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.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- 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 | $0.00024 | $0.00498 |
| Sonnet 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 8d 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.
- 8d 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 (1,763 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. 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…
paid-ads-amazon
Plan and review Amazon Ads with margin-aware ACoS, product, and search-term guardrails. Use for Amazon advertising, Sponsored Products, Sponsored Brands, Sponsored Display, ASIN targeting, Amazon ACoS, or Amazon Ads performance exports.
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-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.
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.