AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
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 sickn33/agentic-awesome-skills --skill agent-memory-systemsgit clone --depth 1 https://github.com/sickn33/agentic-awesome-skillsWrote 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/sickn33/agentic-awesome-skills/agent-memory-systems)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/agent-memory-systems"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/agent-memory-systems/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/sickn33/agentic-awesome-skills/agent-memory-systems"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/agent-memory-systems.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00033 | $0.00534 |
| Opus 5.5 | $0.00013 | $0.00214 |
| Sonnet 5.5 | $0.00007 | $0.00107 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
agent-memory-systems 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- agent-memory-systems — 100% identical, 1,083 lines differ
- agent-memory-systems — 100% identical, 41 lines differ
- agent-memory-systems — 100% identical, 1,083 lines differ
- agent-memory-systems — 100% identical, 1,083 lines differ
- agent-memory-systems — 100% identical, 1,087 lines differ
- agent-memory-systems — 100% identical, 1,083 lines differ
- agent-memory-systems — 100% identical, 1,083 lines differ
- agent-memory-systems — 100% identical, 1,083 lines differ
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Memory Systems
Choose semantic records for facts/preferences, episodic records for events, and procedural records for reusable methods. Keep retrieval quality separate from storage volume and bind persistent access to verified identity.
Procedure
- Establish the actual task, authenticated tenant/user, permission to retain content, retention limits and existing store/model versions.
- Read the guide's tenant-scoped contract and relevant storage/chunking sections. Select an adapter supported by the installed SDK; the guide's historical sketches are not deployable integrations.
- Specify record IDs, source evidence, timestamps, namespace, retrieval limits and conflict/version policy. Preserve originals and propose consolidation without deletion.
- Test cross-identity rejection, stale/conflicting records, bounded retrieval and failed writes with isolated fixtures. Benchmark retrieval against held-out questions before expanding storage.
- Deliver the architecture and evidence-backed change plan, listing unresolved adapters and hosted cost/data destinations. Apply only the persistence or provider operations actually authorized.
Detailed Guide
Read the detailed guide before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.
When to Use
- Design memory namespaces and retention for an agent serving distinct tenants or users.
- Diagnose retrieval of stale, conflicting or unauthorized conversation records.
- Plan an embedding/store migration while preserving source records and verifying isolation.
Example
Request: “Our support agent forgets preferences between sessions. Design memory for two customer tenants without sharing their history.”
Output: Load the tenant-scoped contract and background-extraction sections. Propose a semantic namespace per verified tenant/user, records with source IDs and revisions, and bounded retrieval. Retain conflicting preferences until the owner resolves them; include tests that tenant B cannot retrieve or consolidate tenant A records. Identify the existing persistent adapter and consent/retention evidence before any write.
What ships with it
1 file 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 Changed · -15 lines · -18 tokens per session 22f3841f3ad9
- 1mo ago Changed · -1,034 lines a288f3315fe0
- 1mo ago First seen · 1,089 lines · 51 tokens per session scan A 2003324855b6
agent-memory-systems is a skill published in the GitHub repository sickn33/agentic-awesome-skills (48,465 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 534 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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