Run data cleaning to executive summary with agent pipeline
Five specialized agents. Task: The author used an AI planning agent to generate a 713-line specification for a data analysis pipeline, then instructed Claude Code to build it. The resulting suite includes five specialized agents (cleaner, analyzer, visualizer, report writer, exec summarizer) and an orchestrator. The human role was limited to defining requirements, approving permissions (~20 times), and reviewing outputs, with zero manual coding.; tools: Claude Code. Human role: The original post does not say how a person stayed involved.; limitations: Prerequisites include a Claude Pro or Max subscription and a detailed specification document. The author notes that while the build cost ~$35 in API calls, the Max plan was used for convenience, not necessity. Critical constraint: outputs require human verification for data integrity and narrative accuracy; the agents replace grunt work, not judgment..
Tools
Published on Agent Work Atlas:
Overview
Five specialized agents.
Workflow
The author used an AI planning agent to generate a 713-line specification for a data analysis pipeline, then instructed Claude Code to build it. The resulting suite includes five specialized agents (cleaner, analyzer, visualizer, report writer, exec summarizer) and an orchestrator. The human role was limited to defining requirements, approving permissions (~20 times), and reviewing outputs, with zero manual coding.
Reported result
The build completed in approximately five hours, generating 627 passing tests and a functional agent suite. The author estimates saving 7-9 hours per analysis cycle after one hour of human review. However, the author explicitly states they have not yet used this system on production work data, so real-world business impact remains unverified.
Human role
The original post does not say how a person stayed involved.
Limitations
Prerequisites include a Claude Pro or Max subscription and a detailed specification document. The author notes that while the build cost ~$35 in API calls, the Max plan was used for convenience, not necessity. Critical constraint: outputs require human verification for data integrity and narrative accuracy; the agents replace grunt work, not judgment.
Try it
Act as a technical lead. I want to build a data analysis agent suite using Claude Code. First, help me draft a detailed specification document defining five agents: @data-cleaner, @data-analyzer, @data-visualizer, @report-writer, and @exec-summarizer, plus an orchestrator. Specify input/output contracts and test requirements for each. Once I approve the spec, use Claude Code to implement the agents and write unit tests. Run a dry run on [replaceable sample CSV file] and show me the cleaned data, analysis JSON, and executive summary before finalizing. Do not deploy to production without my explicit confirmation of the test results.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.