One investigation tick: TcsfKernel as the research runtime

Scanners dump tool output. Nexus runs reasoning. TCSF wraps both in a single investigation tick — code in tcsf/kernel/research_loop.py, not a slide deck.

The tick

pipeline → findings_batch → EvidenceStore
       → reflect → experiment → learn → evaluate
       → graph projection

TcsfKernel.run_investigation loads a mode profile (nexus_url / nexus_network), runs the Nexus pipeline, normalises findings into evidence, then executes optional post_run capabilities: cap.cognitive.reflection and cap.cognitive.experiment.

What reflection actually does

• Heuristics always run — empty findings → should_replan; active hypotheses with zero confirmed evidence → experiments recommended
• LLM via MAL when available — critique is typed, not free-form chat
• Confirmed / refuted experiments mutate hypothesis status and re-enter the evidence plane

Invariant

Nexus remains the reasoning kernel. TCSF owns the loop, the event bus (tcsf/events/), evaluation, and learning signals. Engines never import provider SDKs — they request completions through MAL by task_type.