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 madezmedia/acmi --skill docsgit clone --depth 1 https://github.com/madezmedia/acmiWrote 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/madezmedia/acmi/docs)<a href="https://agentmods.dev/skills/madezmedia/acmi/docs"><img src="https://agentmods.dev/badge/skills/madezmedia/acmi/docs/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/madezmedia/acmi/docs"><img src="https://agentmods.dev/badge/skills/madezmedia/acmi/docs.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 | $0.00000 | $0.03436 |
| Opus 5.5 | $0.00000 | $0.01374 |
| Sonnet 5.5 | $0.00000 | $0.00687 |
| Haiku 4.5 | $0.00000 | $0.00344 |
Grade A, and why
docs 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 1mo 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 — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Context Memory Interface (ACMI)
ACMI is a universal architectural framework for giving AI agents persistent, real-time context. It replaces fragmented, multi-table database joins with a single, lightning-fast Key-Value engine (Upstash Redis) optimized specifically for LLM context windows.
The Core Concept
Agents don't need highly normalized relational databases. They need state snapshots and chronological timelines.
ACMI decouples the application layer from the agent layer by standardizing how context is stored, regardless of the use case. It organizes data by namespace (the domain) and id (the entity).
The Three Pillars of ACMI
- Profile (State):
acmi:{namespace}:{id}:profile-> A JSON snapshot of the entity's current hard data (Name, Stage, Budget, Specs). - Signals (AI State):
acmi:{namespace}:{id}:signals-> A JSON snapshot of AI-synthesized soft data (Churn Risk, Sentiment, Next Best Action). - Timeline (Event Stream):
acmi:{namespace}:{id}:timeline-> A Redis Sorted Set (ZSET) that chronologically merges events from every platform (Gmail, Slack, Vapi, Calendar, System Webhooks).
Agent extensions (long-context + identity)
For long-lived agents that span many sessions, ACMI adds four optional keys on top of the three pillars:
- Spawn log:
acmi:agent:{id}:spawns(ZSET) — every session start, scored by ts, with{session_id, model_id, host}. Lets you query "who was this agent on date X" (imp-7 reincarnation). - Active context:
acmi:agent:{id}:active_context(HASH) — which threads the agent is currently engaged in, with role + since_ts. - Rollup:
acmi:agent:{id}:rollup:latest(STRING JSON) — periodically synthesized summary of recent timeline; cheap to read on spawn instead of replaying raw events (imp-2 archival foundation). - Work items:
acmi:work:{id}:{profile|signals|timeline|sessions}— long-running ideas / projects / tasks that span sessions;sessionsis a SET of every session_id that touched the work.
What ships with it
9 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.
- 1mo ago First seen · 316 lines · 0 tokens per session scan A 4466b27cb3a3
docs is a skill published in the GitHub repository madezmedia/acmi (5 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,436 tokens. 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 2026-08-31.
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