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 parisgroup-ai/imersao-ia-setup --skill memory-bankgit clone --depth 1 https://github.com/parisgroup-ai/imersao-ia-setupWrote 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/parisgroup-ai/imersao-ia-setup/memory-bank)<a href="https://agentmods.dev/skills/parisgroup-ai/imersao-ia-setup/memory-bank"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/memory-bank/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/parisgroup-ai/imersao-ia-setup/memory-bank"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/memory-bank.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 | $0.00070 | $0.04436 |
| Opus 5.5 | $0.00028 | $0.01774 |
| Sonnet 5.5 | $0.00014 | $0.00887 |
| Haiku 4.5 | $0.00007 | $0.00444 |
Grade A, and why
memory-bank 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 — 770 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Bank Skill
This skill manages the project's memory-bank system - a structured set of files that preserve context between Claude Code sessions. The memory-bank ensures continuity, reduces repetitive explanations, and maintains project intelligence.
Core Philosophy
Claude's memory resets between sessions. The memory-bank serves as persistent project memory:
- Read memory-bank files at session start
- Use context throughout the session
- Update files before session ends or after significant changes
Memory Bank Structure
project-root/
├── CLAUDE.md # Primary entry point (required)
├── memory-bank/
│ ├── projectbrief.md # Foundation document
│ ├── productContext.md # Why and how
│ ├── activeContext.md # Current focus (update frequently)
│ ├── systemPatterns.md # Architecture patterns
│ ├── techContext.md # Technical details
│ ├── progress.md # What's done, what's next (keep slim!)
│ ├── errors.md # Known issues and solutions
│ └── archive/ # (Optional) Historical details
│ ├── index.md # Quick lookup for archived items
│ └── YYYY-MM.md # Monthly archives (e.g., 2025-12.md)
When to Archive
When progress.md exceeds ~500 lines, split it:
- Keep in progress.md: Current sprint, next up, milestone summary table, known issues
- Move to archive/: Detailed session logs, files created/modified, commits, lessons learned
This keeps progress.md scannable (<100 lines) while preserving full history.
File Hierarchy
┌─────────────────────────────────────────┐
│ CLAUDE.md │ ← Start here ALWAYS
│ (Entry Point) │
└─────────────────┬───────────────────────┘
│
▼
┌─────────────────────────────────────────┐
│ projectbrief.md │ ← Foundation
│ (Project Foundation) │
└─────────────────┬───────────────────────┘
│
┌─────────┴─────────┐
▼ ▼
┌───────────────┐ ┌───────────────┐
│ productContext│ │ techContext │ ← Core Context
│ (Why/How) │ │ (Stack/Tech) │
└───────┬───────┘ └───────┬───────┘
│ │
└─────────┬─────────┘
▼
┌─────────────────────────────────────────┐
│ systemPatterns.md │ ← Patterns
│ (Architecture Decisions) │
└─────────────────┬───────────────────────┘
│
▼
┌─────────────────────────────────────────┐
│ activeContext.md │ ← Current State
│ (Now + Next Actions) │
└─────────────────┬───────────────────────┘
│
▼
┌─────────────────────────────────────────┐
│ progress.md │ ← History
│ (Done + Remaining Work) │
└─────────────────────────────────────────┘
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 · 770 lines · 70 tokens per session scan A bc087931ebcb
memory-bank is a skill published in the GitHub repository parisgroup-ai/imersao-ia-setup (1 stars, last pushed 20d ago), licensed MIT. It adds 70 tokens to every session and 4,436 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
init-workspace-documentation
Skill "init-workspace-documentation" from griddynamics/rosetta, covering agent memory.md, agent memory, preventive rules, what worked and what failed.
forgetful-context-gather
Gather deep context before planning or implementing — one pass that turns a task description into a cited context pack: relevant decisions, patterns, constraints, code pointers, procedures, and explicit gaps. Runs recall from several angles, explores the graph around the strongest hits, and opens the linked material.
core
Use when knowledge base hub — PARA-structured company memory combining company-kb and kb for persistent context, project documentation, and agent recall across sessions. Use when working with knowledge base, company knowledge, or persistent memory.
berkahkarya-orchestrator
Use when orchestrate multi-skill workflows by routing tasks to the right agents and coordinating cross-platform operations.
langchain-patterns
Use when langChain/LangGraph patterns — chains, agents, tools, memory, retrieval, graph workflows. Use when working with langchain patterns.
kb-memory
Use when knowledge base and memory system for AI agents. Covers company KB, persistent memory, session recall, and brain architecture for context preservation.