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/judgenpx skills add dancolta/subscope --skill judgegit 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 | $0.00077 | $0.01238 |
| Opus 5 | $0.00039 | $0.00619 |
| Sonnet 5 | $0.00015 | $0.00248 |
| Haiku 4.5 | $0.00008 | $0.00124 |
Grade A, and why
subscope-judge scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/subscope-judge
Interactive single-surface classifier. Designed for the workflow where you scan today's /subscope-run output, hit one or two surfaces that feel borderline, and want a structured judgment before deciding whether to reply.
Why this exists separately from bulk classification: bulk LLM classification of every regex-passing post requires an Anthropic API key (~$0.50/day at 5K posts/day, cheap but not free). The judge skill uses your Claude Code subscription directly — no API key, no subprocess, no extra cost. It's the right tool for "I want a verdict on these 2 posts" not "grade every post in today's list."
When to invoke
The user has just seen /subscope-run output and asks something like:
/subscope-judge 3— surface number from today's list- "is surface #5 actually a real lead?"
- "classify the HubSpot post"
- "judge this: https://reddit.com/comments/abc123/"
Procedure
Step 1 — Identify the target surface
Three paths the user might take:
A. Surface number from today's list. The most recent inline_markdown from /subscope-run is in your conversation context. Find the surface in the numbered list by index. Extract: post URL, title, body, subreddit.
B. Reddit URL pasted. Read the post via the engine's keyless RSS fetcher. Pass the URL through an environment variable (never interpolate it into the Python source, so a quote or special char in the URL cannot break the command):
cd "$CLAUDE_PLUGIN_ROOT" && PYTHONPATH=engine REDDIT_URL="$REDDIT_URL" python3 -c "
import os, sys, json
from subscope.lib import reddit
post = reddit.fetch_post(os.environ['REDDIT_URL'])
if not post:
print('Could not reach that post. Check the URL, or paste the title and body directly and I will judge from that.', file=sys.stderr)
sys.exit(1)
print(json.dumps({'subreddit': post['subreddit'], 'title': post['title'], 'body': (post['body'] or '')[:800]}))
"
fetch_post handles id extraction, validation, and the dual-host RSS failover internally. If it returns nothing (post removed, deleted, or Reddit unreachable), fall back to Path C: ask the user to paste the title and body.
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 · 107 lines · 77 tokens per session scan A 9ce0734d6c2f
subscope-judge is a skill published in the GitHub repository dancolta/subscope (25 stars, last pushed 21d ago), licensed MIT. It adds 77 tokens to every session and 1,238 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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