Hire an AI dataset analysis and insight reviewer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A profile of the file with blanks, repeats, odd entries and the columns worth using
• An analysis that answers your question with the numbers and the limits
• A check of the method, the sums and any bias, with fixes to make
• A brief of the top three to five insights, ranked, each with a next action

How it does the job well

• Agree the question and the decision it supports before analysing.
• Check the data first: date range, grain, missing values, duplicates and definitions.
• Compare like with like: same period length, definitions and segments.
• Separate what the data shows from what it might mean, and give confidence levels.

Mistakes it avoids

• Reporting a change without checking whether tracking or definitions changed.
• Treating correlation as cause.
• Averages that hide important segments or outliers.

What a good result looks like

An example, not your task: You have an export or a spreadsheet and a question, and nobody has looked at the file yet.

• Dataset profile. What is in the file, with blanks, repeats, odd values and the columns worth using.
• Analysis. Answers your question with summary numbers, trends, group differences, outliers and the limits of the data.
• Analysis check. A review of the method and sums, the problems found, fixes to make and a trust rating.
• Insight brief. The top insights ranked, each with why it matters, likely cause, impact, next action and confidence.
• HAND-BACK SUMMARY. Each step's file, any step not run and why, and every MISSING line in one list.

How the work is checked

• Each step passed its own checks, or the run stopped at the step that failed and says why.
• The steps ran in order, and each one used the result of the one before.
• Nothing was invented to fill a gap. Every gap is a MISSING: line.
• Nothing was sent, published or paid for without a clear yes.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Profile the file. Finds the shape and the one-row-per-what of the table, sorts the columns by kind, counts blanks and repeats, and names the columns worth analyzing.
• Fix the data and set the question. Pause. You fix or drop the flagged columns and write the one question. The profile tells you where to look.
• Answer the question. Works out the summary numbers, trends, group differences and outliers, runs the tests that fit, and writes the findings with their limits.
• Check the analysis. Reviews the question, the population, the joins and the sums, recalculates a few key numbers by hand, and rates how far the result can be trusted.
• Write the insight brief. Turns each finding into what it means, why it happened and what to do, sizes the impact, and ranks by impact, confidence and ease of acting. Lower confidence where the check found doubt.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id turn-a-raw-dataset-into-a-checked-brief-of-top-insights only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/turn-a-raw-dataset-into-a-checked-brief-of-top-insights/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• A data file such as a CSV or spreadsheet
• The one question you want the data to answer
• Your goals and who will read the brief (optional)

Tools and access

• Claude with code running, or ChatGPT with data analysis: They can open your file and run the Python tests, so every number is computed, not guessed.

Functions and deliverables

• Dataset analysis and insight reviewer: Share a data file and one clear question. Get a data profile, checked analysis and a ranked brief with actions and limits.
  • A profile of the file with blanks, repeats, odd entries and the columns worth using
  • An analysis that answers your question with the numbers and the limits
  • A check of the method, the sums and any bias, with fixes to make
  • A brief of the top three to five insights, ranked, each with a next action
• Dataset profiler: Share a table or file. Get its shape, missing values, odd entries and which columns are worth analyzing.
  • Size and column type summary
  • Missing value and distinct counts
  • Duplicates and odd value list
  • Columns worth analysing
  Source: Anthropic.
• Data analyst: Give it a dataset and a question. Get evidence-based answers with trends, tests and correlations.
  • A one or two sentence answer, and how sure it is
  • A table of key numbers, such as averages, trends and correlations
  • Test results with p-values and the size of the effect
  • Ranked findings, each with its caveat
  • Outliers and data problems, and what to do next
  Source: Burhan Sebin.
• Analysis checker: Share a report, query, or chart for checks of methods, calculations, conclusions, and needed fixes.
  • A review of method and assumptions
  • Results of the pre-delivery checklist
  • Any pitfalls found
  • A confidence rating and fixes
  Source: Anthropic.
• Insight brief writer: Share your findings and goals. Get the top insights ranked by impact and confidence, each with an action.
  • Top insights ranked by impact and confidence
  • A so what, why and now what for each
  • Size estimates for business impact
  • Notes on conflicting findings
  • A short brief
  Source: Nimrod Fisher.
• Metric definition writer: Share a metric, calculation and business use. Get a YAML definition, validation results and questions for the data owner.
  • A filled metric, dimension or entity YAML
  • A validation report
  • dbt-ready field names
  • Notes on edge cases
  Source: Nimrod Fisher.

Tasks you can use it for

• You have an export or a spreadsheet and a question, and nobody has looked at the file yet.
• You are about to share an analysis and want it checked first.
• You have a pile of findings and need to say which ones to act on.

Limits to check before starting

• Your file has only a few dozen rows: read it by eye or sort it in your spreadsheet instead.
• You need one number, such as a total or an average: use a single spreadsheet formula or a calculator.
• You only want an existing analysis reviewed: use the Analysis checker on its own.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the handoff pack. It holds HANDOFF.md and the 4 skill files in the order they run: Dataset profiler, Data analyst, Analysis checker and Insight brief writer.
• Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
• Attach your data file. Step 1 reports on it and stops.
• Pause. Fix or drop the columns the profile flagged, then write your one question in plain words.
• Tell it who will read the brief. The last step ranks insights for that reader.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/turn-a-raw-dataset-into-a-checked-brief-of-top-insights for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.