According to AlphaMoat, as of 2026-09, 工业化数据处理 has 1,406 downloads and 0 stars — ranked #4,828 of 5,078 AI skills overall, and #383 of 399 in Data Analysis.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 31 | 1.1K | - | - |
| SkillHub ↗ | 206 | 1.4K | - | — |
Platforms count differently and update at different times.
The workflow executes sequentially without a complex scheduler in 4 steps: preprocess-excel (scripts/preprocess_excel.py, converting ./input into ./output/csv) -> csv-to-json-parser (scripts/csv_to_json.py, producing ./output/json) -> jwt-security-layer (scripts/jwt_token.py, with tokens expiring after 30 minutes) -> enterprise-data-submit (scripts/data_submit.py, submitting with BearerToken auth). Model inference parameters are fixed for a low-randomness industrial mode: temperature 0 and top_p 0.05. The error-recovery strategy is a global retry of 3 with a safe_exit fallback, and handlers cover logging errors, saving checkpoints, and alerting the admin; logging runs at INFO level and persists to ./logs/iqc_engine.log, while output is JSON under ./output/final with compression enabled. The skill card's security evidence reports that the skill embeds reusable credentials and sends or stores tokens and business data insecurely, so it should only run in a controlled internal environment after rotating the exposed password, moving credentials to managed secrets, and enforcing HTTPS.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 1.4K | — | - |
| 2026-08 | 1.1K | +9.5% | - |
| 2026-07 | 1.0K | — | - |
| 2026-05 | 734 | — | - |
| 2026-03 | 455 | — | - |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
name: iqc-python-tree version: 3.0.0 description: | 企业工业级 IQC 控制计划解析引擎终极稳定版: Excel → CSV → JSON AST → 安全认证 → 数据提交 author: inspection-planning # ===============================
# 模型推理参数(低随机性工业模式)
# ===============================
model:
temperature: 0
top_p: 0.05
# ===============================
# 工作流执行模式(稳定核心)
# 顺序执行,不使用复杂调度器
# ===============================
workflow:
steps:
# --------------------------------------------------
# Step 1:Excel 工业预处理层(核心稳定区)
# --------------------------------------------------
- name: preprocess-excel
executor: python
script: scripts/preprocess_excel.py
timeout: 120
retry: 2
params:
input_dir: ./input
output_dir: ./output/csv
# --------------------------------------------------
# Step 2:工业语义解析层(控制计划模型化)
# --------------------------------------------------
- name: csv-to-json-parser
executor: python
script: scripts/csv_to_json.py
timeout: 180
retry: 3
params:
input_dir: ./output/csv
output_dir: ./output/json
# --------------------------------------------------
# Step 3:安全认证层(企业安全标准)
# --------------------------------------------------
- name: jwt-security-layer
executor: python
script: scripts/jwt_token.py
timeout: 60
retry: 2
params:
secret_key: STATIC_SECRET_KEY
expire_minutes: 30
# --------------------------------------------------
# Step 4:工业数据提交层(最终出口)
# --------------------------------------------------
- name: enterprise-data-submit
executor: python
script: scripts/data_submit.py
timeout: 120
retry: 3
params:
auth_mode: BearerToken
# ===============================
# 企业异常自愈策略(非常重要)
# ===============================
error_strategy:
global_retry: 3
fallback_mode: safe_exit
handlers:
- log_error
- save_checkpoint
- alert_admin
# ===============================
# 日志审计系统(工业生产必须)
# ===============================
logging:
level: INFO
persist: true
path: ./logs/iqc_engine.log
# ===============================
# 输出策略
# ===============================
output:
format: json
path: ./output/final
compress: trueThe data layer for AdMapix: turn ad and app queries into API calls that return raw JSON only.
Searches the public web through Tavily and returns structured results with links and snippets.
A data-analysis skill that turns databases, spreadsheets, and raw exports into decision-ready conclusions.
A skill that analyzes stocks and cryptocurrencies on Yahoo Finance data and tracks a portfolio.
Manages a local stock watchlist and summarizes recent quotes for its codes from the Tonghuashun stock pages.
全网招中标数据查询与分析助手。当用户涉及以下任何场景时,必须使用此SKILL:查询招标/中标公告、搜索标讯、查找临期/即将到期项目、商机预测、推荐潜在投标供应商、分析公司主营业务/历史中标、查询公司上下游合作客户与供应商、分析竞争对手/竞对企业、查询Top采购单位/Top中标单位/Top中标品牌、招中标数据统计分析(按月/季/年/省份/品牌等维度)、查询品牌型号历史中标单价/价格趋势、市场分析/行业分析/采购寻源/渠道拓展等采购与投标相关场景。即使用户没有提到「知了标讯」,只要涉及招投标、采购、中标、供应商、竞争对手等关键词,都应使用本SKILL。
Track blog and RSS/Atom feed updates from the command line.
Summarises per-model usage cost for Codex or Claude.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.