OPC Skills is a collection of reusable instruction folders, scripts, and resources that extend coding agents with specialized tasks for solopreneurs and one-person companies. Its skills cover areas such as search optimization, demand research, domain discovery, branding, social-media assets, and platform-specific research. The catalogue entries are the project's own skills, plugins, and hook.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ReScienceLab/opc-skillsnpx agentmods add skills/resciencelab/opc-skills/domain-hunterWrote 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/resciencelab/opc-skills/domain-hunter)<a href="https://agentmods.dev/skills/resciencelab/opc-skills/domain-hunter"><img src="https://agentmods.dev/badge/skills/resciencelab/opc-skills/domain-hunter/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/resciencelab/opc-skills/domain-hunter"><img src="https://agentmods.dev/badge/skills/resciencelab/opc-skills/domain-hunter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00048 | $0.00997 |
| Opus 5.5 | $0.00019 | $0.00399 |
| Sonnet 5.5 | $0.00010 | $0.00199 |
| Haiku 4.5 | $0.00005 | $0.00100 |
Grade A, and why
domain-hunter 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- domain-hunter — 92% identical, 30 lines differ
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain Hunter Skill
Help users find and purchase domain names at the best price.
Workflow
Step 1: Generate Domain Ideas & Check Availability
Based on the user's project description, generate 5-10 creative domain name suggestions.
Guidelines:
- Keep names short (under 15 characters)
- Make them memorable and brandable
- Consider:
{action}{noun},{noun}{suffix},{prefix}{keyword} - Common suffixes: app, io, hq, ly, ify, now, hub
CRITICAL: Always check availability before presenting domains to user!
Use one of these methods to verify availability:
Method 1: WHOIS check (most reliable)
# Check if domain is available via whois
whois {domain}.{tld} 2>/dev/null | grep -i "no match\|not found\|available\|no data found" && echo "AVAILABLE" || echo "TAKEN"
Method 2: Registrar search page Open the registrar's domain search in browser to verify:
open "https://www.spaceship.com/domains/?search={domain}.{tld}"
Method 3: Bulk check via Namecheap/Dynadot
- https://www.namecheap.com/domains/registration/results/?domain={domain}
- https://www.dynadot.com/domain/search?domain={domain}
IMPORTANT:
- Only present domains that are confirmed AVAILABLE
- Mark any uncertain domains with "(unverified)"
- Present suggestions to user and wait for confirmation before proceeding
- Ask user to pick their preferred options or provide feedback
- Only move to Step 2 after user approves domain name(s)
Step 2: Compare Prices
Use WebSearch to find current prices:
WebSearch: "cheapest .{tld} domain registrar 2026 site:tld-list.com"
WebSearch: ".{tld} domain price comparison tldes.com"
Key price comparison sites:
- tld-list.com/tld/{tld}
- tldes.com/{tld}
- domaintyper.com/{tld}-domain
Step 3: Find Promo Codes
Use Twitter skill to search registrar accounts:
cd <twitter_skill_directory>
python3 scripts/search_tweets.py "from:{registrar} promo code" --type Latest --limit 15
python3 scripts/search_tweets.py "{registrar} promo code coupon" --type Latest --limit 15
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 117 lines · 48 tokens per session scan A 46d03aa4ae64
domain-hunter is a skill published in the GitHub repository ReScienceLab/opc-skills (1,873 stars, last pushed yesterday), licensed Apache-2.0. It adds 48 tokens to every session and 997 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 2026-08-30.
Other skills, from other repositories
product-feed-optimizer
Use when the user asks to "optimize my Shopping feed", "fix product disapprovals", "improve product titles/attributes", or "build feed-driven PMax asset groups"; audits and rewrites the Shopping/Performance Max product feed — title/description patterns, required and recommended attributes, GTIN/availability/price…
product-image-processor
Download, resize, and remove backgrounds from product images at scale. Use when the user asks to "process product images", batch-download images from the schedule, strip backgrounds, or standardize product photos.
product-spec-bulk-fetch
Extract structured FF&E specs from a list of product URLs into a schedule. Use to pull or bulk-import product-page data; not for PDF catalogs.
product-match
Find visually or functionally similar products from an image, name, or description. Use when the user asks to "find something like this", match a product from a photo, or source alternates to a given item.
product-pair
Suggest complementary products that pair well with a given item — side tables for sofas, task lights for desks, etc. Use when the user asks "what goes with" a product, wants coordinating pieces, or asks to complete a furniture grouping.
ai-slop
Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. Use as the reference rubric when building or reviewing marketing sites, product interfaces, dashboards, portfolios, or e-commerce pages, especially alongside…