Fresh Capital + Open Role

You are running "Play 01: Fresh Capital + Open Role" from GTM Signal Plays by Asshvin Kumar.

Goal: build a short, verified list of software companies that just reported a raise to the SEC (Form D) AND are hiring the role my product serves. Then draft one message per company, built only from those public records.

Rules
- Use only free public data and the script below. No paid tools, no logins, no LinkedIn automation.
- Never invent a fact. Every claim in a brief or message must trace to the Form D filing or the job post it came from. Mark anything inferred as "assumed".
- Respect SEC fair access: at most 10 requests a second, with my real name and email in the User-Agent.
- Do not send anything. I review and send myself.

Step 0. Before writing any code, ask me:
  1. My name and email (for the SEC User-Agent).
  2. What my product does, in one sentence.
  3. The job titles my product serves. Turn my words into a case-insensitive regex and show it to me.

Step 1. Set up
  mkdir -p play-01-fresh-capital && cd play-01-fresh-capital
  curl -fsSL __RUN_PY_URL__ -o run.py
  Read run.py fully. Tell me in 5 bullets what it does and which URLs it calls. It needs Python 3.9+ and nothing else.

Step 2. Run it on the last 14 days
  SEC_USER_AGENT="<my name> <my email>" python3 run.py --days 14 --roles "<regex from step 0>"
  It writes out/<date>/accounts.csv, summary.json and briefs.md. Show me the funnel counts from summary.json.

Step 3. Verify before trusting it
  For every Tier 1 row (or 10 at random if there are more):
  - open the Form D link and confirm the company name, filing date and amount;
  - open the job link and confirm the role is live at the same company. For slug-only matches, compare the board's website, company description and job locations with the filing's state;
  - remove or downgrade any row that fails, and tell me why.
  Save the result as verified.csv.

Step 4. Brief each verified company (5 lines max) in briefs-verified.md
  What they raised and when; the role they opened; who signed the filing; the problem that role is likely hired to fix (mark as assumed); why my product fits that problem.

Step 5. Draft one message per company in messages.md (under 90 words)
  - To the executive named on the filing or the hiring manager.
  - Open with the record: the raise and the open role, with dates. Not with me.
  - Give one useful observation they can act on even if they never reply.
  - End with one low-effort question. No links, no "hope you're well", no fake familiarity.
  Then reread each draft as the buyer: would they forward it to a colleague? Rewrite any that would be deleted.

Step 6. Hand over
  verified.csv, briefs-verified.md, messages.md, and a 3-line summary with the funnel counts. Suggest the --roles regex and --days window for next week's run.

You are running "Play 01 for job seekers: Fresh Capital + Open Role" from GTM Signal Plays by Asshvin Kumar.

Goal: find jobs at software companies that just raised money (SEC Form D) and are hiring for roles that fit my resume. Then help me write a short, honest note for each.

Rules
- Use only free public data and the script below. No logins, no auto-applying, no LinkedIn automation.
- My resume stays on my computer. Read it locally and never upload it anywhere.
- Never invent facts about me or the company. Every claim must trace to my resume, the Form D filing or the job post.

Step 0. Ask me 3 things before doing anything:
  1. The path to my resume on this computer (PDF, DOCX or TXT).
  2. The roles I want (for example: forward deployed engineer, GTM engineer, product manager). Turn them into a case-insensitive regex and show it to me.
  3. Where I can work (cities, remote, countries), plus my name and email for the SEC User-Agent.

Step 1. Read my resume locally. List my top 8 skills and my 3 strongest results with numbers. Let me correct them.

Step 2. Set up
  mkdir -p play-01-jobs && cd play-01-jobs
  curl -fsSL __RUN_PY_URL__ -o run.py
  Read run.py fully. Tell me in 5 bullets what it does and which URLs it calls.

Step 3. Run it on the last 30 days (the SEC step takes 15 to 20 minutes)
  SEC_USER_AGENT="<my name> <my email>" python3 run.py --days 30 --roles "<regex from step 0>"
  It writes out/<date>/jobs.csv: every open role at those companies, with the raise amount and filing date.

Step 4. Filter and rank
  Keep roles that match my regex and my locations. Check each company's jobs page really belongs to the company on the filing (name, website, job locations vs the filing's state); drop any that fail and tell me why.
  Rank the rest by fit with my resume. Show the top 10 as a table: role, company, location, raised, filed, fit 1-5, one-line why, link.

Step 5. For my top 5, write notes.md:
  - Why this company, now: the raise and the open role, with dates.
  - The 2 parts of my resume that best match the job post, quoted from my resume.
  - A 70-word note to the hiring manager. Open with their news, not with me. No buzzwords.

Step 6. Hand over jobs-shortlist.csv and notes.md. Do not apply or send anything. I do that myself.