We plan to investigate how Claude might assist authors with manuscript preparation, metadata, and launch planning. The interactive sample below is entirely local. We have not enabled a Claude API connection.
An author would choose a task and explicitly select the context needed, such as publishing format, manuscript preferences, or task instructions.
2. Claude processing (planned)
A future server-side integration would interpret the request and create bounded, structured recommendations.
3. Reviewable output
Suggested checklists, book descriptions, preparation steps, or alternatives would be presented for editing before use.
4. Author decision
The author would approve or revise any suggestions. No autonomous posting to Amazon KDP or other publishing services is promised.
Privacy considerations
A production version would require consent, data minimization, server-only credentials, retention rules, abuse protection, and budget limits.
Why API credits matter
Credits could support prompt evaluations, structured-output reliability, multilingual tests, latency and cost measurement, and an early pilot.
Planned Claude use cases
These are proposed workflows, not features currently connected to the website.
Publishing brief into a project checklist
An author could describe a manuscript and desired formats. Claude would suggest an editable preparation checklist and clarify what information is still missing.
Metadata drafts and alternatives
With author-selected book details, Claude could draft candidate descriptions and keyword ideas for the author to correct, verify, and adapt before entering them in KDP.
Formatting and launch guidance
Based on author-selected format settings, Claude could explain trade-offs, flag questions to investigate, and propose a release checklist without promising retailer approval.
Try the interaction concept
This browser-only preview demonstrates the proposed review step using predefined examples. It never sends information to Claude, a server, or a database.
INTERACTIVE CONCEPT · NOT AN AI SERVICE
Preview the planned author assistant
Try a predefined example of the proposed Claude experience. Responses are local sample text, not generated by Claude. Nothing is uploaded, stored, or sent to an API.
Demo only
Select a task and choose “Show sample recommendations” to see the concept.
Data boundaries and author control
What a future Claude request would need
Author-selected goals, target book format, approved excerpt or summary, relevant settings, and a specific request. No unrestricted access to the author's account.
What the author would receive
Structured suggestions displayed as editable text, checklists, or alternatives. Acceptance would be deliberate: no automated book upload or publication.
Safeguards planned before launch
• Only selected, task-relevant author content would be transmitted with explicit consent.• The planned API key would remain server-side; no browser key or direct client-to-Claude request.• Validate request size, output schema, access controls, and cost ceilings before production.• Never send passwords, payment credentials, or unrelated customer files to a model.• The author reviews and edits suggestions; nothing is automatically posted to KDP.
Development workflow and API plan
We plan to evaluate Claude Code for implementation, refactoring, debugging, test design, and code review. This describes a future engineering workflow, not verified past usage.
Proposed request lifecycle
Author-selected task → consent and validation → protected server endpoint → Claude API suggestions → output checks → editable preview → author approvalNo endpoint, API key, Claude SDK, or model calls are implemented in this PR. A separate backend implementation would need approval and security testing.
Evaluation before production
Structured output
Verify that responses match explicit schemas and that unexpected data cannot silently change the interface.
Publishing accuracy
Check guidance against current KDP requirements; label uncertain information and keep a human verification step.
Language and accessibility
Evaluate author briefs in English and additional languages as needed, with readable output and keyboard-accessible review.
Cost, latency, and reliability
Measure API spend, response times, error handling, timeouts, and per-user request limits with synthetic cases.
These are planned evaluation gates. They have not been completed, and API credits would help fund implementation and testing rather than certify product readiness.