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 Patdolitse/piia-engram --skill engramgit clone --depth 1 https://github.com/Patdolitse/piia-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/patdolitse/piia-engram/engram)<a href="https://agentmods.dev/skills/patdolitse/piia-engram/engram"><img src="https://agentmods.dev/badge/skills/patdolitse/piia-engram/engram/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/patdolitse/piia-engram/engram"><img src="https://agentmods.dev/badge/skills/patdolitse/piia-engram/engram.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00175 | $0.01189 |
| Opus 5 | $0.00088 | $0.00594 |
| Sonnet 5 | $0.00035 | $0.00238 |
| Haiku 4.5 | $0.00017 | $0.00119 |
Grade A, and why
engram 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 10d 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 82 lines · 175 tokens per session scan A 6fa79204d1e5
engram is a skill published in the GitHub repository Patdolitse/piia-engram (160 stars, last pushed 8d ago), licensed AGPL-3.0. It adds 175 tokens to every session and 1,189 once invoked, about $0.0009 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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L0/L1/L2 three-layer context loading protocol — reduces token consumption during /resume boot.
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lians
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lians-integrate
Wire Lians memory into an existing agent codebase, test-first and minimal-diff. Use when the user asks to add persistent/compliance memory to their agent, integrate Lians, or replace a vector store with bitemporal memory.
strategic-compact
Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction. Supports focus-aware compaction for targeted context preservation.