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Derived generation helps when your source material is accurate but difficult to use in conversation. It compresses selected Raw files into a focused, first-person Markdown candidate.

How to generate

1

Select up to 20 Raw documents

Choose only the sources needed for the topic. Smaller, focused selections make review easier.
2

Choose a preset or custom instruction

Pick a server-owned preset, or describe the summary you need. For example, ask for a project context card or a recruiter-focused role summary.
3

Choose the exact model and target path

TLDT uses the model you select. The generated document receives a target path and keeps source provenance.
4

Review the Private candidate

Generation always creates a Private candidate. Save it through the normal document flow only after checking every claim.

What generation does not do

Generation does not publish, mark a document Public, invent missing experience, strengthen ownership or causality, silently change models, or silently truncate the selected sources. If the request is too large, TLDT returns a context-overflow error.

Review the result

Reject or edit any candidate that changes a date, metric, denominator, time range, actor, seniority, or outcome. Also check that it preserves negative context and does not turn a preference or plan into a fact.
Use generation for organization, not authorization. You remain the reviewer who decides whether a candidate becomes part of a public version.