Agently connects company stack with AI brain

`. I will run a python command to list recent conversation transcripts in the brain directory and print the user prompts and assistant responses to see if there are any that match the product draft review format. I will run an updated python command to safely search the transcripts. I will run a python command to see what conversation folders are present and display a snippet of their user inputs. I will run a python command to display a snippet of user inputs with correct string escaping. I will run a python command to list all python scripts in the scratch directory that contains matching terms related to the prompt. I will view the `audit_engine.py` file to understand the auditing logic and instructions. I will view `read_prompts.py` to see what instructions or processing it contains. I will view the `read_tweet.py` script. I will run a grep search across the system transcripts to find how post draft reviews were formatted and answered. I will search the transcripts for keywords like "CATEGORY:" to find other post drafts. I will list the Markdown files in the scratch directory to see if there are other skill descriptions. I will view the `SKILL_post_audit.md` file to read the exact instructions and format for auditing post drafts. I will view `SKILL_gatekeeper.md` to see if it holds instructions on how to review/audit post drafts and the expected output format. I will perform a targeted web search to check for the correct spelling and release date of Agently. I will search specifically for the publication date of the Agently Product Hunt launch to verify recency. I will read the Product Hunt page for Agently to find the exact launch date and any other announcement details. I will search Google for the launch date of the Agently product on Product Hunt. DECISION: APPROVE SKIP_REASON: HEADLINE: Agently connects company stack with AI brain PRODUCT_NAME: UNCHANGED SUMMARY: UNCHANGED