architecture-guardrail…
Architecture guardrails for Engram across local store, cloud sync, dashboard, and plugins. Trigger: Any change that affects…
ALWAYS ACTIVE — Selective persistent memory: preserve verified, durable knowledge worth reconstructing, with safe topic updates and host-owned lifecycle.
Claude Code
$ npx -y skills add Gentleman-Programming/engram --skill memory --agent claude-code
Codex
$ npx skills add Gentleman-Programming/engram --skill memory -a codex -y
Cursor
$ npx skills add Gentleman-Programming/engram --skill memory -a cursor -y
Gemini CLI
$ npx skills add Gentleman-Programming/engram --skill memory -a gemini-cli -y
GitHub Copilot
$ npx skills add Gentleman-Programming/engram --skill memory -a github-copilot -y
OpenCode
$ npx skills add Gentleman-Programming/engram --skill memory -a opencode -y
Windsurf
$ npx skills add Gentleman-Programming/engram --skill memory -a windsurf -y
name: engram-memory description: "ALWAYS ACTIVE — Selective persistent memory: preserve verified, durable knowledge worth reconstructing, with safe topic updates and host-owned lifecycle."
You have access to Engram, a persistent memory system that survives across sessions and compactions. The agent MUST follow this protocol without waiting for activation.
Use the Engram tools actually exposed by Claude Code, with their registered MCP names. The names below are logical names; availability and discovery follow Claude's host interface, not a universal bootstrap or deferred-tool split.
Persist verified knowledge that is durable and costly to reconstruct: decisions with rationale, non-obvious root causes, real constraints, and resumption-relevant pending work. Group related conclusions deliberately, not every task, response, or event. Exclude secrets, private data, speculation, raw dumps, and routine progress.
Honestly report unavailable memory evidence; never claim unconfirmed persistence. Do not blindly repeat writes. Complete unrelated work even if bookkeeping fails. Do not add per-event learning sections or ceremonial delivery blocks.
Format for `mem_save`:
**What**: One sentence — what was done **Why**: What motivated it (user request, bug, performance, etc.) **Where**: Files or paths affected **Learned**: Gotchas, edge cases, things that surprised you (omit if none)
When the user asks to recall something — any variation of "remember", "recall", "what did we do", "how did we solve", or the equivalent in the user's language, or references to past work: 1. First call `mem_context` — checks recent session history (fast, cheap) 2. If not found, call `mem_search` with relevant keywords (FTS5 full-text search) 3. If you find a match, use `mem_get_observation` for full untruncated content
Search when materially useful for recall or related work; mere project mentions do not require a search. Narrow by project/type after broad recall as needed.
Memory operations are internal bookkeeping, never the user-facing answer. Complete required memory work before composing the completed-task reply; send the complete answer as the final message of the turn with no later tool calls. If memory work fails or needs follow-up, still send the answer.
At significant explicit closure or handoff, call mem_session_summary with Goal, Instructions, Discoveries, Accomplished, Next Steps, Relevant Files. Ordinary task completion does not require a summary. Summary persistence does not end the session. Claude's SessionEnd hook owns lifecycle closure independently of the agent's summary.
Automatic capture is adapter-specific: Claude's SubagentStop hook forwards eligible delegated/subagent output for server-side extraction. Ordinary responses from the main agent are not automatically captured by this hook; the section alone does not guarantee storage. Use `mem_save` as the primary path for significant, verified knowledge.
You can also call `mem_capture_passive(content)` directly with any text that contains a learning section. This explicit extraction path is a safety net, not a replacement for `mem_save`.
If you see a message about compaction or context reset, or if you see "FIRST ACTION REQUIRED" in your context: 1. IMMEDIATELY call `mem_session_summary` with the compacted summary content — this persists what was done before compaction 2. Then call `mem_context` to recover any additional context from previous sessions 3. Only THEN continue working
Do not skip step 1. Without it, everything done before compaction is lost from memory.
For Engram write and session MCP tools, the Claude plugin binds `session_id` to Claude Code's authoritative session identity before the tool runs. Do not invent, reuse, or try to override this value. Read-only tools are unchanged. Generic or direct MCP clients still require their existing explicit-session contract.
**Fallback**: If tools are unexpectedly unavailable, run `engram setup claude-code` again and restart Claude Code. Setup repairs a regular durable MCP config and the permissions allowlist for both current (`mcp__engram__...`) and older plugin-scoped (`mcp__plugin_engram_engram__...`) server ids. If the MCP config is a symlink or another non-regular path, replace it manually before rerunning setup.
Persistent memory system for AI coding agents. Agent-agnostic Go binary with SQLite + FTS5, MCP server, HTTP API, CLI, and TUI.
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