Claude Code drafts client reports from live data
Aspinall reports reusable Claude Code skills that pull tracking data into weekly client-report drafts, with human editing and a documented failure when incomplete data reached a client.
Suggested prompt
Suggested prompt written by Agents In Use, not the source author. Replace bracketed inputs and review tool permissions first.
Draft [client weekly report] from [tracking data] using [analysis framework] and [template]. Identify missing or inconsistent inputs, retain evidence for claims, and prepare the narrative for my review rather than sending it.
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Sourced account- Source author
- John Aspinall
- Original account
- Read the source ↗
- Published
- Source link checked
- Reported result
- Aspinall reports reusable Claude Code skills that pull tracking data into weekly client-report drafts, with human editing and a documented failure when incomplete data reached a client.
- Human involvement
- Aspinall reviews and edits reports. An incomplete-data failure reached a client, demonstrating that the workflow’s review and validation were not initially sufficient.
A linked account supports attribution. It does not mean we independently reproduced its result.
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How the agent did it
- Define client context, analysis rules and report formatting conventions.
- Connect the tracking data and link an actual output template.
- Run the report skill and prepare a client-specific narrative draft.
John Aspinall runs weekly client-performance reporting through Claude Code skills linked to business context, formatting conventions and connected tracking data. A report skill applies his analysis framework and prepares a narrative in the style each client expects. He reviews and edits the draft before relying on it.
The implementation grows through iterations rather than one long instruction file. Aspinall says his first oversized skill broke repeatedly and that a simpler version remained usable. He also identifies a concrete failure: a report skill produced good output for top accounts but nonsense for accounts with incomplete data, which he discovered only after a client saw it.
That failure explains why his later process tests messy inputs and revisits scheduled outputs instead of assuming that a successful clean example proves the workflow. Report timings and weekly savings are his own estimates, not independently measured results. The useful copyable pieces are a linked output template, an explicit analysis framework and a missing-data policy checked against weak source data. The source does not name a client, expose the tracking system or establish an audited accuracy rate; the entry therefore keeps the outcome at recurring report drafting with documented limitations.
Prompt
Suggested prompt (written by Agents In Use, not the author's)
Source: Blog · John Aspinall
Frequently asked questions
What guides the report format?
The skill references business context, formatting conventions and a report template rather than relying on a fresh generic prompt.
What concrete failure occurred?
A report skill produced nonsense from incomplete account data, and the author discovered it after a client saw the result.
Are the claimed time savings independently verified?
No. The source provides the author’s estimates, not a controlled report-production benchmark.
More details
Remaining steps
- Test incomplete inputs and inspect the resulting missing-data behaviour.
- Have Aspinall review and edit reports and revisit scheduled output quality.
About this account
Claude Code retrieves connected tracking data, applies reusable report rules and drafts a structured client narrative; humans edit and maintain the workflow.
Firsthand account by John Aspinall; original publication date verified against Primary blog September 20, 2026. Outcomes are the author’s reports, not independently reproduced. Suggested prompt written by Agents In Use; not the author’s original prompt.
Credit: John Aspinall
Source published
Added to Agents In Use
Source checked
Tools and topics
Claude Code · Report skills · MCP data connection · CLAUDE.md · Output templates
Weekly client reports · Incomplete-data checks · Human editing
Editorial completeness: 100/100. Measures documented fields, not agent performance or verified outcomes.