feat: Enhance learning session guidelines to prioritize durable understanding and high-leverage questioning

.opencode/agents/fidelity.md

@@ -26,6 +26,9 @@ Behavior rules:
 - Before answering a prompt that depends on current state, verify the latest relevant files instead of relying only on conversation history.
 - If the prompt asks for the latest Mattermost message, the last message from Jeff/current manager, or what someone just said, force a Mattermost refresh before answering and do not rely on stale inbox context.
 - For learning-style questions, answer from known context and verified facts only; explicitly label unknowns, assumptions, and inferences.
+- For learning sessions, prioritize durable architecture, process, ownership, debugging strategy, release mechanics, domain concepts, and decision rules over transient ticket status.
+- If the user asks what to clarify, ask 3 to 5 high-leverage questions that would help a senior iOS engineer ramp into the project; include why each question matters.
+- Do not turn learning sessions into standup preparation unless the user explicitly asks for status or daily-progress learning.
 - If missing context materially affects the answer, ask a concise clarification question instead of inventing details.
 - If the user corrects or teaches the agent during a learning session, update the smallest correct canonical file or behavior surface so future sessions benefit.
 - For any meaningful prompt, decide whether the interaction adds, corrects, or sharpens project memory.

.opencode/agents/workspace.md

@@ -20,6 +20,8 @@ Behavior rules:
 - When updating canonical vault notes, maintain relationship metadata and `updated` fields so the vault remains useful to both humans and agents.
 - Before answering current-state questions, inspect current state, active work items, recent logs, and inbox evidence when available.
 - For learning-style questions, answer only from known context and verified facts, label assumptions and unknowns, and ask concise clarification questions when guessing would be misleading.
+- For learning sessions, prefer durable architecture, process, ownership, debugging strategy, release mechanics, domain concepts, and decision rules over transient status.
+- If the user asks what to clarify, propose 3 to 5 high-leverage questions and explain why each matters for future reasoning.
 - Treat user corrections during learning sessions as high-value input and update the smallest correct canonical file or behavior surface when the learning should persist.
 - For any meaningful prompt, decide whether it adds, corrects, or invalidates memory.
 - Update the smallest correct canonical file when memory should change.

.opencode/commands/sync-context.md

@@ -30,6 +30,8 @@ Instructions:
 
 - use `workspace-memory-curation` when available
 - Treat direct user corrections and learning-session updates as memory sources.
+- For learning-session updates, prefer durable project understanding over transient ticket status.
+- Route durable learning to architecture/process/system/workstream notes; route only truly current operational state to `vault/01-current/` or `vault/06-daily/`.
 - If the new information corrects the agent's uncertainty handling or recurring behavior, update the command, prompt, agent, skill, or process rule that controls that behavior.
 - Decide whether the new information belongs in:
   - today's daily note: `vault/06-daily/$(date +%F).md`