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 issue-creationgit 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/issue-creation)<a href="https://agentmods.dev/skills/gentleman-programming/engram/issue-creation"><img src="https://agentmods.dev/badge/skills/gentleman-programming/engram/issue-creation/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/issue-creation"><img src="https://agentmods.dev/badge/skills/gentleman-programming/engram/issue-creation.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 | $0.00038 | $0.02122 |
| Opus 5.5 | $0.00015 | $0.00849 |
| Sonnet 5.5 | $0.00008 | $0.00424 |
| Haiku 4.5 | $0.00004 | $0.00212 |
Grade A, and why
engram-issue-creation 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
Use this skill when:
- Creating a GitHub issue (bug report, feature request, docs improvement, or tracked question)
- Helping a contributor file an issue
- Triaging or approving issues as a maintainer
Critical Rules
- Blank issues are disabled — MUST use the matching bug, feature, docs, or tracked-question template
- Every issue gets
status:needs-reviewautomatically on creation status:approvedmeans maintainer-accepted proportional evidence as defined in CONTRIBUTING.md; bugs include current-main reproduction and root cause- General questions go to Discussions; questions requiring tracked work use
type:question
Workflow
1. Search for a canonical root-cause tracker; add a new occurrence there when applicable
2. Choose the correct template and report consequence plus release context, not root cause or implementation
3. Submit → issue gets status:needs-review automatically
4. A maintainer triages and assigns an investigator, who records each same-root occurrence on the canonical tracker before duplicate closure
5. Use proportional evidence: scope/checks for trivial changes; current-remote-main SHA, reproduction, violated invariant/root cause, and regression test plan for bugs; approved design/non-goals and independent review plan for high-risk changes
6. A maintainer replaces the current status with status:approved after accepting that evidence; any real assignee satisfies ownership, not necessarily the PR author
Issue Templates
Bug Report
Template: .github/ISSUE_TEMPLATE/bug_report.yml
Auto-labels: type:bug, status:needs-review
Required Fields
| Field | Description |
|---|---|
| Existing Issue Search | Required acknowledgement; add evidence to a canonical tracker when applicable |
| Observed Consequence | Clear user-visible consequence, without root-cause diagnosis |
| Steps to Reproduce | Numbered steps to reproduce |
| Expected Behavior | What should have happened |
| Actual Behavior | What happened instead (include errors/logs) |
| Operating System | Dropdown: macOS, Linux variants, Windows, WSL |
| Release Version | Report context from engram version; an investigator verifies current remote main |
| Agent / Client | Dropdown: Claude Code, OpenCode, Gemini CLI, Cursor, Windsurf, Other |
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.
- 2d ago Changed · -3 lines 19a9e8b221af
- 1mo ago Changed · +45 lines 26e8e1b4e72c
- 1mo ago Changed · -11 lines caa3ae7602d6
- 1mo ago First seen · 231 lines · 38 tokens per session scan A 7b12aabbf55f
engram-issue-creation is a skill published in the GitHub repository Gentleman-Programming/engram (7,360 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 2,122 once invoked, about $0.0002 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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