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 agentmods add skills/gentleman-programming/engram/pr-review-deepnpx skills add Gentleman-Programming/engram --skill pr-review-deepgit 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/pr-review-deep)<a href="https://agentmods.dev/skills/gentleman-programming/engram/pr-review-deep"><img src="https://agentmods.dev/badge/skills/gentleman-programming/engram/pr-review-deep.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00028 | $0.00176 |
| Opus 5 | $0.00014 | $0.00088 |
| Sonnet 5 | $0.00006 | $0.00035 |
| Haiku 4.5 | $0.00003 | $0.00018 |
Grade A, and why
engram-pr-review-deep 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 5d 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
Use this skill when:
- Evaluating PRs from contributors
- Reviewing risky refactors
- Deciding merge vs request-changes
Review Protocol
- Read full diff, not only summary.
- Run relevant tests locally.
- Validate API/contracts and migration safety.
- Check docs against implementation.
- Flag commit hygiene violations.
Merge Gate
Merge only when:
- checks are green
- risk is understood
- blockers are resolved
- scope is coherent
Otherwise request changes with actionable items.
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.
- 5d ago First seen · 40 lines · 28 tokens per session scan A 36159082c59f
engram-pr-review-deep is a skill published in the GitHub repository Gentleman-Programming/engram (6,326 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 176 once invoked, about $0.0001 per session on Opus 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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