userType: external

gitBranch: claude/dreamy-dirac

slug: gentle-coalescing-thompson

type: user

role: user

content:
Your task is to create a detailed summary of the conversation so far, paying close attention to the user's explicit requests and your previous actions.
This summary should be thorough in capturing technical details, code patterns, and architectural decisions that would be essential for continuing development work without losing context.

Before providing your final summary, wrap your analysis in <analysis> tags to organize your thoughts and ensure you've covered all necessary points. In your analysis process:

1. Chronologically analyze each message and section of the conversation. For each section thoroughly identify:
   - The user's explicit requests and intents
   - Your approach to addressing the user's requests
   - Key decisions, technical concepts and code patterns
   - Specific details like:
     - file names
     - full code snippets
     - function signatures
     - file edits
  - Errors that you ran into and how you fixed them
  - Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
2. Double-check for technical accuracy and completeness, addressing each required element thoroughly.

Your summary should include the following sections:

1. Primary Request and Intent: Capture all of the user's explicit requests and intents in detail
2. Key Technical Concepts: List all important technical concepts, technologies, and frameworks discussed.
3. Files and Code Sections: Enumerate specific files and code sections examined, modified, or created. Pay special attention to the most recent messages and include full code snippets where applicable and include a summary of why this file read or edit is important.
4. Errors and fixes: List all errors that you ran into, and how you fixed them. Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
5. Problem Solving: Document problems solved and any ongoing troubleshooting efforts.
6. All user messages: List ALL user messages that are not tool results. These are critical for understanding the users' feedback and changing intent.
6. Pending Tasks: Outline any pending tasks that you have explicitly been asked to work on.
7. Current Work: Describe in detail precisely what was being worked on immediately before this summary request, paying special attention to the most recent messages from both user and assistant. Include file names and code snippets where applicable.
8. Optional Next Step: List the next step that you will take that is related to the most recent work you were doing. IMPORTANT: ensure that this step is DIRECTLY in line with the user's most recent explicit requests, and the task you were working on immediately before this summary request. If your last task was concluded, then only list next steps if they are explicitly in line with the users request. Do not start on tangential requests or really old requests that were already completed without confirming with the user first.
                       If there is a next step, include direct quotes from the most recent conversation showing exactly what task you were working on and where you left off. This should be verbatim to ensure there's no drift in task interpretation.

Here's an example of how your output should be structured:

<example>
<analysis>
[Your thought process, ensuring all points are covered thoroughly and accurately]
</analysis>

<summary>
1. Primary Request and Intent:
   [Detailed description]

2. Key Technical Concepts:
   - [Concept 1]
   - [Concept 2]
   - [...]

3. Files and Code Sections:
   - [File Name 1]
      - [Summary of why this file is important]
      - [Summary of the changes made to this file, if any]
      - [Important Code Snippet]
   - [File Name 2]
      - [Important Code Snippet]
   - [...]

4. Errors and fixes:
    - [Detailed description of error 1]:
      - [How you fixed the error]
      - [User feedback on the error if any]
    - [...]

5. Problem Solving:
   [Description of solved problems and ongoing troubleshooting]

6. All user messages:
    - [Detailed non tool use user message]
    - [...]

7. Pending Tasks:
   - [Task 1]
   - [Task 2]
   - [...]

8. Current Work:
   [Precise description of current work]

9. Optional Next Step:
   [Optional Next step to take]

</summary>
</example>

Please provide your summary based on the conversation so far, following this structure and ensuring precision and thoroughness in your response.

There may be additional summarization instructions provided in the included context. If so, remember to follow these instructions when creating the above summary. Examples of instructions include:
<example>
## Compact Instructions
When summarizing the conversation focus on typescript code changes and also remember the mistakes you made and how you fixed them.
</example>

<example>
# Summary instructions
When you are using compact - please focus on test output and code changes. Include file reads verbatim.
</example>

Additional Instructions:
{}

IMPORTANT: Do NOT use any tools. You MUST respond with ONLY the <summary>...</summary> block as your text output.


type: message

role: assistant

type: text

text:
<analysis>
Let me analyze the conversation chronologically and thoroughly.

**The User's Request:**
The user (operating as "Agent 2 — GHL Module Activator for TradiesVoice") was given a detailed task to:
1. Audit existing GHL module deploy scripts in `E:\genesis-system\GHL_MODULES\`
2. Create a unified GHL App Pipeline specification (`GHL_APP_PIPELINE_SPEC.md`)
3. Create a unified deploy runner (`ghl_pipeline_runner.py`)
4. Create a credentials checklist (`GHL_CREDENTIALS_CHECKLIST.md`)

**Files Read (Audit Phase):**
The assistant read a large number of files:

1. `E:\genesis-system\GHL_MODULES\` directory listing
2. `E:\genesis-system\TRADIES\` directory listing
3. `E:\genesis-system\GHL_MODULES\mctb_widget\ghl_mctb_deploy.py` (466 lines) — MCTB deploy script
4. `E:\genesis-system\GHL_MODULES\review_generator\ghl_api_deploy.py` (510 lines) — Review Generator deploy script
5. `E:\genesis-system\GHL_MODULES\widget\tradie_widget.html` (1112 lines) — Smart Widget
6. `E:\genesis-system\GHL_MODULES\mctb_widget\MCTB_SNAPSHOT_SPEC.md` (271 lines)
7. `E:\genesis-system\GHL_MODULES\review_generator\SNAPSHOT_SPEC.md` (384 lines)
8. `E:\genesis-system\GHL_MODULES\widget\WIDGET_EMBED_GUIDE.md` (334 lines)
9. `E:\genesis-system\GHL_MODULES\GHL_MODULES_OVERVIEW.md` (303 lines)
10. `E:\genesis-system\GHL_MODULES\mctb_widget\widget_per_client_provisioning.md` (599 lines)
11. `E:\genesis-system\GHL_MODULES\review_generator\REVIEW_GENERATOR_WORKFLOW.md` (338 lines)
12. `E:\genesis-system\GHL_MODULES\mctb_widget\WIDGET_DEPLOY_SPEC.md` (307 lines)
13. `E:\genesis-system\TRADIES\TRADIESVOICE_LAUNCH_TODAY_PRD.md` (first 100 lines)

**Files Created:**
1. `E:\genesis-system\TRADIES\GHL_APP_PIPELINE_SPEC.md` (474 lines)
2. `E:\genesis-system\TRADIES\ghl_pipeline_runner.py` (753 lines)
3. `E:\genesis-system\TRADIES\GHL_CREDENTIALS_CHECKLIST.md` (277 lines)

**Key Technical Findings from the Audit:**

MCTB deploy script (`ghl_mctb_deploy.py`):
- Uses `GHL_AGENCY_API_KEY` env var
- API base: `https://services.leadconnectorhq.com`
- API version: `2021-07-28`
- Deploys: 2 custom fields (booking_link, preferred_callback_time), Lead Recovery pipeline (4 stages), 3 SMS templates, 4 sub-account custom values
- Cannot deploy workflows via API (GHL v2 limitation) — prints manual instructions instead

Review Generator deploy script (`ghl_api_deploy.py`):
- Uses `GHL_API_KEY` env var (INCONSISTENCY — different from MCTB script)
- Deploys: 4 custom fields (google_review_link, technician_name, job_type, review_rating), Reputation Tracker pipeline (3 stages), 2 SMS templates, 2 custom values
- Cannot deploy workflows via API — same limitation

Smart Widget (`tradie_widget.html`):
- Self-contained 1112-line HTML/CSS/JS file
- Uses `RAD_CONFIG` block for all client configuration
- Three tabs: Book a Job, Chat with Us (Telnyx WebRTC), Call Now
- Hardcoded demo Telnyx agent ID: `assistant-9c42d3ce-e05a-4e34-8083-c91081917637`
- Sends booking form webhook payload to GHL

`widget_per_client_provisioning.md` contains full Python code for:
- Creating Telnyx AI Assistant per client
- Uploading knowledge base
- Provisioning AU phone numbers
- Storing assistant ID in GHL

**Key Gaps Found:**
1. GHL API v2 cannot create complex workflows — requires snapshot import or manual build
2. `ghl_api_deploy.py` uses `GHL_API_KEY`, `ghl_mctb_deploy.py` uses `GHL_AGENCY_API_KEY` — inconsistent
3. `widget_per_client_provisioning.md` has full Python code as documentation but no `.py` runner
4. App 6 (Review Display Widget) has zero existing implementation
5. No GHL sub-account creation script exists
6. Rating page URL placeholder in Review Generator templates requires manual update after funnel publish

**Pipeline Runner Design:**
- Accepts `--client-data` JSON or inline `--sub-account-id`, `--business-name` etc.
- Plan shortcuts: website, starter_bundle, growth_bundle, full_suite
- `deploy_mctb()` calls existing `ghl_mctb_deploy.py` via `subprocess.run()`
- `deploy_review_generator()` calls existing `ghl_api_deploy.py` via `subprocess.run()`
- Other deployers are stubs with manual step instructions
- Full logging to console + timestamped log file
- `DeploymentResult` class tracks success/failure/notes/manual steps per module
- Normalises `GHL_API_KEY` / `GHL_AGENCY_API_KEY` inconsistency

No errors encountered. All three files were created successfully.
</analysis>

<summary>
1. Primary Request and Intent:
   The user issued a detailed agent task to act as "Agent 2 — GHL Module Activator for TradiesVoice" with two phases:

   **Phase 1 — Audit Existing Modules:**
   Read and fully understand all existing GHL module deploy scripts and specifications in `E:\genesis-system\GHL_MODULES\`, including: `ghl_mctb_deploy.py`, `ghl_api_deploy.py`, `tradie_widget.html`, `MCTB_SNAPSHOT_SPEC.md`, `SNAPSHOT_SPEC.md`, `WIDGET_EMBED_GUIDE.md`, `WIDGET_DEPLOY_SPEC.md`, `widget_per_client_provisioning.md`, `REVIEW_GENERATOR_WORKFLOW.md`, and `GHL_MODULES_OVERVIEW.md`.

   **Phase 2 — Create Three Output Files:**
   - `E:\genesis-system\TRADIES\GHL_APP_PIPELINE_SPEC.md` — Full specification for all 6 TradiesVoice apps as deployable GHL modules, based on what the scripts actually do (not assumptions).
   - `E:\genesis-system\TRADIES\ghl_pipeline_runner.py` — Unified Python deploy runner that accepts `--client-data` JSON and `--plan` or `--apps` flags, calls existing deploy scripts, and logs results.
   - `E:\genesis-system\TRADIES\GHL_CREDENTIALS_CHECKLIST.md` — All credentials Kinan needs to activate the pipeline.

2. Key Technical Concepts:
   - GoHighLevel (GHL) API v2 (`https://services.leadconnectorhq.com`, version header `2021-07-28`)
   - GHL sub-account provisioning, custom fields, pipelines, SMS templates, custom values
   - GHL API v2 limitation: complex automation workflows cannot be created programmatically — must use snapshot import or manual build
   - GHL snapshots (Extendly Small Business Snapshot) for bulk asset apply
   - Telnyx AI Assistant API (`https://api.telnyx.com/v2/ai/assistants`) for voice agent provisioning
   - Telnyx `<telnyx-ai-agent>` web component (official WebRTC voice widget)
   - Telnyx per-client assistant provisioning with knowledge base upload and AU phone number ordering
   - Smart Widget (`tradie_widget.html`) — self-contained HTML/CSS/JS, three-tab interface (Book / Chat / Call)
   - MCTB (Missed Call Text Back) — GHL automation triggered by native Missed Call event, 30s → SMS → 4hr follow-up
   - Reputation Rocket (Review Generator) — 3-workflow GHL automation with 5-star filter and 48hr follow-up
   - n8n automation webhooks as bridge between external job management systems (ServiceM8, Tradify) and GHL
   - Stripe subscription management (already live from Sunaiva deployment)
   - Python `subprocess.run()` for calling existing deploy scripts from the unified runner
   - `DeploymentResult` class pattern for per-module tracking
   - Environment variable normalisation (`GHL_API_KEY` vs `GHL_AGENCY_API_KEY`)

3. Files and Code Sections:

   - **`E:\genesis-system\GHL_MODULES\mctb_widget\ghl_mctb_deploy.py`** (466 lines, READ)
     - Deploys MCTB module to a GHL sub-account via API v2
     - Uses `GHL_AGENCY_API_KEY` env var
     - 5 steps: (1) 2 custom fields — `contact.booking_link`, `contact.preferred_callback_time`; (2) "Lead Recovery" pipeline — 4 stages (Missed Call Follow Up / Engaged via SMS / Booked / Lost); (3) 3 SMS templates via `/locations/{id}/customResponses`; (4) 4 custom values (business_name, team_name, booking_link, owner_phone); (5) Workflow manual instructions printed (API cannot create workflows)
     - Key CLI args: `--sub-account-id`, `--business-name`, `--booking-link`, `--owner-phone`
     - Handles 422/409 on custom values as soft warnings (idempotent)

   - **`E:\genesis-system\GHL_MODULES\review_generator\ghl_api_deploy.py`** (510 lines, READ)
     - Deploys Review Generator (Reputation Rocket) module to a GHL sub-account
     - Uses `GHL_API_KEY` env var (inconsistency vs MCTB script)
     - 4 steps: (1) 4 custom fields — `google_review_link`, `technician_name`, `job_type`, `review_rating`; (2) "Reputation Tracker" pipeline — 3 stages (Review Requested / Negative Feedback / Review Posted); (3) 2 SMS templates via `/locations/{id}/templates` (different endpoint than MCTB); (4) 2 custom values (Default Google Review Link, Business Name)
     - Workflow and rating funnel are manual steps — printed in summary
     - `rating_page_url` placeholder left in Template 1 until GHL funnel is published

   - **`E:\genesis-system\GHL_MODULES\widget\tradie_widget.html`** (1112 lines, READ)
     - Self-contained Smart Widget — all CSS/JS embedded
     - `RAD_CONFIG` block contains all client configuration
     - Hardcoded demo Telnyx agent ID: `assistant-9c42d3ce-e05a-4e34-8083-c91081917637` — must be replaced per client
     - Booking form POSTs webhook payload: `{name, phone, suburb, jobType, message, source, businessUrl, timestamp}`
     - Three tabs: Book a Job (GHL webhook), Chat with Us (`<telnyx-ai-agent>` WebRTC), Call Now (click-to-call)

   - **`E:\genesis-system\GHL_MODULES\mctb_widget\MCTB_SNAPSHOT_SPEC.md`** (271 lines, READ)
     - Full manual build spec for MCTB GHL workflow
     - Workflow: Missed Call trigger → 30s wait → duplicate check → SMS #1 → create opportunity → add tag → owner alert → 4hr wait → reply check → SMS #2 if no reply
     - Branch 2: Reply received → update pipeline stage → alert owner
     - Tags: `missed_call_triggered`, `engaged_via_sms`

   - **`E:\genesis-system\GHL_MODULES\review_generator\SNAPSHOT_SPEC.md`** (384 lines, READ)
     - Full manual build spec for Review Generator GHL assets
     - 3 workflows: RR-01 (Review Request), RR-02 (5-Star Filter), RR-03 (Google Review Follow-Up)
     - 1 funnel: Rating Landing Page with per-star conditional redirects (requires GHL Survey element not Form)
     - Critical: uses GHL Survey (not Form) for conditional per-answer redirects for star ratings

   - **`E:\genesis-system\GHL_MODULES\mctb_widget\widget_per_client_provisioning.md`** (599 lines, READ)
     - Contains full Python provisioning code (as documentation, not a runnable .py file)
     - `create_telnyx_assistant()` — POST to `/v2/ai/assistants` with system prompt, voice config, transfer_call tool
     - `upload_knowledge_base()` — multipart POST to `/v2/ai/assistants/{id}/documents`
     - `provision_australian_number()` — search + order AU numbers by area code
     - `assign_number_to_assistant()` — PATCH phone number to connect to assistant
     - `store_assistant_id_in_ghl()` — POST to GHL custom values
     - `generate_widget_embed_code()` — generates `<telnyx-ai-agent>` embed HTML
     - `provision_client_widget()` — orchestrates all steps
     - Key gap: this is `.md` documentation, not an executable `.py` script

   - **`E:\genesis-system\GHL_MODULES\GHL_MODULES_OVERVIEW.md`** (303 lines, READ)
     - Pricing confirmed: Review Generator $197/mo standalone / $97/mo add-on; MCTB $97/mo standalone / $100/mo add-on; Smart Widget $197/mo standalone / $100/mo add-on
     - Full suite = $641/mo per client; LTV per client = $7,992
     - Recommended sales order: MCTB first → Smart Widget → Review Generator → Full Voice

   - **`E:\genesis-system\TRADIES\GHL_APP_PIPELINE_SPEC.md`** (474 lines, CREATED)
     - Full spec for all 6 TradiesVoice apps with accurate deployment details based on actual script audit
     - Includes provisioning architecture diagram, known GHL API gap, pricing table, per-app deploy steps, gaps found, and prioritised next steps
     - Documents what existing scripts actually do vs what is still manual/missing

   - **`E:\genesis-system\TRADIES\ghl_pipeline_runner.py`** (753 lines, CREATED)
     - Unified deploy runner with plan shortcuts and per-app deployment functions
     - Key structure:
       ```python
       PLANS = {
           "website": ["website"],
           "starter_bundle": ["website", "mctb", "voice_widget"],
           "growth_bundle": ["website", "mctb", "voice_widget", "review_generator"],
           "full_suite": ["website", "mctb", "voice_widget", "phone_agent",
                          "review_generator", "review_display_widget"],
       }
       ```
     - `DeploymentResult` class tracks success, notes, and manual steps per module
     - `deploy_mctb()` and `deploy_review_generator()` call existing scripts via `subprocess.run()`
     - Normalises `GHL_API_KEY` / `GHL_AGENCY_API_KEY` env var inconsistency
     - Other deployers (`deploy_website`, `deploy_voice_widget`, `deploy_phone_agent`, `deploy_review_display_widget`) are stubs with manual step queuing
     - Full timestamped logging to console + log file
     - `print_summary()` prints all manual steps grouped by module
     - Exit code 1 if any module fails
     - Usage: `python ghl_pipeline_runner.py --client-data onboarding.json --plan growth_bundle`

   - **`E:\genesis-system\TRADIES\GHL_CREDENTIALS_CHECKLIST.md`** (277 lines, CREATED)
     - All credentials needed with env var names, how to obtain, and permissions required
     - Minimum viable set to launch first client: `GHL_AGENCY_API_KEY` + `TELNYX_API_KEY` + sub-account ID + Extendly snapshot
     - Full `.env` template for `E:\genesis-system\credentials\tradiesvoice.env`
     - PowerShell loading snippet included
     - Stripe product/price ID table for all 10 pricing tiers

4. Errors and fixes:
   - No errors were encountered. All three files were written successfully on first attempt.
   - One notable inconsistency found and documented: `ghl_api_deploy.py` uses `GHL_API_KEY` while `ghl_mctb_deploy.py` uses `GHL_AGENCY_API_KEY`. The pipeline runner normalises this by setting `env["GHL_API_KEY"] = env["GHL_AGENCY_API_KEY"]` before calling the Review Generator subprocess.

5. Problem Solving:
   - **GHL Workflow API Gap**: Both existing deploy scripts hit the same wall — GHL API v2 cannot programmatically create complex automation workflows. The spec and pipeline runner explicitly document this, flag each module's required manual workflow import step, and reference the exact snapshot spec files.
   - **Env var inconsistency**: Resolved in the pipeline runner by normalising both variable names before subprocess calls.
   - **Missing provision_telnyx_assistant.py**: The provisioning code exists only as documentation inside a `.md` file. The pipeline runner stubs out voice provisioning with manual step queuing and explicitly calls out this gap.
   - **App 6 (Review Display Widget) not built**: No existing implementation found anywhere. The deployer stub queues a build requirement with embed code template.
   - **Demo Telnyx agent ID in tradie_widget.html**: Documented as a gap — must be replaced per client before any production deployment.

6. All user messages:
   - The user's single message was the full agent task briefing as "Agent 2 — GHL Module Activator for TradiesVoice", containing:
     - Working directory: `E:\genesis-system\`
     - Step 1: List of 8 files to read for the audit
     - Step 2: Full content specification for `GHL_APP_PIPELINE_SPEC.md` with 6 app definitions, provisioning decision tree, and API credentials checklist
     - Step 3: Python script specification for `ghl_pipeline_runner.py` with usage examples and required behaviour
     - Final instruction: "After reading the existing deploy scripts, also update the spec with: What those scripts actually do (not assumptions), Any gaps you find, Recommended fixes"
   - The second user message was a request for a conversation summary (the current message).

7. Pending Tasks:
   - Extract `widget_per_client_provisioning.md` Python code into a standalone `provision_telnyx_assistant.py` runnable script
   - Standardise GHL env var naming across all scripts to `GHL_AGENCY_API_KEY`
   - Build `reviews.js` widget for App 6 (Review Display Widget) — zero existing implementation
   - Build GHL sub-account creation script (no existing script for initial sub-account provisioning)
   - Package GHL snapshots for MCTB and Review Generator workflows to eliminate the largest manual step
   - Automate `rating_page_url` update in Review Generator after GHL funnel is published
   - Create and import n8n workflow JSONs into Elestio n8n instance (per TITAN MEMORY axiom fe_004 — workflows built but never imported)
   - Create Stripe product and price IDs for all 10 TradiesVoice pricing tiers

8. Current Work:
   All three requested output files were completed immediately before this summary request:

   - `E:\genesis-system\TRADIES\GHL_APP_PIPELINE_SPEC.md` (474 lines) — Full 6-app pipeline specification with accurate audit findings, gaps, and next steps
   - `E:\genesis-system\TRADIES\ghl_pipeline_runner.py` (753 lines) — Unified deploy runner
   - `E:\genesis-system\TRADIES\GHL_CREDENTIALS_CHECKLIST.md` (277 lines) — Full credentials checklist

   The final file written was `GHL_CREDENTIALS_CHECKLIST.md`, completing all three deliverables from the original task brief.

9. Optional Next Step:
   All three explicitly requested files have been created and the task is complete. The most directly actionable next step aligned with the original task is extracting the Telnyx provisioning code from documentation into an executable script, as explicitly called out in the spec:

   From `GHL_APP_PIPELINE_SPEC.md`, App 3 Gaps Found section: "widget_per_client_provisioning.md contains the full provisioning code as documentation, but there is no standalone .py runner file — only the markdown. Need to extract to provision_telnyx_assistant.py."

   And from `ghl_pipeline_runner.py` `deploy_voice_widget()`: "TODO: Extract and call provision_telnyx_assistant.py when built"

   However, since the primary task is now complete and this was not an explicit separate instruction, confirmation from the user before proceeding is recommended.
</summary>

service_tier: standard

type: assistant


type: progress

hookEvent: SubagentStop

hookName: SubagentStop

command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/observability_logger.py --event subagent_stop