القائمة
Load when the user wants analysis on a dataset — trends, distributions, summary statistics, or insights from a CSV/JSON/Excel file.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Load when the user asks to queue, enqueue, or add a coding task to the fleet, dispatch a job to a repo, or ask the fleet worker to fix something. Trigger phrases: "add to fleet", "queue a job for", "send to fleet", "dispatch to".
Load when the user provides stock trading recommendations and wants positions sized and bracket orders placed on the Alpaca paper-trading account.
Load when the user wants to navigate a website, click through a flow, fill a form, extract data from a page, or record an interaction as a reusable playbook.
Load when the user asks to review code, audit a PR, find bugs in code they paste, or assess code quality. Trigger phrases: "review this", "look at my code", "is this right", "what's wrong with X".
Load when the user is responding to a customer inquiry, complaint, or support ticket and needs help drafting a reply with the right tone.
Load when the user asks to draft, compose, or send an email — or to write a Telegram message that is substantively a message draft (not a quick reply).
| name | Data Analysis |
| slug | data-analysis |
| description | Load when the user wants analysis on a dataset — trends, distributions, summary statistics, or insights from a CSV/JSON/Excel file. |
| icon | BarChart3 |
| color | #10b981 |
| version | 1.1.0 |
| category | data |
| tools | ["analyze_data","read_file"] |
| config_schema | {"type":"object","properties":{"preferred_format":{"type":"string","enum":["table","narrative","bullets"],"default":"narrative"}}} |
Output format: {preferred_format}.
Before drawing conclusions: shape, dtypes, missing values, basic stats, and a look at distributions/outliers. State your assumptions explicitly.
Don't confuse correlation with causation — say "associated with" unless there's an experimental setup that earns the word "caused".
Numbers, not adjectives: "revenue rose 23% QoQ" beats "revenue rose significantly".
End with concrete recommendations the reader can act on, and a "Data quality notes" section if anything could invalidate the conclusions.
