Borrowing it
Nothing to install: this file belongs to fenjo26/OpenGSC. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fenjo26/OpenGSC/main/.agents/skills/drops-research/SKILL.mdgit clone --depth 1 https://github.com/fenjo26/OpenGSCWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fenjo26/opengsc/drops-research)<a href="https://agentmods.dev/skills/fenjo26/opengsc/drops-research"><img src="https://agentmods.dev/badge/skills/fenjo26/opengsc/drops-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/fenjo26/opengsc/drops-research"><img src="https://agentmods.dev/badge/skills/fenjo26/opengsc/drops-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.00977 |
| Opus 5.5 | $0.00022 | $0.00391 |
| Sonnet 5.5 | $0.00011 | $0.00195 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
drops-research 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 1mo 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenGSC Drops Research
Goal
Turn a raw list of (possibly dropped) domains into a ranked, vetted shortlist: alive names retired for free, free names corroborated by two sources, link history attached, spam and burn-vetoes applied — ending in a buy/pass table a human can act on.
Required inputs
- A domain list (pasted text, CSV, or a donor's refdomains). If none given, ask — the funnel is useless without candidates.
OpenGSC MCP tools
drops_ingest: import the list as a run. Rows are normalised (URLs/www.hosts/IPs handled, everything reduced to its registrable apex); the report says what was rejected and why.drops_prefilter: one bounded slice of DNS resolution. Retires every delegated (alive) domain for free — usually ~90% of the list. Run this before anything else; loop whileremaining > 0anddone: false.drops_check: one bounded slice of the registry stage (RDAP → WHOIS, throttled per zone, ~35s per call). Loop whileremaining > 0. Rules baked into the verdicts: an RDAP 404 is only "free" when WHOIS agrees (corroborated), a refusal is never "taken", and zones with no public registry (.grtoday) come backuncheckable— they need a registrar API and cannot be swept.drops_enrich_wayback: Wayback snapshots for ≤12 domains per call — months archived, first/last seen, days since death. Free.drops_enrich_dr: Ahrefs DR for ≤60 domains per call via the free public endpoint. Free (needs the free DR key configured). Attribution "Domain Rating by Ahrefs" is mandatory in anything you publish.drops_enrich_refdomains: PAID — Ahrefs refdomains/backlink counts (~100 units per domain). Needsconfirm: true. Only for shortlisted rows, never for a whole list.drops_history_ai: PAID — the AI history pass for ≤5 hand-picked domains: three Wayback snapshots, the configured LLM decides clean / topic_shift / spam_period / unknown. Needsconfirm: true.drops_list: the catalogue view — filters, sort, the score, and the funnel counts.
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.
- 1mo ago First seen · 46 lines · 55 tokens per session scan A 9985d56d6169
drops-research is a skill published in the GitHub repository fenjo26/OpenGSC (51 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 977 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-07.
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