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Agent skill

Scientific DB Uspto Database

by affaan-m in affaan-m/ECC

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

MITAuto-check passedLegal & Compliance

Install Scientific DB Uspto Database

skills CLI
$ npx skills add affaan-m/ECC --skill scientific-db-uspto-database -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC scientific-db-uspto-database --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scientific-db-uspto-database .claude/skills/scientific-db-uspto-database && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
scientific-db-uspto-database
GitHub stars
277k
Used in
1 other repo
Token cost
~1.6k tokens
SKILL.md length
631 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

  • Works in 5 steps: Identify the endpoint from the current… → Build a JSON query with explicit filters. → Request only the fields needed for the… → …
  • A task needs official United States patent
  • SKILL.md covers When to Use, Source Selection, Authentication and Secrets and PatentSearch Workflow, plus 6 more sections
  • Reaches search.patentsview.org; needs PATENTSVIEW_API_KEY and API_KEY

What it does

Scientific DB Uspto Database is an agent skill from affaan-m/ECC. USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs. Use when a task needs official United States patent or trademark records from USPTO systems.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Legal & Compliance, covering Intellectual property. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • A task needs official United States patent
  • Trademark records from USPTO systems

Example prompts

  • “/scientific-db-uspto-database”

Requirements

  • Python 3
  • A credential in USPTO_API_KEY
  • A credential in PATENTSVIEW_API_KEY

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Identify the endpoint from the current PatentSearch reference or Swagger UI.
  2. Build a JSON query with explicit filters.
  3. Request only the fields needed for the analysis.
  4. Sort and paginate deterministically.
  5. Record the endpoint, query body, date, data currency note, and result count.

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash, python and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • search.patentsview.org

    Also links to:

    • developer.uspto.gov
    • data.uspto.gov

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • PATENTSVIEW_API_KEY
    • API_KEY
    • USPTO_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scientific DB Uspto Database loads about 1.6k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 631 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 631 words, ~1,583 tokens.

Download SKILL.mdSave it as .claude/skills/scientific-db-uspto-database/SKILL.md (or your agent's skills folder).
name
scientific-db-uspto-database
description
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs. Use when a task needs official United States patent or trademark records from USPTO systems.
metadata.origin
community

USPTO Database

Use this skill when a task needs official United States patent or trademark records from USPTO systems.

When to Use

  • Searching granted patents or pre-grant publications.
  • Checking patent application status, file-wrapper data, assignments, or public prosecution history.
  • Looking up trademark status, documents, or assignment history.
  • Building reproducible prior-art, portfolio, or IP landscape research logs.
  • Comparing USPTO records with secondary tools such as Google Patents, Lens.org, Semantic Scholar, or company patent pages.

Do not use this skill to give legal advice. Treat it as a data-gathering and record-verification workflow.

Source Selection

Prefer official USPTO or USPTO-supported surfaces first:

  • Open Data Portal (ODP): current home for migrated USPTO datasets and APIs.
  • Patent File Wrapper: public patent application bibliographic data and file wrapper records.
  • PatentSearch API: PatentsView search API for granted patents and pre-grant publication datasets.
  • TSDR Data API: trademark status and document retrieval.
  • Patent and Trademark Assignment Search: ownership transfer records.
  • PTAB data in ODP: Patent Trial and Appeal Board proceedings.

Use secondary sources only as convenience indexes. When the answer matters, cross-check the official record.

Authentication and Secrets

Many USPTO API flows require an API key. Store keys in environment variables or a secret manager, never in committed files or pasted transcripts.

Common environment names:

bash
export USPTO_API_KEY="..."
export PATENTSVIEW_API_KEY="..."

For PatentSearch, send the key with the X-Api-Key header. For TSDR, follow the current USPTO API Manager instructions and rate-limit guidance.

PatentSearch Workflow

Use PatentSearch for broad patent and pre-grant publication search when the question is about trends, inventors, assignees, classifications, dates, or portfolio slices.

Workflow:

  1. Identify the endpoint from the current PatentSearch reference or Swagger UI.
  2. Build a JSON query with explicit filters.
  3. Request only the fields needed for the analysis.
  4. Sort and paginate deterministically.
  5. Record the endpoint, query body, date, data currency note, and result count.

Python request skeleton:

python
import os
import requests

API_KEY = os.environ["PATENTSVIEW_API_KEY"]
BASE = "https://search.patentsview.org/api/v1"

payload = {
    "q": {
        "_and": [
            {"patent_date": {"_gte": "2024-01-01"}},
            {"assignees.assignee_organization": {"_text_any": ["Google", "Alphabet"]}},
        ]
    },
    "f": ["patent_id", "patent_title", "patent_date"],
    "s": [{"patent_date": "desc"}],
    "o": {"per_page": 100, "page": 1},
}

response = requests.post(
    f"{BASE}/patent/",
    headers={"X-Api-Key": API_KEY, "Content-Type": "application/json"},
    json=payload,
    timeout=30,
)
response.raise_for_status()
print(response.json())

Before reusing a query, verify current endpoint names, field paths, request parameters, and API-key availability in the live PatentSearch docs.

Trademark/TSDR Workflow

Use TSDR when the task needs trademark case status, documents, images, owner history, or prosecution events.

Workflow:

  1. Normalize the serial number or registration number.
  2. Check the current TSDR API instructions and required API-key header.
  3. Fetch status first, then documents only if needed.
  4. Respect the lower rate limit for PDF, ZIP, and multi-case downloads.
  5. Capture retrieval date and serial/registration identifier in the output.

For large trademark pulls, prefer documented bulk-data flows rather than screen-scraping public pages.

Show full SKILL.md (227 more words)Show less

File Wrapper and Prosecution History

For application status, transaction history, and prosecution documents:

  • Start with ODP Patent File Wrapper search.
  • Use exact identifiers when available: application number, publication number, patent number, or party name.
  • Record whether the record is a granted patent, pre-grant publication, or pending application.
  • Cross-check document dates and status against the record detail page before citing them.

Assignment Workflow

For patent or trademark ownership:

  1. Search official assignment data by patent/application/registration number, assignor, assignee, or reel/frame when available.
  2. Record conveyance text, execution date, recordation date, and parties.
  3. Distinguish assignment records from current legal ownership conclusions.
  4. If ownership is material, flag the result for attorney or subject-matter review.

Reproducible Output

Every USPTO research pass should include a log table:

markdown
| Source | Date searched | Identifier/query | Filters | Results | Notes |
| --- | --- | --- | --- | ---: | --- |
| PatentSearch | 2026-05-11 | `assignee=Alphabet AND date>=2024` | patent endpoint | 118 | API docs checked before run |
| TSDR | 2026-05-11 | `serial=90000000` | status only | 1 | API-key flow, no document bulk pull |

For final writeups, separate:

  • official record facts
  • inferred analysis
  • secondary-source convenience matches
  • unresolved gaps or records that require legal review

Review Checklist

  • Did you use an official USPTO or USPTO-supported source first?
  • Did you verify current endpoint and field names before running code?
  • Are API keys kept out of files, shell history, and output logs?
  • Does the query log include the date searched and exact request shape?
  • Are rate limits respected?
  • Are legal conclusions avoided or explicitly escalated?
  • Are secondary sources labeled as secondary?

References

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/scientific-db-uspto-database of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Scientific DB Uspto Database next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Scientific DB Uspto Database compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scientific DB Uspto Database this skillaffaan-m/ECC277k1 repos~1.6kAutomated safety check: PassMIT
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Paper To Cn Patentsnipp-zha/Paper-to-patent-Skill1071 repos~959Automated safety check: PassNone
Patent Examinegfodor/legal-skills393—~4.8kAutomated safety check: PassGPL-3.0
Patent Auditgfodor/legal-skills393—~2.9kAutomated safety check: PassGPL-3.0
Replica BrandJakeschincariol/replica-skill1.4k—~1.1kAutomated safety check: PassMIT

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Categories

Questions about Scientific DB Uspto Database

What does Scientific DB Uspto Database do?

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs. Scientific DB Uspto Database is an agent skill from affaan-m/ECC. USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

When should I use Scientific DB Uspto Database?

Scientific DB Uspto Database fits situations like: A task needs official United States patent; trademark records from USPTO systems.

How do I install Scientific DB Uspto Database in Claude Code?

Run `npx skills add affaan-m/ECC --skill scientific-db-uspto-database -a claude-code`. Or copy the skill folder (skills/scientific-db-uspto-database in affaan-m/ECC) into .claude/skills/scientific-db-uspto-database in your project. Claude Code loads it when a task matches its description.

How do I install Scientific DB Uspto Database in Codex?

Run `npx skills add affaan-m/ECC --skill scientific-db-uspto-database -a codex`. Or copy the skill folder (skills/scientific-db-uspto-database in affaan-m/ECC) into .agents/skills/scientific-db-uspto-database in your project. Codex loads it when a task matches its description.

Can I use Scientific DB Uspto Database in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill scientific-db-uspto-database -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scientific-db-uspto-database, .gemini/skills/scientific-db-uspto-database, .github/skills/scientific-db-uspto-database and .opencode/skills/scientific-db-uspto-database in your project.

What does Scientific DB Uspto Database need to run?

Going by SKILL.md and its folder, Scientific DB Uspto Database needs credentials named PATENTSVIEW_API_KEY, API_KEY and USPTO_API_KEY. Our summary lists: Python 3; A credential in USPTO_API_KEY; A credential in PATENTSVIEW_API_KEY.

Does Scientific DB Uspto Database access the network?

SKILL.md names 3 domains. In commands or code: search.patentsview.org; the agent is likely to contact it when it follows the instructions. As links in the text: developer.uspto.gov and data.uspto.gov. This is read from the text; nothing was executed.

Is Scientific DB Uspto Database safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Scientific DB Uspto Database use?

Scientific DB Uspto Database is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scientific DB Uspto Database use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Scientific DB Uspto Database?

Skills that share tags, products or a category with Scientific DB Uspto Database: Paper to Chinese Patent Drafter (Yuan1z0825/nature-skills, 47k stars), Paper To Cn Patent (snipp-zha/Paper-to-patent-Skill, 107 stars), Patent Examine (gfodor/legal-skills, 393 stars) and Patent Audit (gfodor/legal-skills, 393 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scientific DB Uspto Database?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.