docs: salvage USPTO and gget skills

.claude-plugin/marketplace.json

@@ -11,7 +11,7 @@
     {
       "name": "ecc",
       "source": "./",
-      "description": "The most comprehensive Claude Code plugin — 53 agents, 200 skills, 69 legacy command shims, selective install profiles, and production-ready hooks for TDD, security scanning, code review, and continuous learning",
+      "description": "The most comprehensive Claude Code plugin — 53 agents, 202 skills, 69 legacy command shims, selective install profiles, and production-ready hooks for TDD, security scanning, code review, and continuous learning",
       "version": "2.0.0-rc.1",
       "author": {
         "name": "Affaan Mustafa",

.claude-plugin/plugin.json

@@ -1,7 +1,7 @@
 {
   "name": "ecc",
   "version": "2.0.0-rc.1",
-  "description": "Battle-tested Claude Code plugin for engineering teams — 53 agents, 200 skills, 69 legacy command shims, production-ready hooks, and selective install workflows evolved through continuous real-world use",
+  "description": "Battle-tested Claude Code plugin for engineering teams — 53 agents, 202 skills, 69 legacy command shims, production-ready hooks, and selective install workflows evolved through continuous real-world use",
   "author": {
     "name": "Affaan Mustafa",
     "url": "https://x.com/affaanmustafa"

AGENTS.md

@@ -1,6 +1,6 @@
 # Everything Claude Code (ECC) — Agent Instructions
 
-This is a **production-ready AI coding plugin** providing 53 specialized agents, 200 skills, 69 commands, and automated hook workflows for software development.
+This is a **production-ready AI coding plugin** providing 53 specialized agents, 202 skills, 69 commands, and automated hook workflows for software development.
 
 **Version:** 2.0.0-rc.1
 
@@ -146,7 +146,7 @@ Troubleshoot failures: check test isolation → verify mocks → fix implementat
 
 ```
 agents/          — 53 specialized subagents
-skills/          — 200 workflow skills and domain knowledge
+skills/          — 202 workflow skills and domain knowledge
 commands/        — 69 slash commands
 hooks/           — Trigger-based automations
 rules/           — Always-follow guidelines (common + per-language)

README.md

@@ -351,7 +351,7 @@ If you stacked methods, clean up in this order:
 /plugin list ecc@ecc
 ```
 
-**That's it!** You now have access to 53 agents, 200 skills, and 69 legacy command shims.
+**That's it!** You now have access to 53 agents, 202 skills, and 69 legacy command shims.
 
 ### Dashboard GUI
 
@@ -1341,7 +1341,7 @@ The configuration is automatically detected from `.opencode/opencode.json`.
 |---------|-------------|----------|--------|
 | Agents | PASS: 53 agents | PASS: 12 agents | **Claude Code leads** |
 | Commands | PASS: 69 commands | PASS: 31 commands | **Claude Code leads** |
-| Skills | PASS: 200 skills | PASS: 37 skills | **Claude Code leads** |
+| Skills | PASS: 202 skills | PASS: 37 skills | **Claude Code leads** |
 | Hooks | PASS: 8 event types | PASS: 11 events | **OpenCode has more!** |
 | Rules | PASS: 29 rules | PASS: 13 instructions | **Claude Code leads** |
 | MCP Servers | PASS: 14 servers | PASS: Full | **Full parity** |
@@ -1446,7 +1446,7 @@ ECC is the **first plugin to maximize every major AI coding tool**. Here's how e
 |---------|------------|------------|-----------|----------|
 | **Agents** | 53 | Shared (AGENTS.md) | Shared (AGENTS.md) | 12 |
 | **Commands** | 69 | Shared | Instruction-based | 31 |
-| **Skills** | 200 | Shared | 10 (native format) | 37 |
+| **Skills** | 202 | Shared | 10 (native format) | 37 |
 | **Hook Events** | 8 types | 15 types | None yet | 11 types |
 | **Hook Scripts** | 20+ scripts | 16 scripts (DRY adapter) | N/A | Plugin hooks |
 | **Rules** | 34 (common + lang) | 34 (YAML frontmatter) | Instruction-based | 13 instructions |

README.zh-CN.md

@@ -160,7 +160,7 @@ Copy-Item -Recurse rules/typescript "$HOME/.claude/rules/"
 /plugin list ecc@ecc
 ```
 
-**完成！** 你现在可以使用 53 个代理、200 个技能和 69 个命令。
+**完成！** 你现在可以使用 53 个代理、202 个技能和 69 个命令。
 
 ### multi-* 命令需要额外配置
 

docs/zh-CN/AGENTS.md

@@ -1,6 +1,6 @@
 # Everything Claude Code (ECC) — 智能体指令
 
-这是一个**生产就绪的 AI 编码插件**，提供 53 个专业代理、200 项技能、69 条命令以及自动化钩子工作流，用于软件开发。
+这是一个**生产就绪的 AI 编码插件**，提供 53 个专业代理、202 项技能、69 条命令以及自动化钩子工作流，用于软件开发。
 
 **版本:** 2.0.0-rc.1
 
@@ -147,7 +147,7 @@
 
 ```
 agents/          — 53 个专业子代理
-skills/          — 199 个工作流技能和领域知识
+skills/          — 202 个工作流技能和领域知识
 commands/        — 69 个斜杠命令
 hooks/           — 基于触发的自动化
 rules/           — 始终遵循的指导方针（通用 + 每种语言）

docs/zh-CN/README.md

@@ -224,7 +224,7 @@ Copy-Item -Recurse rules/typescript "$HOME/.claude/rules/"
 /plugin list ecc@ecc
 ```
 
-**搞定！** 你现在可以使用 53 个智能体、200 项技能和 69 个命令了。
+**搞定！** 你现在可以使用 53 个智能体、202 项技能和 69 个命令了。
 
 ***
 
@@ -1134,7 +1134,7 @@ opencode
 |---------|-------------|----------|--------|
 | 智能体 | PASS: 53 个 | PASS: 12 个 | **Claude Code 领先** |
 | 命令 | PASS: 69 个 | PASS: 31 个 | **Claude Code 领先** |
-| 技能 | PASS: 200 项 | PASS: 37 项 | **Claude Code 领先** |
+| 技能 | PASS: 202 项 | PASS: 37 项 | **Claude Code 领先** |
 | 钩子 | PASS: 8 种事件类型 | PASS: 11 种事件 | **OpenCode 更多！** |
 | 规则 | PASS: 29 条 | PASS: 13 条指令 | **Claude Code 领先** |
 | MCP 服务器 | PASS: 14 个 | PASS: 完整 | **完全对等** |
@@ -1242,7 +1242,7 @@ ECC 是**第一个最大化利用每个主要 AI 编码工具的插件**。以
 |---------|------------|------------|-----------|----------|
 | **智能体** | 53 | 共享 (AGENTS.md) | 共享 (AGENTS.md) | 12 |
 | **命令** | 69 | 共享 | 基于指令 | 31 |
-| **技能** | 200 | 共享 | 10 (原生格式) | 37 |
+| **技能** | 202 | 共享 | 10 (原生格式) | 37 |
 | **钩子事件** | 8 种类型 | 15 种类型 | 暂无 | 11 种类型 |
 | **钩子脚本** | 20+ 个脚本 | 16 个脚本 (DRY 适配器) | N/A | 插件钩子 |
 | **规则** | 34 (通用 + 语言) | 34 (YAML 前页) | 基于指令 | 13 条指令 |

manifests/install-modules.json

@@ -297,6 +297,8 @@
         "skills/exa-search",
         "skills/research-ops",
         "skills/scientific-db-pubmed-database",
+        "skills/scientific-db-uspto-database",
+        "skills/scientific-pkg-gget",
         "skills/scientific-thinking-literature-review",
         "skills/scientific-thinking-scholar-evaluation"
       ],

package.json

@@ -214,6 +214,8 @@
     "skills/remotion-video-creation/",
     "skills/research-ops/",
     "skills/scientific-db-pubmed-database/",
+    "skills/scientific-db-uspto-database/",
+    "skills/scientific-pkg-gget/",
     "skills/scientific-thinking-literature-review/",
     "skills/scientific-thinking-scholar-evaluation/",
     "skills/returns-reverse-logistics/",

skills/scientific-db-uspto-database/SKILL.md

@@ -0,0 +1,177 @@
+---
+name: uspto-database
+description: USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
+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.
+
+## 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
+
+- [USPTO APIs catalog](https://developer.uspto.gov/api-catalog)
+- [USPTO Open Data Portal](https://data.uspto.gov/)
+- [PatentSearch API reference](https://search.patentsview.org/docs/docs/Search%20API/SearchAPIReference/)
+- [PatentSearch API updates](https://search.patentsview.org/docs/)
+- [TSDR API bulk download FAQ](https://developer.uspto.gov/faq/tsdr-api-bulk-download)

skills/scientific-pkg-gget/SKILL.md

@@ -0,0 +1,166 @@
+---
+name: gget
+description: gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.
+origin: community
+---
+
+# gget
+
+Use this skill when a task needs quick bioinformatics lookup across genomic
+reference databases with the `gget` CLI or Python package.
+
+## When to Use
+
+- Finding Ensembl IDs, gene metadata, transcript details, or sequences.
+- Running quick BLAST or BLAT lookups without building a full local pipeline.
+- Fetching reference genome links and annotations from Ensembl.
+- Querying protein structure, pathway, cancer, expression, or disease-association
+  modules through a single interface.
+- Creating a reproducible first-pass evidence log before moving to heavier
+  tools such as Biopython, Snakemake, Nextflow, BLAST+, or database-specific
+  clients.
+
+Use a dedicated workflow instead of `gget` when the task requires regulated
+clinical interpretation, high-throughput production pipelines, or fine-grained
+control over database versions and local indexes.
+
+## Installation
+
+Use a clean Python environment.
+
+```bash
+python -m venv .venv
+. .venv/bin/activate
+python -m pip install --upgrade pip
+python -m pip install --upgrade gget
+gget --help
+```
+
+If `uv` is available:
+
+```bash
+uv venv
+. .venv/bin/activate
+uv pip install gget
+```
+
+Before relying on an older environment, upgrade `gget` and re-check the module
+docs. The upstream databases queried by `gget` change over time.
+
+## Basic Patterns
+
+CLI shape:
+
+```bash
+gget <module> [arguments] [options]
+```
+
+Python shape:
+
+```python
+import gget
+
+result = gget.search(["BRCA1"], species="human")
+print(result)
+```
+
+Common workflow:
+
+1. Identify the species, assembly, gene ID type, and database needed.
+2. Check the current module documentation for arguments.
+3. Run a small query first.
+4. Save output with an explicit filename and date.
+5. Record module name, version, arguments, and database assumptions.
+
+## Common Modules
+
+Use current upstream docs for exact arguments. These modules are common first
+choices:
+
+- `gget search`: find Ensembl IDs from search terms.
+- `gget info`: retrieve metadata for Ensembl, UniProt, or related IDs.
+- `gget seq`: fetch nucleotide or amino-acid sequences.
+- `gget ref`: retrieve reference genome download links.
+- `gget blast`: run a quick BLAST query.
+- `gget blat`: locate a sequence against supported genome assemblies.
+- `gget muscle`: run multiple sequence alignment.
+- `gget diamond`: run local sequence alignment against reference sequences.
+- `gget alphafold` and `gget pdb`: inspect protein-structure references.
+- `gget enrichr`, `gget opentargets`, `gget archs4`, `gget bgee`, `gget cbio`,
+  and `gget cosmic`: explore enrichment, target, expression, cancer, and disease
+  association data.
+
+Do not assume every module supports every Python version or dependency set.
+Some optional scientific dependencies have narrower version support than the
+core package.
+
+## Quick Examples
+
+Find genes:
+
+```bash
+gget search -s human brca1 dna repair -o brca1-search.json
+```
+
+Fetch gene metadata:
+
+```bash
+gget info ENSG00000012048 -o brca1-info.json
+```
+
+Fetch a sequence:
+
+```bash
+gget seq ENSG00000012048 -o brca1-seq.fa
+```
+
+Run a small BLAST query:
+
+```bash
+gget blast "MEEPQSDPSVEPPLSQETFSDLWKLLPEN" -l 10 -o blast-results.json
+```
+
+Python example:
+
+```python
+import gget
+
+genes = gget.search(["BRCA1", "DNA repair"], species="human")
+info = gget.info(["ENSG00000012048"])
+sequence = gget.seq("ENSG00000012048")
+```
+
+## Reproducibility Log
+
+For scientific outputs, include enough metadata to replay the query.
+
+```markdown
+| Date | gget version | Module | Query | Species/assembly | Output | Notes |
+| --- | --- | --- | --- | --- | --- | --- |
+| 2026-05-11 | `gget --version` | search | `BRCA1 DNA repair` | human | `brca1-search.json` | Docs checked before run |
+```
+
+Also record:
+
+- Python version and environment manager.
+- Any optional dependency installed through `gget setup`.
+- Database-specific identifiers returned by the query.
+- Whether output is JSON, CSV, FASTA, or a DataFrame export.
+- Any failures that were resolved by upgrading `gget`.
+
+## Review Checklist
+
+- Did you upgrade or verify the installed `gget` version?
+- Did you check the current upstream module docs before using arguments?
+- Is the species or assembly explicit?
+- Are identifiers preserved exactly, including Ensembl/UniProt prefixes?
+- Is the result labeled as database output rather than clinical interpretation?
+- Is the query reproducible from the saved command or Python snippet?
+- Are optional dependencies installed in an isolated environment?
+
+## References
+
+- [gget documentation](https://pachterlab.github.io/gget/)
+- [gget updates](https://pachterlab.github.io/gget/en/updates.html)
+- [gget GitHub repository](https://github.com/pachterlab/gget)
+- [gget Bioinformatics paper](https://doi.org/10.1093/bioinformatics/btac836)