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 mahmoud20138/Tradecraft --skill agentic-storagegit clone --depth 1 https://github.com/mahmoud20138/TradecraftWrote 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/mahmoud20138/tradecraft/agentic-storage)<a href="https://agentmods.dev/skills/mahmoud20138/tradecraft/agentic-storage"><img src="https://agentmods.dev/badge/skills/mahmoud20138/tradecraft/agentic-storage/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/mahmoud20138/tradecraft/agentic-storage"><img src="https://agentmods.dev/badge/skills/mahmoud20138/tradecraft/agentic-storage.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 | $0.00189 | $0.02382 |
| Opus 5.5 | $0.00076 | $0.00953 |
| Sonnet 5.5 | $0.00038 | $0.00476 |
| Haiku 4.5 | $0.00019 | $0.00238 |
Grade A, and why
agentic-storage 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 — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Storage — Persistent Memory for AI Agents
Source: IBM Technology — Martin Keen (March 2026). "What Is Agentic Storage? Solving AI's Limits with LLMs & MCP." 51K+ views.
The Problem: Agents Are Stateless
AI agents powered by LLMs have a fundamental limitation:
Agent Session
│
├── Context Window = RAM (volatile, temporary)
│
└── Session ends → Memory resets → Agent forgets everything
- The context window is like RAM — volatile, temporary storage
- When a session ends or the context fills up, the agent's memory resets completely
- The agent forgets what it did, what it produced, what it learned
RAG Only Partially Helps
RAG (Retrieval Augmented Generation) connects the LLM to a vector database for semantic search.
But RAG is fundamentally read-only:
| Problem | RAG Solves? |
|---|---|
| Getting information INTO the model (input) | Yes |
| Persisting agent work products (output) | No |
If your agent writes a Python script, creates a remediation playbook, or generates a report — where does that work product actually go? RAG doesn't answer this.
What Is Agentic Storage?
Storage that is aware of and designed for autonomous agents.
It's more than giving an agent a hard drive. It's a storage layer purpose-built for AI agents:
- Persists work products between sessions (code, playbooks, reports, analysis)
- Standardized access via MCP (no custom API integrations per storage system)
- Safety layers built in for autonomous operation
- Audit trail for every agent action
The Analogy
| Concept | Human Computer | AI Agent |
|---|---|---|
| Volatile memory | RAM | Context window |
| Persistent storage | Hard drive / SSD | Agentic storage |
| File system | OS file system | MCP server |
| Access control | User permissions | Sandboxing + intent validation |
MCP as the Storage Interface
The Problem with Custom Integrations
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 · 298 lines · 189 tokens per session scan A 1cb7acd72860
agentic-storage is a skill published in the GitHub repository mahmoud20138/Tradecraft (17 stars, last pushed 6mo ago), licensed MIT. It adds 189 tokens to every session and 2,382 once invoked, about $0.0008 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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