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Load when the user wants analysis on a dataset — trends, distributions, summary statistics, or insights from a CSV/JSON/Excel file.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
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.
