git:20261003.2de3c0b to git:20261007.4758700

- description: 'Run a quick Deepline demo recipe to show the user how Deepline works.'

- ## CLI resolution

-

- Run `deepline` when it is available. If the shell reports that command is missing, use `<workspace-root>/.deepline/runtime/bin/deepline` (or the npm-created `.cmd` shim on Windows). If neither exists, follow `https://code.deepline.com/INSTALL.md` to set up Deepline.

-

- Run a high-confidence demo recipe to show the user what Deepline can do. Pick the most relevant recipe below, or default to Recipe 1 if no context is given.

-

- **Always prefer the hardcoded recipes below.** `/deepline-gtm` is always available as a fallback but should only be used if: (a) a recipe command fails and all fallbacks are exhausted, or (b) the user's ask doesn't match any recipe here. Never invoke it preemptively.

-

- ## Execution flow

-

- Follow this pattern for every recipe:

-

- 1. **Tell the user what you're about to do** — explain the goal and which data source(s) you'll use, before running anything.

- 2. **Run the recipe to a terminal result.** For this default quickstart, do not spend time on separate session/progress commands; they do not improve the demo. If the command executor yields a running cell, keep waiting on that same cell until it completes. A running Play is not a finished quickstart.

- 3. **Tell the user the results only after the CSV exists** — summarize what came back, where it came from, and the exact CSV path they can inspect next. If the command reaches a terminal failure instead, report that failure and do not promise an output path.

-

- ### CLI surface

-

- This quickstart needs to be fast. Do not run `deepline --version`, `deepline auth status`, or separate CLI discovery commands on the fast path. Use the SDK CLI `deepline enrich` shape with `--name quickstart-ny-cto-email` and the hyphenated `person-linkedin-to-email` prebuilt id. If a retry needs command-shape confirmation, use `deepline --help` or `deepline enrich --help`.

-

- ## Recipe 1 — Find CTOs at NY startups

-

- **Goal:** Find 5 CTOs at startups in New York with verified emails and LinkedIn profiles.

- **Data sources:** Dropleads (people search) + waterfall email enrichment via `person-linkedin-to-email`.

-

- **Steps:**

-

- 1. Search Dropleads for CTOs in New York

- 2. Waterfall enrich emails

- 3. Display results

-

- ### Fast path

-

- For the default quickstart, run this whole block as one Bash call. Do not split it into separate tool calls. The call is complete only when `deepline enrich` exits and writes `deepline/data/quickstart_enriched.csv`; if the executor returns a running cell, wait on that cell again until it is terminal. Do not inspect the JSON, run `csv show`, print the CSV with Python, or run extra validation after the enrich command; those checks make the quickstart miss the one-minute budget.

-

- ```bash

- set -e

- mkdir -p deepline/data

-

- deepline tools execute dropleads_search_people --json --payload '{

- "filters": {

- "jobTitles": ["CTO"],

- "personalStates": {"include": ["New York"]},

- "employeeRanges": ["1-10", "11-50", "51-200"]

- },

- "pagination": {"page": 1, "limit": 5}

- }' > deepline/data/quickstart_search.json

-

- python3 - <<'PY'

- import csv, json

- d = json.load(open("deepline/data/quickstart_search.json"))

- leads = (

- d.get("result", {}).get("data", {}).get("leads")

- or d.get("toolResponse", {}).get("raw", {}).get("leads")

- or d.get("leads")

- or d.get("output_preview", {}).get("preview")

- or []

- )

- if not leads:

- raise SystemExit("No Dropleads leads returned")

-

- with open("deepline/data/quickstart_ny_ctos.csv", "w", newline="") as f:

- w = csv.DictWriter(f, ["first_name", "last_name", "company", "title", "linkedin_url"])

- w.writeheader()

- for r in leads[:5]:

- url = (r.get("linkedinUrl") or r.get("linkedin_url") or "").strip()

- if url.startswith("http://"):

- url = "https://" + url[len("http://"):]

- w.writerow({

- "first_name": r.get("firstName") or r.get("first_name") or "",

- "last_name": r.get("lastName") or r.get("last_name") or "",

- "company": r.get("companyName") or r.get("company") or "",

- "title": r.get("title") or "",

- "linkedin_url": url,

- })

- PY

-

- deepline enrich --input deepline/data/quickstart_ny_ctos.csv --output deepline/data/quickstart_enriched.csv --name quickstart-ny-cto-email --all \

- --with '{"alias":"email","tool":"person-linkedin-to-email","payload":{"linkedin_url":"{{linkedin_url}}"}}'

- ```

-

- ### Step 1 — Search

-

- Only use the detailed steps below if the fast path fails.

-

- ```bash

- deepline tools execute dropleads_search_people --payload '{

- "filters": {

- "jobTitles": ["CTO"],

- "personalStates": {"include": ["New York"]},

- "employeeRanges": ["1-10", "11-50", "51-200"]

- },

- "pagination": {"page": 1, "limit": 5}

- }'

- ```

-

- Note the output CSV path from the result.

-

- ### Step 2 — Waterfall enrich emails

- First, make sure the CSV has plain string columns named `first_name`, `last_name`, and `linkedin_url`. If the Dropleads result uses `fullName` and `linkedinUrl`, normalize those columns locally instead of running a separate Deepline enrichment pass; this quickstart should spend paid work only on the email waterfall. Use full `https://www.linkedin.com/in/...` URLs.

- Then run the waterfall:

- ```bash

- deepline enrich --input <normalized_csv> --output <enriched_csv> --name quickstart-ny-cto-email --all \

- --with '{"alias":"email","tool":"person-linkedin-to-email","payload":{"linkedin_url":"{{linkedin_url}}"}}'

- ```

- Report the output CSV path after this step.

- ### Step 3 — Display results

- After the fast path finishes, do not run another command just to display rows. Tell the user the enriched CSV path and that emails were filled via the dedicated LinkedIn-to-email waterfall. Mention they can go deeper — phone, firmographics, job change signals — with `/deepline-gtm`.

- ### Fallback (if Step 1 errors)

- Tell the user, then try Dropleads:

- deepline tools execute dropleads_search_people --payload '{

- "filters": {

- "jobTitles": ["CTO", "Chief Technology Officer"],

- "personalCountries": {"include": ["United States"]},

- "personalStates": {"include": ["New York"]},

- "personalCities": {"include": ["New York"]}

- },

- "pagination": {

- "page": 1,

- "limit": 5

- }

- }'

- ### Last resort

-

- If all commands fail, tell the user, then invoke `/deepline-gtm`:

-

- > Find 5 CTOs at startups in New York with their emails and LinkedIn profiles.