Df Merger
v2.1.0Merge pandas DataFrames from multiple construction sources. Handle different schemas, keys, and data quality issues.
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
The name/description and the provided Python implementation align: the skill is focused on merging DataFrames and schema reconciliation for construction data. However, the SKILL.md code uses pandas and numpy but the skill's requirements only list python3 (no declared Python package dependencies or install steps), which is a functional/coherence gap.
Instruction Scope
Instructions and code are limited to reading and merging user-provided data (CSV/Excel/JSON/DFs) and presenting results; they do not reference external network endpoints, environment secrets, or other system-wide config. That scope is appropriate, but because this is an instruction-only skill containing runnable Python code, confirm how and where the code will be executed and that the agent will only process files you explicitly provide.
Install Mechanism
There is no install spec (instruction-only), which lowers supply-chain risk. However, the missing declaration of required Python packages (pandas, numpy) means the agent or a user might attempt to install packages at runtime (e.g., pip), which is an operational concern to clarify before execution.
Credentials
The skill does not request environment variables, credentials, or external API tokens. This is proportionate to the stated purpose (local data merging).
Persistence & Privilege
always:false and model invocation is allowed (platform default). The claw.json lists a general 'filesystem' permission which is consistent with reading user-supplied files, but you should confirm the exact filesystem access scope and that it won't be used to read system files you didn't intend to share.
What to consider before installing
What to check before installing or running this skill:
- Confirm your runtime has the required Python packages (pandas, numpy, possibly others). Ask the author for an explicit dependency list or a requirements.txt/install instructions; do not let the agent auto-install packages without oversight.
- Review the full SKILL.md (and any truncated parts) to ensure there are no hidden network calls, telemetry, or unexpected file-system operations.
- Only provide the files/data you want merged; avoid giving access to system directories or secrets. The skill declares filesystem permission — verify whether execution will be sandboxed or limited to user-supplied paths.
- If you need to be cautious, run the provided Python code locally in an isolated environment (venv/container) with the datasets you control before enabling autonomous invocation.
- If anything is unclear, request the vendor/owner for a clearer install manifest and a list of runtime dependencies and file-access behavior.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.
Runtime requirements
🐼 Clawdis
OSmacOS · Linux · Windows
Binspython3