投放数据分析
v1.0.1基于超级直播、淘宝直播及财务数据,自动识别文件并计算ROI、转化率等关键指标,生成综合投放数据分析报告。
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the code: modules read local 超级直播/淘宝直播/财务 files, compute ROI and other KPIs, and generate HTML/CSV reports. No network calls or external services are required. Minor mismatch: SKILL.md and examples refer to environment variables (TOUFANG_DATE_RANGE, TOUFANG_DATA_DIR, TOUFANG_OUTPUT_DIR) and a CLI name '投放数据分析', but the package metadata declares no required env vars and the provided entry points are Python scripts (main.py / clawhub_main.py). This is a documentation/configuration inconsistency, not an obvious malicious indicator.
Instruction Scope
Runtime instructions and code operate on local filesystem paths (default /Users/zhouhao/Documents/投放数据 and ~/Desktop outputs) and use environment variables if present. They do not read unrelated system config or network endpoints. Notes: SKILL.md shows single env var examples but the code references several optional env vars (TOUFANG_DATA_DIR, TOUFANG_OUTPUT_DIR, TOUFANG_METRICS, TOUFANG_OUTPUT_FORMAT). The README/usage examples mention a CLI name that isn't implemented as a packaged command — usage is via python main.py.
Install Mechanism
No install spec or remote downloads are used. Dependencies are listed in requirements.txt (pandas, numpy, chardet, openpyxl, etc.), which is appropriate for the stated purpose. No URLs, archive extraction, or third-party install hooks are present.
Credentials
The skill requests no credentials and does not access networked secrets. It does read and write local files (including user document and Desktop paths) which is expected given the purpose. Minor concern: the manifest does not declare any required env vars even though SKILL.md and code expect optional env vars; this is a transparency/configuration gap but not excessive privilege.
Persistence & Privilege
always is false and the skill does not attempt to modify other skills or system-wide settings. It creates output files in the user's configured output directory (default Desktop) and otherwise runs transient analysis — this matches normal behavior for a data-processing tool.
Assessment
This skill appears to be what it says: a local data-processing/reporting tool that reads CSV/XLSX files, computes KPIs, and writes HTML/CSV reports. Before installing or running: 1) Note the default data and output directories (/Users/zhouhao/... and ~/Desktop) and change them if you prefer to keep data elsewhere. 2) The SKILL.md shows environment variables (TOUFANG_*) but the registry listing does not declare them — the code will still read those env vars if you set them; decide which you want to use. 3) Install dependencies in a virtualenv (pip install -r requirements.txt) and inspect the three main scripts (main.py, clawhub_main.py, simple_run.py) if you want to confirm behavior. 4) Run on non-sensitive sample data first to confirm outputs and column name expectations (some cross-report formulas assume specific columns like 退货率 or 保量佣金). 5) If you need assurance about network/exfiltration risk: there are no network calls in the code, but if you modify the skill to add integrations, review those changes. Overall: functionally coherent and proportionate; proceed with normal caution for any tool that reads local files.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
