AG Kit is a toolkit that gives Google Antigravity coding agents a structured workspace with rules, skills, specialist agents, workflows, persistent memory, orchestration, MCP guidance, and a safety hook. It is for building and operating agent workflows in Antigravity, and its catalogue entries provide parts of that workspace contract.
Borrowing it
Nothing to install: this file belongs to vudovn/ag-kit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/vudovn/ag-kit/main/.agents/skills/memory-system/SKILL.mdgit clone --depth 1 https://github.com/vudovn/ag-kitWrote 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/vudovn/ag-kit/memory-system)<a href="https://agentmods.dev/skills/vudovn/ag-kit/memory-system"><img src="https://agentmods.dev/badge/skills/vudovn/ag-kit/memory-system/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/vudovn/ag-kit/memory-system"><img src="https://agentmods.dev/badge/skills/vudovn/ag-kit/memory-system.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 56 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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 | $0.00035 | $0.01468 |
| Opus 5.5 | $0.00014 | $0.00587 |
| Sonnet 5.5 | $0.00007 | $0.00294 |
| Haiku 4.5 | $0.00003 | $0.00147 |
Grade A, and why
memory-system 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory System — Persistent Cross-Session Memory
Enables agents to remember across sessions. Never re-discover what was already learned.
Overview
The Memory System provides persistent, searchable memory that survives across sessions. Instead of re-explaining preferences, conventions, and past decisions every time, agents read a structured MEMORY.md index and topic files.
Token Impact: +1,000 tokens to load index, but saves 3,000-10,000 tokens by eliminating re-discovery.
Architecture
.agents/memory/
├── MEMORY.md ← Lightweight index (max 200 lines)
├── user-preferences.md ← Topic file: user role, style, tools
├── project-conventions.md ← Topic file: coding standards, patterns
├── tech-decisions.md ← Topic file: past architectural decisions
├── feedback-history.md ← Topic file: what user liked/disliked
└── [topic-name].md ← Additional topic files as needed
MEMORY.md Index Format
The index is a lightweight pointer file — short entries that reference topic files for details.
Rules:
- Maximum 200 lines total
- Each entry: ~150 characters max
- Format:
- [type] summary → topic-file.md - Types:
[user][feedback][project][reference]
Example:
# Memory Index
## User
- [user] Prefers dark mode, uses Windows 11, PowerShell → user-preferences.md
- [user] Senior DevOps engineer, 8 years experience → user-preferences.md
- [user] Primary language: English, sometimes Turkish → user-preferences.md
## Project
- [project] Always use bun instead of npm → project-conventions.md
- [project] Tailwind v4 preferred, no v3 → tech-decisions.md
- [project] No purple/violet colors in UI → project-conventions.md
## Feedback
- [feedback] User likes concise responses, no filler → feedback-history.md
- [feedback] User dislikes verbose explanations → feedback-history.md
- [feedback] User prefers tables over bullet lists → feedback-history.md
## Reference
- [reference] Squid proxy runs on port 3128 → infrastructure-notes.md
- [reference] Git workflow: feature branches → main → project-conventions.md
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 · 183 lines · 35 tokens per session scan A 40ffe215156b
memory-system is a skill published in the GitHub repository vudovn/ag-kit (8,199 stars, last pushed 3d ago), licensed MIT. It adds 35 tokens to every session and 1,468 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.
Other skills, from other repositories
mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.