Aloudata CAN SKILLS - forecast-simulation
v1.0.0基于已有数据进行趋势预测、目标缺口分析、What-if 模拟和耗尽/饱和预测。当用户希望了解指标的未来走势、评估目标是否可达、模拟假设场景的影响时，必须使用此 Skill。 触发场景包括但不限于：用户提到"预测""预估""月底能到多少""能不能完成目标""还差多少""如果XX会怎样""提升10%会怎样""库存还能...
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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 focus on forecasting and simulation and the SKILL.md contains forecasting methods, delegation to metric-query for data, and code for trend/target/what‑if calculations. There are no unrelated requirements (no cloud creds, no unrelated binaries).
Instruction Scope
Instructions stay within forecasting scope and explicitly require delegating data retrieval to metric-query rather than calling external APIs directly, which limits surface area. Note: the SKILL.md includes Python code (numpy) and expects the agent to execute those snippets — the skill does not declare that Python or numpy are available, so execution could fail or require environment support.
Install Mechanism
This is an instruction-only skill with no install spec and no downloads. No risky install mechanisms are present.
Credentials
The skill requests no environment variables, credentials, or config paths. It explicitly delegates API authentication and data access to metric-query, so it does not ask for elevated secrets itself.
Persistence & Privilege
always is false and the skill does not request permanent presence or modify other skills/configs. Autonomous invocation is allowed (platform default) but not combined with other privilege concerns.
Assessment
This skill appears internally consistent with its stated forecasting purpose. Before installing: 1) Confirm your agent environment can run the provided Python snippets (numpy is used) or that you have a standard-model execution path that supports them; otherwise the skill may fail. 2) Verify the metric-query skill you delegate to is trusted and has the appropriate authentication/authorization — this skill expects metric-query to handle all data access and credentials. 3) Understand that forecasts are simple mathematical extrapolations (linear, moving averages, weighted averages) and are not ML models — check that the assumptions/uncertainty notes are surfaced to end users. 4) If you want to limit autonomous use, consider restricting model-driven invocation in your agent policy; this skill does not request unusual privileges but autonomous invocation is platform-default.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.