Engram is a local or cloud-backed memory system for AI coding agents, provided as a single Go binary with SQLite full-text search and interfaces including a command line, HTTP API, MCP server, and terminal UI. It helps compatible coding agents retain project decisions, bugs, conventions, and other useful context across sessions. The catalogue add-ons configure and operate Engram’s memory workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Gentleman-Programming/engram --skill memory-protocolgit clone --depth 1 https://github.com/Gentleman-Programming/engramWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gentleman-programming/engram/memory-protocol)<a href="https://agentmods.dev/skills/gentleman-programming/engram/memory-protocol"><img src="https://agentmods.dev/badge/skills/gentleman-programming/engram/memory-protocol/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gentleman-programming/engram/memory-protocol"><img src="https://agentmods.dev/badge/skills/gentleman-programming/engram/memory-protocol.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.00356 |
| Opus 5.5 | $0.00012 | $0.00142 |
| Sonnet 5.5 | $0.00006 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
engram-memory-protocol scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
When to Use
The agent MUST follow this protocol without waiting for activation.
Use this skill when:
- Making architecture or implementation decisions
- Fixing bugs with non-obvious root causes
- Discovering patterns, gotchas, or user preferences
- Closing a session or after compaction
Save Rules
Call mem_save immediately after:
- decision
- bugfix
- pattern/discovery
- config/preference changes
Use structured content:
- What
- Why
- Where
- Learned
Use stable topic_key for evolving topics.
Search Rules
- On recall requests:
mem_contextfirst, thenmem_search. - Before similar work: run proactive
mem_search. - On first message: if user references the project, a feature, or a problem, call
mem_searchwith their keywords before responding.
Session Close Rules
Before saying done/listo:
- Call
mem_session_summary. - Include goal, discoveries, accomplished, next steps, relevant files.
After compaction:
- Save summary first.
- Recover context.
- Continue work.
Delivery Guarantee
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · +2 lines 3d4f5dcac5db
- 1mo ago Changed · +6 lines 79ecd2fc110e
- 1mo ago First seen · 58 lines · 30 tokens per session scan A b3fb9733f07a
engram-memory-protocol is a skill published in the GitHub repository Gentleman-Programming/engram (7,360 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 356 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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