Require memory retrieval after compaction signals

.agents/skills/memory-manager/SKILL.md

@@ -50,10 +50,14 @@ Todo granularity should be task-level (small stages/subtasks), not command-level
 Retrieve early when useful, but do not block execution:
 
 1. Query by `project`, `task_type`, `error_signature` first.
-2. Add tags and FTS when exact filters miss.
-3. Prefer `active` procedures/insights when confidence is similar.
-4. Flag stale entries with low confidence.
-5. If retrieval is low-yield and task is time-sensitive, continue with search/deep research directly.
+2. Upgrade retrieval from optional to mandatory before continuing when either of these triggers is present:
+   - you are modifying `memory-manager` or another Memory-related skill/instruction
+   - a status, state, or context file contains compaction markers such as `Compact`, `压缩`, `Summary`, or similar summary/compression techniques
+3. In mandatory-retrieval cases, read prior Memory first and treat the result as required context recovery rather than a best-effort lookup.
+4. Add tags and FTS when exact filters miss.
+5. Prefer `active` procedures/insights when confidence is similar.
+6. Flag stale entries with low confidence.
+7. If retrieval is low-yield and task is time-sensitive, continue with search/deep research directly only when the mandatory-retrieval triggers are absent.
 
 ## Writeback Policy
 
@@ -91,7 +95,17 @@ If execution becomes repetitive or confused:
 
 1. Rebuild working state from action and observation logs.
 2. Run targeted retrieval by project/task/error signature.
-3. Publish compact state summary before continuing.
+3. If drift followed a compaction step or summary-style recovery, read prior Memory before publishing or trusting a compact state summary.
+4. Publish compact state summary before continuing.
+
+## Compaction Recovery Policy
+
+When context may have been compressed:
+
+1. Inspect available status/state/context files for markers such as `Compact`, `压缩`, `Summary`, or equivalent summary/compression techniques.
+2. If any marker is present, call `memory-manager` to read prior Memory before editing instructions, planning next actions, or resuming execution.
+3. If prior Memory cannot be read, treat that as an active blocker because key context may be missing.
+4. Record the compaction trigger and retrieval result in working state or the next stage report.
 
 ## Promotion Policy
 

.agents/skills/research-workflow/SKILL.md

@@ -68,15 +68,20 @@ Repeat this loop until completion:
 Use these in combination:
 
 1. Treat memory as an optional accelerator, not a hard prerequisite.
-2. Use search/deep research directly when topic is time-sensitive, new, or currently blocked.
-3. For open-ended research/scoping requests, run deep research before giving decomposition or roadmap recommendations.
-4. For unknown errors, use this branch:
+2. Override that default and retrieve memory first when either of these is true:
+   - the current task modifies `memory-manager` or another Memory-related skill/policy
+   - state/context files show compaction markers such as `Compact`, `压缩`, `Summary`, or equivalent summary/compression techniques
+3. In those override cases, call `memory-manager` to read prior Memory before planning, editing, or resuming execution.
+4. Use search/deep research directly when topic is time-sensitive, new, or currently blocked.
+5. For open-ended research/scoping requests, run deep research before giving decomposition or roadmap recommendations.
+6. For unknown errors, use this branch:
    - local evidence triage (logs, stack trace, recent changes)
    - targeted search
    - deep research (debug-investigation) if still unresolved
    - minimal fix validation
-5. If skipping memory before search, record reason in the stage report.
-6. If intake information is missing, trigger `human-checkpoint` before deep research or planning.
+7. If compaction is detected, treat missing memory retrieval as a workflow violation and recover by reading prior Memory before continuing.
+8. If skipping memory before search outside the override cases, record reason in the stage report.
+9. If intake information is missing, trigger `human-checkpoint` before deep research or planning.
 
 ## Replanning Policy
 

AGENTS.md

@@ -6,13 +6,14 @@ This workspace is for AI research and development tasks (reproduction, debugging
 1. Start each non-trivial research task with `run-governor` to select mode and initialize `run_id` paths.
 2. Use `research-workflow` as the default orchestration loop.
 3. Use `memory-manager` to maintain working todo state and long-term memory.
-4. Trigger `human-checkpoint` using mode-aware policy, always for major safety risks and shared-memory publication.
-5. Use `experiment-execution` only for actual run execution.
-6. Use `project-context` to collect and persist per-project private runtime context before experiments or report/eval execution.
-7. Use `deep-research` for deep external investigation and evidence synthesis, including early-stage project scoping when a user wants to write a research study or paper on a topic.
-8. Base conclusions on evidence only (command outputs, metrics, logs, and file diffs).
-9. Prefer small, reversible, verifiable steps over broad speculative changes.
-10. Follow `REPO_CONVENTIONS.md` for artifact placement and commit hygiene.
+4. If you modify `memory-manager` or any Memory-related skill, or detect compaction markers in state/context files such as `Compact`, `压缩`, `Summary`, or similar summary/compression techniques, invoke `memory-manager` to read prior Memory before continuing so key context is not dropped.
+5. Trigger `human-checkpoint` using mode-aware policy, always for major safety risks and shared-memory publication.
+6. Use `experiment-execution` only for actual run execution.
+7. Use `project-context` to collect and persist per-project private runtime context before experiments or report/eval execution.
+8. Use `deep-research` for deep external investigation and evidence synthesis, including early-stage project scoping when a user wants to write a research study or paper on a topic.
+9. Base conclusions on evidence only (command outputs, metrics, logs, and file diffs).
+10. Prefer small, reversible, verifiable steps over broad speculative changes.
+11. Follow `REPO_CONVENTIONS.md` for artifact placement and commit hygiene.
 
 ## Skill Paths
 - `.agents/skills/run-governor`