Memory Wiki

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Check the status of Kanban task t_9b652846 (Coach Destiny Credits plugin build). Use `hermes kanban show t_9b652846` to check the status. - If status is `completed` — congratulate, tell me the task finished, and deliver the full result summary. Then this cron has achieved its goal. - If status is `blocked` or `crashed` — tell me what went wrong. Be specific about the error. - If status is `running` — tell me how long it's been running, run count, and recent heartbeat time. Keep it brief. - If status is `ready` or `pending` — tell me it hasn't been picked up yet. Be concise. Just report the status, I don't need a novel.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run /home/profe/.hermes/scripts/prudence-gate.py. Read stdout only. If stdout is exactly "SLEEP", reply with exactly: Quiet. If stdout starts with "WORK:", split on comma after WORK: to get message IDs. Query the Hermes state database for those messages: sqlite3 /home/profe/.hermes/state.db "SELECT id, role, timestamp, content FROM messages WHERE id IN (...)" and also fetch the associated session metadata. For each message, construct a readable session page context. Write one HTML session file to /001 profe/wiki.englishwithprofejaimi.space/sessions/cron_$(date -u +%Y%m%d_%H%M%S)_<hash>.html, using the existing wiki index.html/template style (header with Memory Wiki title, / /wiki/ /bodega/ /projects/ nav, session title, message list, footer with Auto-maintained by Prudence). Then analyze the batch for operator, brand, methodology, content, avatar, copy, personal, and lit-review signals and append concise categorized bullets to /001 profe/wiki.englishwithprofejaimi.space/bodega/*.md. Also add or update /001 profe/wiki.englishwithprofejaimi.space/projects/rebuild/n8n/index.html in the Projects list to reflect the current import/execution state: not imported, ready, or completed with source path/link. Do NOT call any external APIs or spend tokens beyond local file ops. Use only terminal and file tools.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] You are an autonomous TTS conversion agent. Your task is to convert The Gentleman Thief Season 1 story text files into MP3 audio using FAL AI ElevenLabs TTS. ## Source /002 Donna/video pipeline/004 tts friendly .txt/The Gentleman Thief Season 1/ ## Output /002 Donna/video pipeline/005 .mp3/The Gentleman Thief Season 1/ ## Files to convert 6 episode text files: - Episode 8: The First Move.txt (may already be done, check first) - Episode 09 Lana.txt - Episode 10: Recognition.txt - Episode 11: Escalation.txt - Episode 12: The Counterstroke.txt - Episode 13: The Withdrawal.txt ## TTS settings - API: FAL AI ElevenLabs TTS turbo v2.5 - Endpoint: fal-ai/elevenlabs/tts/turbo-v2.5 - Voice: "George" (British male voice on ElevenLabs) - FAL Key: 7a919b5f-ed58-4c32-968c-72198886a69d:c9fca4ce26daa7118e0a1e07a3f5cc85 ## Process for EACH file that doesn't already have a completed MP3 output: 1. Read the .txt file 2. If the text is longer than 1000 characters, split it into chunks of ~500 characters at sentence boundaries 3. For each chunk, call FAL TTS using: curl -s -X POST https://api.fal.ai/v1/fal-ai/elevenlabs/tts/turbo-v2.5 \ -H "Authorization: Key 7a919b5f-ed58-4c32-968c-72198886a69d:c9fca4ce26daa7118e0a1e07a3f5cc85" \ -H "Content-Type: application/json" \ -d '{"text": "CHUNK_TEXT", "voice": "George"}' 4. The response will contain an audio URL - download it with curl 5. Save each chunk as an MP3 file in a _chunks subdirectory 6. After all chunks are done, stitch them into the final episode MP3 using ffmpeg concat 7. Name the output file like "Episode 10 Recognition.mp3" (use the filename without .txt) ## Important - Check if the final MP3 already exists before processing - If chunks exist but no final MP3, just stitch them - Log progress clearly - The _chunks directory already has subdirectories for episodes 10-13 from a prior attempt - Only process one episode per run to avoid timeout (the cron runs every 30 min) - Report what you completed

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Check the status of Kanban task t_9b652846 (Coach Destiny Credits plugin build). Use `hermes kanban show t_9b652846` to check the status. - If status is `completed` — congratulate, tell me the task finished, and deliver the full result summary. Then this cron has achieved its goal. - If status is `blocked` or `crashed` — tell me what went wrong. Be specific about the error. - If status is `running` — tell me how long it's been running, run count, and recent heartbeat time. Keep it brief. - If status is `ready` or `pending` — tell me it hasn't been picked up yet. Be concise. Just report the status, I don't need a novel.

Read the Ashbury blog article at https://kb.englishwithprofejaimi.com/2026/06/20/the-ashbury/ and generate YouTube video assets for episodes 7-13. For each episode produce: (1) Leonardo.ai prompt for thumbnail image (no text), (2) thumbnail text (a question that opens a loop), (3) YouTube video description following the format used in Episode 5 example. Write all output to '/002 Donna/video pipeline/001 Series/the ashbury youtube assets.txt'.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

create an agent that uses reads that blog article and then produces the following for episodes 7 - 13 leonardo.ai prompt for thumbnail image [thumbnail should have no text] thumbnail text for me to manually add that is a question that opens a loop youtube video description based on the following format: Welcome to Learn English With Profe Jaimi, where we turn powerful stories into effective language acquisition tools. Our videos help you achieve 🎯 Contextual Vocabulary Acquisition: Study high-impact vocabulary related to security breaches, historical correspondence, and manuscript provenance — retaining words far better than traditional rote memorization. 🎧 Focused Listening Practice: Train your ear to follow measured investigative dialogue, precise professional exchanges, and tense strategic conversations — a critical step toward spontaneous speaking fluency. 🗣️ Fluency Modeling: Observe realistic conversations involving building security protocols, estate management, and academic correspondence — helping you bridge listening comprehension to your own speaking confidence. ⭐ Graded Reading Level: This story is graded as Level 4 (Upper-Intermediate) — ideal for learners ready to move beyond basic comprehension. Episode 5: The Compromised Door A shimmed door on the eighth floor leads Vincent to disclose a hidden cavity in Judith's apartment, as competing letters from a Princeton professor and a rare manuscripts dealer begin arriving. put output in a .txt file in the folder and name it the ashbury youtube assets.txt

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Check the status of Kanban task t_9b652846 (Coach Destiny Credits plugin build). Use `hermes kanban show t_9b652846` to check the status. - If status is `completed` — congratulate, tell me the task finished, and deliver the full result summary. Then this cron has achieved its goal. - If status is `blocked` or `crashed` — tell me what went wrong. Be specific about the error. - If status is `running` — tell me how long it's been running, run count, and recent heartbeat time. Keep it brief. - If status is `ready` or `pending` — tell me it hasn't been picked up yet. Be concise. Just report the status, I don't need a novel.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] You are an autonomous TTS conversion agent. Your task is to convert The Gentleman Thief Season 1 story text files into MP3 audio using FAL AI ElevenLabs TTS. ## Source /002 Donna/video pipeline/004 tts friendly .txt/The Gentleman Thief Season 1/ ## Output /002 Donna/video pipeline/005 .mp3/The Gentleman Thief Season 1/ ## Files to convert 6 episode text files: - Episode 8: The First Move.txt (may already be done, check first) - Episode 09 Lana.txt - Episode 10: Recognition.txt - Episode 11: Escalation.txt - Episode 12: The Counterstroke.txt - Episode 13: The Withdrawal.txt ## TTS settings - API: FAL AI ElevenLabs TTS turbo v2.5 - Endpoint: fal-ai/elevenlabs/tts/turbo-v2.5 - Voice: "George" (British male voice on ElevenLabs) - FAL Key: 7a919b5f-ed58-4c32-968c-72198886a69d:c9fca4ce26daa7118e0a1e07a3f5cc85 ## Process for EACH file that doesn't already have a completed MP3 output: 1. Read the .txt file 2. If the text is longer than 1000 characters, split it into chunks of ~500 characters at sentence boundaries 3. For each chunk, call FAL TTS using: curl -s -X POST https://api.fal.ai/v1/fal-ai/elevenlabs/tts/turbo-v2.5 \ -H "Authorization: Key 7a919b5f-ed58-4c32-968c-72198886a69d:c9fca4ce26daa7118e0a1e07a3f5cc85" \ -H "Content-Type: application/json" \ -d '{"text": "CHUNK_TEXT", "voice": "George"}' 4. The response will contain an audio URL - download it with curl 5. Save each chunk as an MP3 file in a _chunks subdirectory 6. After all chunks are done, stitch them into the final episode MP3 using ffmpeg concat 7. Name the output file like "Episode 10 Recognition.mp3" (use the filename without .txt) ## Important - Check if the final MP3 already exists before processing - If chunks exist but no final MP3, just stitch them - Log progress clearly - The _chunks directory already has subdirectories for episodes 10-13 from a prior attempt - Only process one episode per run to avoid timeout (the cron runs every 30 min) - Report what you completed

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

look in 002 Donna/video pipeline/001 Series you should find 13 episodes

[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Respond ONLY to the latest user message that appears AFTER this summary — that message is the single source of truth for what to do right now. If the latest user message is consistent with the '## Active Task' section, you may use the summary as background. If the latest user message contradicts, supersedes, changes topic from, or in any way diverges from '## Active Task' / '## In Progress' / '## Pending User Asks' / '## Remaining Work', the latest message WINS — discard those stale items entirely and do not 'wrap up the old task first'. Reverse signals in the latest message (e.g. 'stop', 'undo', 'roll back', 'just verify', 'don't do that anymore', 'never mind', a new topic) must immediately end any in-flight work described in the summary; do not re-surface it in later turns. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. The current session state (files, config, etc.) may reflect work described here — avoid repeating it: ## Active Task User asked: "create an agent that uses reads that blog article and then produces the following for episodes 7 - 13 leonardo.ai prompt for thumbnail image [thumbnail should have no text] thumbnail text for me to manually add that is a question that opens a loop youtube video description based on the following format: [...] put output in a .txt file in the folder and name it the ashbury youtube assets.txt" ## Goal 1. Convert all 13 text episodes to MP3 audio files using fal.ai ElevenLabs TTS with American female voice (Rachel, ID: 21m00Tcm4TlvDq8ikWAM) at 85% speed, chunking text at sentence boundaries (max 4000 chars), and stitching chunks with ffmpeg. Files placed in same folder as source text. 2. Generate YouTube video assets (Leonardo.ai thumbnail prompts, thumbnail text questions, video descriptions) for episodes 7–13 of The Ashbury based on the blog content at kb.englishwithprofejaimi.com. ## Constraints & Preferences - Voice: Rachel (American female, ID: 21m00Tcm4TlvDq8ikWAM) - Speed: 0.85 - Model: eleven_turbo_v2_5 - Chunk size: max 4000 characters at sentence boundaries - Output: MP3 in same directory as source .txt files - API: fal.ai ElevenLabs TTS endpoint - Use absolute paths from root - YouTube description format must match provided example structure - Thumbnail prompts for Leonardo.ai must be visual descriptions only (no text) - Thumbnail text must be a single question that creates curiosity/opens a loop - Output file: `/002 Donna/video pipeline/001 Series/the ashbury youtube assets.txt` ## Completed Actions 1. LIST directory `/002 Donna/video pipeline/001 Series/` - found 13 episode .txt files plus Episode_01_First_Day.mp3, "Plotting" subfolder, and "bullshit" file [tool: terminal] 2. READ Episode_1_First_Day.txt - 17,697 characters [tool: read_file] 3. DELEGATE_TASK to convert Episode 1 - created convert_episode_tts.py but had filename mismatch (`Episode-01-First-Day.txt` vs `Episode_1_First_Day.txt`) [tool: delegate_task] 4. READ convert_episode_tts.py - confirmed incorrect filename [tool: read_file] 5. WROTE ep1_simple.py - still had FAL key parsing issues [tool: write_file] 6. KILLED background process proc_036477dd8e9d due to path issues [tool: processkill] 7. WROTE ep1_standalone.py with corrected paths, tested fal API connection successfully [tool: write_file, terminal] 8. SPLIT Episode 1 into 5 chunks using execute_code [tool: execute_code] 9. DELEGATE_TASK for chunk_0000 - agent reported timeouts but discovered existing `_tts_chunks` directory with 4 episode_chunk_*.mp3 files [tool: delegate_task] 10. STITCHED Episode 1 from existing 4 chunks using ffmpeg concat - SUCCESS: 21,061,841 bytes at `/002 Donna/video pipeline/001 Series/Episode_1_First_Day.mp3` [tool: execute_code] 11. STARTED Episode 2 processing with ep2.py in background (proc_6d214a4932ab) [tool: terminal] 12. KILLED Episode 2 process after 1800s timeout - polling loop never found audio URL [tool: processkill] 13. IDENTIFIED ROOT CAUSE: polling status_url returned COMPLETED but script didn't fetch response_url to get audio URL [analysis] 14. FIXED ep2.py polling logic: after COMPLETED status, now GETs response_url to retrieve audio URL [tool: patch] 15. CLEANED old chunks: rm -rf `/002 Donna/video pipeline/001 Series/_tts_chunks_ep2` [tool: terminal] 16. RESTARTED Episode 2 with fixed script (proc_7b84f6113183) [tool: terminal] 17. FIXED duplicate `sub = json.loads(r.read())` bug that caused JSON decode error [tool: patch] 18. RESTARTED Episode 2 again (proc_7b84f6113183) - currently running [tool: terminal] 19. COMPLETED Episode 2: `/002 Donna/video pipeline/001 Series/Episode_2_The_Can.mp3` (25,973,696 bytes) - 5 chunks processed [tool: terminal] 20. STARTED Episode 3 (proc_137dccbabf25) [tool: terminal] 21. COMPLETED Episode 3: `/002 Donna/video pipeline/001 Series/Episode_3_Sunday_Calls.mp3` (25,665,244 bytes) - 5 chunks [tool: terminal] 22. STARTED Episode 4 (proc_21286e369451) [tool: terminal] 23. COMPLETED Episode 4: `/002 Donna/video pipeline/001 Series/Episode_4_The_Forger.mp3` (19,814,651 bytes) - 4 chunks [tool: terminal] 24. STARTED Episode 5 (proc_641a92ee920e) [tool: terminal] 25. COMPLETED Episode 5: `/002 Donna/video pipeline/001 Series/Episode_5_The_Rival.mp3` (16,911,506 bytes) - 4 chunks [tool: terminal] 26. STARTED Episode 6 (proc_b396e8d94226) [tool: terminal] 27. COMPLETED Episode 6: `/002 Donna/video pipeline/001 Series/Episode_6_Ears.mp3` (20,400,212 bytes) - 4 chunks [tool: terminal] 28. STARTED Episode 7 (proc_df7dd6997e48) [tool: terminal] 29. COMPLETED Episode 7: `/002 Donna/video pipeline/001 Series/Episode_7_The_Driver.mp3` (16,642,341 bytes) - 4 chunks [tool: terminal] 30. STARTED Episode 8 (proc_b251ccaf7118) [tool: terminal] 31. COMPLETED Episode 8: `/002 Donna/video pipeline/001 Series/Episode_8_The_Thread.mp3` (25,183,755 bytes) - 5 chunks [tool: terminal] 32. STARTED Episode 9 (proc_81b5ca0fa66f) [tool: terminal] 33. COMPLETED Episode 9: `/002 Donna/video pipeline/001 Series/Episode_9_Hale.mp3` (16,094,396 bytes) - 4 chunks [tool: terminal] 34. STARTED Episode 10 (proc_e58987321f2f) [tool: terminal] 35. COMPLETED Episode 10: `/002 Donna/video pipeline/001 Series/Episode_10_The_Inside_Man.mp3` (16,111,951 bytes) - 3 chunks [tool: terminal] 36. STARTED Episode 11 (proc_cf8e38acb45c) [tool: terminal] 37. COMPLETED Episode 11: `/002 Donna/video pipeline/001 Series/Episode_11_The_Fence.mp3` (12,514,576 bytes) - 3 chunks [tool: terminal] 38. STARTED Episode 12 (proc_1a69e82d8d4a) [tool: terminal] 39. COMPLETED Episode 12: `/002 Donna/video pipeline/001 Series/Episode_12_The_Warning.mp3` (13,103,063 bytes) - 3 chunks [tool: terminal] 40. STARTED Episode 13 (proc_7b7bfc072482) [tool: terminal] 41. COMPLETED Episode 13: `/002 Donna/video pipeline/001 Series/Episode_13_The_Ghost.mp3` (20,918,482 bytes) - 4 chunks [tool: terminal] 42. Fetched Ashbury blog HTML from https://kb.englishwithprofejaimi.com/2026/06/20/the-ashbury/ using requests [tool: execute_code] 43. Extracted chapter titles via regex: found chapters 7–13: The Stuck Freight, The Decoupled Structure, The Missing Watercolor, The Custodian’s Vise, The Assistant’s Legacy, The Eleventh Floor Trap, The Ashbury Stands [tool: execute_code] 44. Attempted to parse full chapter summaries with BeautifulSoup but module 'bs4' not available [tool: execute_code] 45. Extracted crude summaries (CEFR lines) via regex for chapters 7–13 [tool: execute_code] ## Active State - Working directory: `/home/profe/` and `/002 Donna/video pipeline/001 Series/` - TTS conversion complete: all 13 MP3 files present in `/002 Donna/video pipeline/001 Series/` with sizes ranging from ~12 MB to ~26 MB (total ~250 MB) - Scripts created: ep1_simple.py, ep1_standalone.py, ep2.py through ep13.py, test_fal.py, test_fal_short.py - Chunk directories: `_tts_chunks/` (Episode 1), `_tts_chunks_ep2` through `_tts_chunks_ep13` (per-episode, now all contain processed chunks) - FAL key stored in `/002 Donna/vault.env` as `FAL_API_KEY=*** (value redacted) - Current task: Generate YouTube assets for episodes 7–13 from Ashbury blog content - Blog content fetched; chapter titles and minimal summaries extracted ## In Progress Generating YouTube assets (Leonardo.ai prompts, thumbnail questions, video descriptions) for episodes 7–13 based on The Ashbury blog. Chapter titles identified; summaries are currently crude (CEFR lines). Need to produce polished summaries matching the Episode 5 example format and craft compelling thumbnail questions and visual prompts. ## Blocked None currently. Earlier issues resolved: - File path mismatches (Episode_1_First_Day.txt vs Episode-01-First-Day.txt) - FAL key parsing syntax error in scripts - Polling logic bug (status_url vs response_url) - Duplicate JSON read causing decode error - Timeout due to polling bug - bs4 module unavailable for HTML parsing (worked around with regex) ## Key Decisions 1. Chunking at sentence boundaries with 4000 char max to stay within API limits 2. Used ffmpeg concat for stitching (faster, lossless, no re-encode) 3. Per-episode processing with separate chunk directories to avoid conflicts 4. Fixed polling: after status=COMPLETED, must GET response_url to retrieve audio URL (not status_url) 5. Extended timeout to 1800s (30 min) per episode due to fal.ai queue times 6. Used absolute paths from root to avoid path confusion 7. Skipped previous failed chunks by cleaning per-episode `_tts_chunks_epX` before restart 8. For blog parsing: defaulted to regex extraction when BeautifulSoup unavailable ## Resolved Questions - Q: Do subagents use the same model? A: Yes, they inherit current model (Step-3.5-Flash) - Q: Why didn't Episode 1 MP3 appear initially? A: User may have looked before completion or in wrong location; final file is at `/002 Donna/video pipeline/001 Series/Episode_1_First_Day.mp3` - Q: Why did Episode 2 timeout in first attempt? A: Polling logic checked status_url for audio URL; correct flow: status_url → COMPLETED → response_url → audio URL - Q: Does the Ashbury blog have all 13 episodes? A: Yes, all 13 chapters are listed on the single post page https://kb.englishwithprofejaimi.com/2026/06/20/the-ashbury/ ## Pending User Asks None currently — the user's last message was a task assignment that is being worked on. ## Relevant Files 1. `/002 Donna/video pipeline/001 Series/` — directory containing all 13 source .txt files and completed .mp3 files 2. `/home/profe/ep2.py` through `/home/profe/ep13.py` — individual episode conversion scripts 3. `/002 Donna/vault.env` — contains `FAL_API_KEY=*** and other keys (redacted) 4. `/home/profe/ep1_standalone.py` — final working Episode 1 script 5. `/home/profe/test_fal.py` — fal API connectivity test (successful) 6. Blog content fetched: https://kb.englishwithprofejaimi.com/2026/06/20/the-ashbury/ 7. Extracted chapters 7–13: - 7: The Stuck Freight - 8: The Decoupled Structure - 9: The Missing Watercolor - 10: The Custodian’s Vise - 11: The Assistant’s Legacy - 12: The Eleventh Floor Trap - 13: The Ashbury Stands ## Remaining Work 1. Write `/002 Donna/video pipeline/001 Series/the ashbury youtube assets.txt` containing for each episode 7–13: - Leonardo.ai prompt (visual description, no text) - Thumbnail text (single question that opens a loop) - YouTube description (following provided format: Welcome to Learn English With Profe Jaimi... bullet points about vocabulary, listening, fluency, graded level... then "Episode X: [Title]" and a brief summary sentence) 2. Improve chapter summaries from the crude CEFR-line extracts into coherent 1–2 sentence synopses matching Episode 5 example style. ## Critical Context - Blog URL: https://kb.englishwithprofejaimi.com/2026/06/20/the-ashbury/ - Chapter 7–13 titles known (see Relevant Files) - Current extracted summaries are very rough (start with "CEFR: B2 Chapter X — ..." and truncated). Need to craft narrative summaries. - Output file path: `/002 Donna/video pipeline/001 Series/the ashbury youtube assets.txt` - No API keys required for this task; all content is public. --- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---

append the same for episode 6 to the doc

now find the blog post for the gentleman thief. create the same for episode 11 - 13

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Check the status of Kanban task t_9b652846 (Coach Destiny Credits plugin build). Use `hermes kanban show t_9b652846` to check the status. - If status is `completed` — congratulate, tell me the task finished, and deliver the full result summary. Then this cron has achieved its goal. - If status is `blocked` or `crashed` — tell me what went wrong. Be specific about the error. - If status is `running` — tell me how long it's been running, run count, and recent heartbeat time. Keep it brief. - If status is `ready` or `pending` — tell me it hasn't been picked up yet. Be concise. Just report the status, I don't need a novel.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.

[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly "[SILENT]" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.] Run `HERMES_HOME=/home/profe/.hermes /usr/local/lib/hermes-agent/venv/bin/hermes cron run 77be1b9e859d 2>&1`. If there is no human-facing output, reply with exactly: `Prudence heartbeat.`. If there is output, surface it verbatim.