subscope-run

A daily Reddit scanner that fetches new posts, scores them by relevance and freshness, optionally classifies them with Claude Haiku, removes duplicates, and displays selected results. It can also synchronize results with Notion.

In plain words
What is it for?
Use it for daily discovery of potential buyer or authority conversations, with optional candidate review and Notion syncing. It can run with generic subreddit settings or a personalized configuration created during onboarding.
Why use it?
It turns a large stream of new Reddit discussions into a smaller list of posts related to configured customer problems. A cooling queue prevents the same opportunity from being surfaced too soon.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/dancolta/subscope/run
Any agent
npx skills add dancolta/subscope --skill run
Clone the repo
git clone --depth 1 https://github.com/dancolta/subscope

Made for: Claude Code, Codex.

Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,929 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5 $0.00093 $0.03929
Opus 5 $0.00046 $0.01965
Sonnet 5 $0.00019 $0.00786
Haiku 4.5 $0.00009 $0.00393

Measured 2d ago against content hash 85ca9eb0507c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

subscope-run 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.

skills/run/SKILL.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/subscope-run

Daily Reddit surfacing orchestrator. Python (under engine/) does fetch + gate + score + SQLite + JSON output. This skill is the Claude-side wrapper: it invokes the engine, optionally syncs to Notion (if configured), and prints the inline list to chat.

Preflight

  1. Check whether user has personalized targeting at ~/.config/subscope/subreddits.yml. If missing, the engine still runs using bundled generic defaults, but results will be off-target. Recommend /subscope-onboard (one conversation, ~5 min, includes the first scan) with a one-line nudge: (no personal targeting found, scanning with generic defaults. /subscope-onboard for sharper results.) Proceed with the run unless user explicitly cancels.

Daily run procedure

Step 1: Fetch + candidates (Python engine)

cd "$CLAUDE_PLUGIN_ROOT" && PYTHONPATH=engine python3 -m subscope.cli fetch-score --candidates

Engine output: a single JSON document on stdout with run_id, status, fetched, surfaced, buyer_count, authority_count, subs_skipped_rate_limit, fetch_stats, dropped_counts, surfaces[], inline_table, inline_markdown, and (with --candidates) a candidates[] array plus candidate_count / candidate_total.

candidates[] is the recall pre-filter: every fetched post that cleared the absolute rejects (NSFW, removed/locked, vendor-spam, off-topic-sub, tier-3), each with deterministic features: title, body, url, sub, tier, age_h, kw_hits, matched_kw, names_brand (matched against the user's brand_anchor), question_intent, pain_intent, engagement_available, soft_reason. The engine deliberately does NOT decide relevance for these. You do, in Step 3.5. The engine's own surfaces[]/inline_table are the older lexical-gate output; under judge-first they are a secondary signal, not the chat output.

The status field tells you why a run produced few or no surfaces, so you never show the wrong message:

  • status: "ok" and surfaced > 0 -> normal run, render the table (Step 4).
  • status: "ok" and surfaced == 0 -> Reddit was reachable, today was just quiet. Show the EMPTY-DAY copy below.
  • status: "rate_limited" -> Reddit rate-limited this run (HTTP 429). Some subreddits may have been skipped (subs_skipped_rate_limit says how many), so the list can be partial or empty. This is transient. Render any surfaces you DID get, then show the RATE-LIMITED copy below. Do NOT call this "blocked".
  • status: "blocked" -> every Reddit feed request failed for a non-rate-limit reason (Reddit's edge returned 403, or the network was down). The scan could not read anything. Show the BLOCKED copy below.

Read the full file on GitHub · 207 lines

Changes

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.

  1. 2d ago First seen · 207 lines · 93 tokens per session scan A 85ca9eb0507c

Subscribe to this mod's changes

subscope-run is a skill published in the GitHub repository dancolta/subscope (25 stars, last pushed 21d ago), licensed MIT. It adds 93 tokens to every session and 3,929 once invoked, about $0.0005 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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