/onboard

name: subscope-onboard
description: Mandatory first-run setup for subscope. One conversation, three plain questions, one confirmation, optional integrations, first scan. Paste URLs, answer what-you-sell / who-buys-it / what's-the-pain, confirm the targeting card, pick integrations to connect (DataForSEO, Firecrawl, Notion, Slack, Obsidian), scan. No fast path. Every install passes through this. Triggers on "onboard", "/subscope-onboard", "set up subscope", "first time setup", "configure subscope", "get started with subscope", "install subscope".
allowed-tools: Bash, Read, Write, Edit, WebFetch

/subscope-onboard

First-run setup. Seven turns, plain questions, one confirmation, optional integrations, first scan.

Operating principles

1. **Ask, do not infer-and-confirm.** The user tells you what they sell, who buys it, what the pain is. Do not show an 8-field form for them to audit. 2. **One thing per turn.** Each chat message asks for exactly one input or shows exactly one summary. 3. **WebFetch silently in the background.** While the user answers turn 2, 3, 4 you are scraping their URLs. Never narrate this. 4. **Integrations are optional, not deferred.** T6 offers DataForSEO, Firecrawl, Notion, Slack, Obsidian as a single menu. Skip is a first-class choice. 5. **Verify creds inline.** If a paste fails, re-ask once. Twice failed, log and move on. The scan still runs. 6. **No filler.** No "welcome", "let's get started", "great", "perfect". No exclamation marks. No em dashes anywhere.

Turn 1: collect URLs

Print verbatim:

SUBSCOPE ONBOARDING  ·  1 / 7
─────────────────────────────

I'll use these URLs to seed your Reddit targeting profile.
Paste the following:

→  Homepage URL
→  Case studies   (optional)
→  Blog / pricing (optional)

One per line.

Wait for input. Accept 1 to N URLs. Warn if more than 8.

Kick off WebFetch on all provided URLs **in parallel and in the background**. Extract:

• H1 / sub-headline / positioning line
• Linked case studies and pricing pages
• Visible competitor names ("alternative to X", "replace Y")
• Pain phrasing from problem statements
• Buyer titles quoted in case studies

Save raw fetch output to `~/.config/subscope/.onboard-draft.json` as you go.

**Background warmup.** As soon as the user pastes URLs, kick off the enrichment warmup in parallel with WebFetch so the DataForSEO competitor list + Firecrawl homepage scrape are cached by the time we reach T5 discovery. Silent no-op if DFS/Firecrawl keys are absent. Substitute `$HOMEPAGE_URL` with the first pasted URL:

cd "$CLAUDE_PLUGIN_ROOT" && PYTHONPATH=engine python3 -c "
from subscope.lib import enrich, store
with store.connect() as conn:
    enrich.warmup_for_onboarding('$HOMEPAGE_URL', conn)
" &

Do not block on this. Do not show any status, recap, or summary. Move straight to T2.

Turn 2: what do you sell

Print verbatim:

SUBSCOPE ONBOARDING  ·  2 / 7
─────────────────────────────

What do you sell?

→  One line is enough.
→  Example: "Reddit lead-gen for B2B SaaS."

Wait for input. Save to scratchpad. No echo, no confirmation. Move to T3.

Turn 3: who buys it

Print verbatim:

SUBSCOPE ONBOARDING  ·  3 / 7
─────────────────────────────

Who buys it?

→  A job title works.
→  Example: "Head of Ops at a SaaS startup."
→  Or just: "RevOps leads."

Wait for input. Save to scratchpad. Move to T4.

Turn 4: what is the pain

Print verbatim:

SUBSCOPE ONBOARDING  ·  4 / 7
─────────────────────────────

What do they complain about right before they find you?

→  A real customer quote is gold.
→  Paraphrase is fine.

Wait for input. Save to scratchpad.

**Run live subreddit discovery before T5.** This calls the engine to find subs where the user's pain phrasing is actively discussed on Reddit. Replaces the old templatish archetype-map seed.

Pipe the answers JSON via stdin so apostrophes / quotes in user input don't break shell quoting. Pass any competitor brands you found in the WebFetch (T1) via `--competitors` as a comma-separated list. These are critical: they generate "replacing X" and "X alternative" queries which dramatically improve sub relevance for Reddit discovery.

cd "$CLAUDE_PLUGIN_ROOT" && python3 -c "
import json
print(json.dumps({
    'what_offering': '''<T2_VALUE>''',
    'who_to_reach':  '''<T3_VALUE>''',
    'pain_quote':    '''<T4_VALUE>''',
}))" | PYTHONPATH=engine python3 -m subscope.cli discover \
  --homepage "$HOMEPAGE_URL" \
  --competitors "<COMMA_SEPARATED_COMPETITOR_BRANDS>" \
  --skip-validation \
  --answers-json -

`--skip-validation` keeps onboarding light: it returns the candidate subs plus a relative `relevance` score (0-100) WITHOUT the per-sub freshness fetches. Onboarding's job is to confirm the sub NAMES; the real `/subscope-run` scan at T7 validates by actually surfacing. This also means fewer Reddit calls during setup.

Substitute:

• `<T2_VALUE>`, `<T3_VALUE>`, `<T4_VALUE>` with the exact answers from the scratchpad
• `<COMMA_SEPARATED_COMPETITOR_BRANDS>` with whatever brands Claude extracted from the user's homepage/case-studies during T1 WebFetch (e.g. `"Zapier,n8n,Make,Bill.com,Apollo.io"`). If no brands were found, pass an empty string.

The triple-quoted strings handle embedded apostrophes safely; `--answers-json -` reads the piped JSON from stdin.

The engine (run with `--skip-validation`) returns JSON with these fields:

• `subs`: ranked candidate subs. Each entry has `name`, `relevance` (0-100, relative match-strength to the offer), `why` (plain-English why-chosen line), `relevance_path` ("competitor"/"noun"), `thread_count`, `sources`, `noise_downranked`, `validation_skipped: true`. (No per-sub freshness fields: validation is deferred to the first scan at T7.)
• `needs_clarification`, `clarifier_reason` (`no_candidates`), `clarifier_prompt`, `discovery_unreachable`, `phase_a_count`, `validation_skipped`

The `relevance` score is a topical match estimate (how strongly the sub's