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 skills add ThomasMoreAI/legal-skills-open --skill screen-trademarkgit clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote 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/thomasmoreai/legal-skills-open/screen-trademark)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/screen-trademark"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/screen-trademark/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/thomasmoreai/legal-skills-open/screen-trademark"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/screen-trademark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00093 | $0.02772 |
| Opus 5 | $0.00046 | $0.01386 |
| Sonnet 5 | $0.00019 | $0.00554 |
| Haiku 4.5 | $0.00009 | $0.00277 |
Grade A, and why
screen-trademark 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 9d 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 — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Screen Trademark
Screen proposed mark → conflicts + assess distinctiveness pre-filing. Search registries, eval Abercrombie, analyze confusion w/ priors, produce report w/ risk ratings.
Use When
- Pre-adopt new brand|product|service mark
- Rebrand|expand into new goods/services class
- Pre-file TM application (national|EU|intl)
- Eval acquisition w/ TM portfolios
- Pre-launch product new geo w/ existing brand
- C&D received → assess exposure
In
- Required: Proposed mark (word|figurative|both)
- Required: Goods/services covered (plain desc)
- Required: Geo scope (US|EU|specific|global)
- Optional: Nice classification classes if known
- Optional: First-use date (US common law priority)
- Optional: Known competing marks
- Optional: Word|figurative|composite
Do
Step 1: Define Mark + Goods/Services
Establish exact what + which classes.
- Record mark precisely:
- Word: text as appears (case for figurative)
- Figurative: visual elements, colors, stylization
- Composite: both
- Describe goods/services plain
- Nice classification:
- TMclass (https://tmclass.tmdn.org/)
- Search keyword → correct class + acceptable terms
- Most marks 1-3 classes; ID all relevant
- Adjacent (Class 9 software vs Class 42 SaaS)
- Geo scope:
- US (USPTO), EU (EUIPO), intl (WIPO Madrid), national offices
- US = first-to-use; EU = first-to-file
→ Record of mark, goods/services, Nice classes, jurisdictions. Defines search scope.
If err: Nice ambiguous → err on more classes. Broader screen safer than missing adjacent conflict.
Step 2: Search TM Databases
Identical + similar across registries.
- Identical first:
- TMview (https://www.tmdn.org/tmview/): EU + national
- WIPO Global Brand DB (https://branddb.wipo.int/): intl regs
- USPTO TESS / Trademark Center (https://tsdr.uspto.gov/): US
- National: DPMAregister (DE), UKIPO (UK), CIPO (CA)
- Similar — expand:
- Phonetic ("Kool" vs "Cool", "Lyft" vs "Lift")
- Visual ("Adidaz" vs "Adidas")
- Transliterations + translations
- Common prefix|suffix added|removed
- Plurals, possessives, abbrev
- Filter:
- Status: live|registered + pending (ignore dead|cancelled)
- Goods/services: same|related Nice
- Geo: target jurisdictions
- Per potential conflict record:
- Mark text + reg/app number
- Owner + jurisdiction
- Nice classes + goods/services
- Status (registered, pending, opposed) + dates
- Identical|similar (and how: phonetic|visual|conceptual)
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.
- 9d ago First seen · 263 lines · 93 tokens per session scan A a402760aa75b
screen-trademark is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (72 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 93 tokens to every session and 2,772 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 2026-09-03.
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