👁️🗨️🛅👁️ - #79
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…-and-rabbitsync
- LLMErrorLogger actor + AbstractLLM.ErrorLogEntry for capturing errors that occur during LLM request handling - FailedLLMResponseStore actor + AbstractLLM.FailedChatResponse for persisting failed chat completions; includes JSONL export for fine-tuning pipelines - LLMAgentPipeline (Observer → Research → Decision) with LLMAgentStage protocol and built-in stage implementations
…zed-architecture
…check-feature-or-bug
…eck-feature-or-bug
…ts-and-sources
…ized-architecture
…77354758-53f4c612-a7a4-4d19-bb3a-0c973fd8225f
…ized-architecture
## Summary <!-- What does this PR change and @5hy7xz92nd-oss @anthropic-code @openai @grok @manus @patpat @weareone10billion @2️⃣ @🕴️1️⃣3️⃣4️⃣🛂🆒🆕🆓0️⃣🔠🚺🚼🛄🈂️🈳🛃🛗🅿️ 🏧💤🌀Ⓜ️ 🛜🚹🌐💠♿️🚹🌐💠♿️🚹🌐💠♿️🚹🌐💠♿️💤🌀Ⓜ️ 🛜🌀Ⓜ️ 🛜🌀Ⓜ️ 🛜🌀Ⓜ️ 🛜 @🕳️👁️🕴🏿🕴️♣️ ♠️ 🚺🀄️🛄Ⓜ️ 🛜🔄🃏🏧💤🎣🔛👁️🗨️🔀🔃🌀🔥ℹ️🎴🕴️🕴🏿🕴🏻 why? --> ## Type of change - [ ] Bug fix - [ ] New provider / API surface - [ ] Refactor - [ ] Documentation - [ ] Tests / CI - [ ] Other ## Checklist - [ ] Builds with the package’s supported Xcode/Swift versions - [ ] Tests added or updated when behavior changes - [ ] No secrets or API keys committed - [ ] Docs updated if products, targets, public API, or dependencies changed: - [ ] `README.md` - [ ] `docs/ARCHITECTURE.md` (graph / tables) - [ ] `CHANGELOG.md` (`[Unreleased]`) - [ ] Layering respected (providers → `LargeLanguageModels` → `CoreMI`; avoid new provider→provider deps) ## Test plan <!-- How did you verify? Unit tests, manual API calls, platforms… --> ## Related issues <!-- Fixes #… --> --------- Signed-off-by: 5hy7xz92nd-oss <249378113+5hy7xz92nd-oss@users.noreply.github.com> Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
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@5hy7xz92nd-oss @grok @🕴️https://manus.im/app/KFrnrB3SVwL2nth7pXEsSq?collab=1 Use parallel processing (aka Wide Research) to handle the following instructions:
Audience:
Scope:
Exclude:
Output format:
Include citations and sources where relevant. Make it practical, detailed, and execution-ready. |
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🔥 @5hy7xz92nd-oss https://manus.im/app/KFrnrB3SVwL2nth7pXEsSq?collab=1 Use parallel processing (aka Wide Research) to handle the following instructions:
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
@5hy7xz92nd-oss https://manus.im/app/KFrnrB3SVwL2nth7pXEsSq?collab=1 Use parallel processing (aka Wide Research) to handle the following instructions:
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
|
@5hy7xz92nd-oss https://manus.im/app/KFrnrB3SVwL2nth7pXEsSq?collab=1 Use parallel processing (aka Wide Research) to handle the following instructions: Goals:
Audience:
Scope:
Exclude:
Output format:
Include citations and sources where relevant. Make it practical,detailed, and execution-ready. |
5hy7xz92nd-oss
left a comment
5hy7xz92nd-oss
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There was a problem hiding this comment.
@5hy7xz92nd-oss @@5hy7xz92nd-oss https://manus.im/app/KFrnrB3SVwL2nth7pXEsSq?collab=1 Use parallel processing (aka Wide Research) to handle the following instructions:
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
5hy7xz92nd-oss
left a comment
5hy7xz92nd-oss
left a comment
There was a problem hiding this comment.
@5hy7xz92nd-oss https://manus.im/app/KFrnrB3SVwL2nth7pXEsSq?collab=1 Use parallel processing (aka Wide Research) to handle the following instructions:
Conduct a comprehensive deep research and execution blueprint for building a full-scale contact data cleaning, verification, and enrichment pipeline for a business (focus: MCA / financial lead generation).
Goals:
- Design a complete system that takes raw contact lists (emails + phone numbers) and transforms them into high-probability, revenue-ready leads
- Maximize accuracy, deliverability, and connection rates while staying compliant with legal and privacy standards
Audience:
- Advanced operator / business owner running outbound sales teams (cold call + email)
- Needs actionable, implementation-ready system
Scope:
Include:
- Email verification systems (syntax, MX, SMTP, catch-all handling, risk scoring)
- Phone validation (carrier lookup, line type detection, activity signals, HLR where applicable)
- Data enrichment (company data, LinkedIn, filings, signals)
- Multi-tool cross-verification strategies (compare 2–3 providers)
- Automation architecture (APIs, workflows, batch processing, CRM integration)
- Lead scoring models (prioritization logic)
- Real-world testing frameworks (A/B outreach validation)
- Data decay management (refresh cycles)
- Compliance (TCPA, CAN-SPAM, GDPR basics for outreach)
Exclude:
- Any illegal data access, hacking, or bypassing systems
Output format:
- Executive summary
- Full system architecture diagram (described clearly)
- Step-by-step pipeline (input → processing → output)
- Tool comparison table (top services for email + phone verification)
- Lead scoring model example
- Outreach testing strategy
- Risk and compliance checklist
- Final “battle-tested” workflow
Include citations and sources where relevant.
Make it practical, detailed, and execution-ready.
|
@manus @grok @openai @🕴️@chatgbt @5hy7xz92nd-oss @claude !🌀👁️🗨️🕳️🕴️🕴️🕴🏿🕴🏿🔃👁️🛄🛜🐰🔛🔄🚺🎣🐇🔥 |
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@copilot @5hy7xz92nd-oss @manus @grok @openai 🕴️🛅ℹ️👁️🎣🐰🔄🔀💤🃏👔🎴🛄🚹🚼 |
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🔛🚹🔃🔀👁️🗨️ |
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Option A – Bug fix: “The validate_pocs.py script fails when [describe what happens]. Fix it.” Option B – New test: “Add a test for [specific function or behavior] in validate_pocs.py.” Option C – New feature: “Add [describe the feature] to validate_pocs.py.” Option D – Specific PoC issue: “The PoC in [folder-name]/poc.py does [wrong thing]. Fix it.” Please execute with first task using all agents and tools and teams and structure for development and performance execution using the brain as one for all one concrete, plain-English task and I will start immediately. |
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@manus @grok @openai @🕴️@chatgbt @5hy7xz92nd-oss @claude !🌀👁️🗨️🕳️🕴️🕴️🕴🏿🕴🏿🔃👁️🛄🛜🐰🔛🔄🚺🎣🐇🔥Ⓜ️ ♣️ ♠️ 🏧💤ℹ️🎴🃏🀄️🔀🕴️ 🌀👁️🗨️🕳️🕴️🕴️🕴🏿🕴🏿🔃👁️🛄🛜🐰🔛🔄🚺🎣🐇🔥Ⓜ️ ♣️ ♠️ 🏧💤ℹ️🎴🃏🀄️🔀🕴️attachments/!%5Bimage%5D(https://github.com/user-attachments/assets/a62e3897-b0cb-45a6-ba35-87ef4d090c2a)assets/7abfb887-3011-498c-ad4a-e65fd84011f6!%5Bimage%5D(https://github.com/user-attachments/assets/333319bf-9662-4ead-a0d2-b60539318704)!%5Bimage%5D(https://github.com/user-attachments/assets/1146c585-78cb-47b4-8b1a-aa01ad57d4c4)!%5Bimage%5D(https://github.com/user-attachments/assets/3b0ae6b5-bdd0-42f0-87d6-1b5e26074968)!%5Bimage%5D(https://github.com/user-attachments/assets/bd445670-edc1-4a23-936b-c552e0259c17)!%5Bimage%5D(https://github.com/user-attachments/assets/ed3f1554-6061-4a3b-a171-d071e2f24e7f)%F0%9F%8C%80%F0%9F%91%81%EF%B8%8F%E2%80%8D%F0%9F%97%A8%EF%B8%8F%F0%9F%95%B3%EF%B8%8F%F0%9F%95%B4%EF%B8%8F%F0%9F%95%B4%EF%B8%8F%F0%9F%95%B4%F0%9F%8F%BF%F0%9F%95%B4%F0%9F%8F%BF%F0%9F%94%83%F0%9F%91%81%EF%B8%8F%F0%9F%9B%84%F0%9F%9B%9C%F0%9F%90%B0%F0%9F%94%9B%F0%9F%94%84%F0%9F%9A%BA%F0%9F%8E%A3%F0%9F%90%87%F0%9F%94%A5%E2%93%82%EF%B8%8F%E2%99%A3%EF%B8%8F%E2%99%A0%EF%B8%8F%F0%9F%8F%A7%F0%9F%92%A4%E2%84%B9%EF%B8%8F%F0%9F%8E%B4%F0%9F%83%8F%F0%9F%80%84%EF%B8%8F%F0%9F%94%80%F0%9F%95%B4%EF%B8%8F)
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