Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/dancolta/subscope/onboardnpx skills add dancolta/subscope --skill onboardgit clone --depth 1 https://github.com/dancolta/subscopeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00128 | $0.05789 |
| Opus 5 | $0.00064 | $0.02894 |
| Sonnet 5 | $0.00026 | $0.01158 |
| Haiku 4.5 | $0.00013 | $0.00579 |
Grade A, and why
subscope-onboard scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
import base64, json, urllib.request, yaml How it starts
The opening of the file, as written. The whole thing — 530 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/subscope-onboard
First-run setup. Seven turns, plain questions, one confirmation, optional integrations, first scan.
Operating principles
- 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.
- One thing per turn. Each chat message asks for exactly one input or shows exactly one summary.
- WebFetch silently in the background. While the user answers turn 2, 3, 4 you are scraping their URLs. Never narrate this.
- Integrations are optional, not deferred. T6 offers DataForSEO, Firecrawl, Notion, Slack, Obsidian as a single menu. Skip is a first-class choice.
- Verify creds inline. If a paste fails, re-ask once. Twice failed, log and move on. The scan still runs.
- 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)
" &
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 530 lines · 128 tokens per session scan A ff9551658551
subscope-onboard is a skill published in the GitHub repository dancolta/subscope (25 stars, last pushed 21d ago), licensed MIT. It adds 128 tokens to every session and 5,789 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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