Agent skill
deepagent-memory-fold
DeepAgent-style memory folding for VCO sessions: compress long context into structured working/tool memory without using episodic-memory.
Install this agent skill to your Project
npx add-skill https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/main/bundled/skills/deepagent-memory-fold
SKILL.md
DeepAgent Memory Fold (VCO)
When to use
Use this skill when:
- The task is long-horizon and context is getting large
- You need to “take a breath” and restart reasoning from a compact state
- You see repeated retries / route instability / losing track of decisions
- You need to hand off to another agent or start a new session
Governance constraints (must follow)
- VCO memory governance disables
episodic-memory. - Use state_store (session) by default.
- Only write to Serena memory when the user explicitly approves a project decision.
Runtime (Upstream vendoring)
DeepAgent upstream is vendored (optional/advanced):
C:\Users\羽裳\.codex\_external\ruc-nlpir\DeepAgent\
Runtime config + preflight (no secrets stored/printed):
C:\Users\羽裳\.codex\skills\vibe\config\ruc-nlpir-runtime.jsonpwsh C:\Users\羽裳\.codex\skills\vibe\scripts\ruc-nlpir\preflight.ps1
Output contract (structured fold)
Produce a “folded memory” object with these sections:
- Working memory
- Current goal
- Current sub-goal
- Current blockers
- Next 3 actions
- Tool memory
- Tools/skills used
- What worked / what failed
- Availability notes (keys required, deps missing)
- Evidence memory
- Top 5 evidence anchors (file:line or URLs)
- Decision log
- Only decisions actually made (no speculation)
- Resume prompt
- A compact prompt that can be pasted into a new session
Where to store it
- Default: write to
outputs/runtime/memory-fold.json(or similar session output) - If user requests: also write a human-readable
memory-fold.md
Minimal template (copy/paste)
{
"working_memory": {
"goal": "",
"sub_goal": "",
"blockers": [],
"next_actions": []
},
"tool_memory": {
"used": [],
"worked": [],
"failed": [],
"availability": []
},
"evidence_memory": {
"anchors": []
},
"decision_log": [],
"resume_prompt": ""
}
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