplification, etc.)
  • Micro-Conversion Tracking — Finds 12 types of hidden value in every message
  • (email captures, budget reveals, pain points, referral signals, etc.)
  • Momentum Scoring — Measures whether the conversation is gaining or losing steam
  • Yield Forecasting — Predicts the total dollar value of the conversation in real-time
  • Play Calling — Recommends from a 20-play behavioral economics playbook
  • (anchoring, loss framing, social proof, empathy bridges, urgency closes, etc.)

    Zero Cost Guarantee

  • Zero external dependencies — Pure Python standard library
  • Zero API calls — All analysis runs locally via pattern matching and heuristics
  • Zero tokens consumed — Does not call any LLM API
  • Zero infrastructurepip install and go
  • <1ms per message — Adds no latency to your bot
  • Quick Start

    from convoyield import ConvoYield

    engine = ConvoYield(base_conversation_value=50.0)

    Process each user message

    result = engine.process_user_message("I'm frustrated with Salesforce, it's way too expensive")

    print(result.recommended_play) # "competitor_displacement" print(result.estimated_yield) # 89.50 print(result.recommended_tone) # "empathetic" print(result.top_arbitrage.type) # "frustration_capture" print(result.risk_level) # 0.21

    Record bot response for full state tracking

    engine.record_bot_response("I hear you. What specifically isn't working?")

    Next message — yield COMPOUNDS

    result = engine.process_user_message("The reporting is terrible and costs $500/month") print(result.estimated_yield) # 142.30 — value is growing!

    The Five Engines

    1. Sentiment Arbitrage Engine

    Detects 7 arbitrage patterns via lexicon-based sentiment scoring tuned for commercial conversations:

    | Pattern | What It Detects | Value Signal | |---------|----------------|--------------| | competitor_displacement | Frustration with a named competitor | $45+ | | frustration_capture | General frustration with current solution | $35+ | | excitement_amplification | User showing enthusiasm | $25+ | | uncertainty_anchoring | User unsure, needs guidance | $20+ | | urgency_premium | Time pressure detected | $30+ | | social_proof_hunger | User seeking validation | $15+ | | budget_value_stack | User discussing budget/cost | $40+ |

    2. Micro-Conversion Tracker

    Detects 12 micro-conversion opportunities between "hello" and "purchase":

  • Email/phone capture opportunities
  • Budget and timeline reveals
  • Team size and need statements
  • Competitor mentions and feature requests
  • Referral and testimonial signals
  • Pain point articulations
  • Each micro-conversion has an estimated dollar value ($0.50-$15).

    3. Momentum Scorer

    Scores engagement momentum (-1.0 to +1.0) using four signals:

  • Message length trend (expanding = engaged)
  • Question frequency trend (asking = curious)
  • Emotional intensity trend (feeling = invested)
  • Vocabulary richness trend (elaborating = committed)
  • Labels: surging | accelerating | stable | declining | hemorrhaging

    4. Yield Forecaster

    Combines all signals to predict a dollar value for the conversation using:

  • Phase multipliers (OPENING → DISCOVERY → ENGAGEMENT → NEGOTIATION → CLOSING)
  • Micro-conversion portfolio value
  • Arbitrage opportunity value
  • Engagement and momentum premiums
  • Risk assessment (0.0-1.0)
  • 5. Play Caller

    Recommends from 20 plays inspired by behavioral economics:

    warm_handshake · pattern_interrupt · deep_probe · empathy_bridge · value_stack · competitor_displacement · social_proof_deploy · dopamine_ride · anchoring · loss_framing · budget_reframe · choice_architecture · assumptive_close · urgency_close · soft_close · momentum_recovery · save_attempt · upsell_bridge · referral_harvest · objection_reframe

    Integration

    Works with any bot framework — hook into your message handler:

    from convoyield import ConvoYield

    engine = ConvoYield()

    def on_user_message(text, conversation_id): result = engine.process_user_message(text)

    # Shape your bot's response using: # result.recommended_play → WHAT strategy to use # result.recommended_tone → HOW to say it # result.arbitrage_opportunities → WHERE the money is # result.micro_conversions → WHAT value to capture # result.risk_level → HOW careful to be # result.estimated_yield → HOW much is at stake

    return generate_response(text, result)

    Premium Playbooks

    Four industry-specific playbook packs available:

    | Playbook | Plays | Price | |----------|-------|-------| | SaaS Sales Mastery | 25 | $49/mo | | E-Commerce Revenue Max | 22 | $39/mo | | Real Estate Closer | 20 | $79/mo | | Healthcare Engagement | 18 | $99/mo |

    Revenue Model

    ConvoYield is free and open source. Revenue comes from:

    1. Premium playbooks — Industry-specific play packs ($39-99/mo) 2. Cloud analytics — Dashboard and yield tracking ($0/49/299/mo tiers) 3. Enterprise — Custom playbooks, webhooks, white-label ($299/mo)

    Architecture

    convoyield/
    ├── orchestrator.py              # Main ConvoYield engine
    ├── engines/
    │   ├── sentiment_arbitrage.py   # 7 arbitrage pattern detectors
    │   ├── micro_conversion.py      # 12 micro-conversion trackers
    │   ├── momentum.py              # 4-signal engagement scorer
    │   ├── yield_forecaster.py      # Dollar-value yield prediction
    │   └── play_caller.py           # 20-play behavioral economics playbook
    ├── models/
    │   ├── conversation.py          # ConversationState, Turn, Phase
    │   └── yield_result.py          # YieldResult, ArbitrageOpportunity
    ├── playbooks/                   # 4 premium industry packs (85 plays)
    ├── coin/                        # ConvoCoin — Proof-of-Yield blockchain
    └── cloud/                       # Telemetry client for analytics
    

    Tests

    40 tests across 7 suites — all passing:

    python -m pytest tests/ -v
    

    💡 Examples

    from convoyield import ConvoYield

    engine = ConvoYield(base_conversation_value=50.0)

    Process each user message

    result = engine.process_user_message("I'm frustrated with Salesforce, it's way too expensive")

    print(result.recommended_play) # "competitor_displacement" print(result.estimated_yield) # 89.50 print(result.recommended_tone) # "empathetic" print(result.top_arbitrage.type) # "frustration_capture" print(result.risk_level) # 0.21

    Record bot response for full state tracking

    engine.record_bot_response("I hear you. What specifically isn't working?")

    Next message — yield COMPOUNDS

    result = engine.process_user_message("The reporting is terrible and costs $500/month") print(result.estimated_yield) # 142.30 — value is growing!