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 agentmods add rules/kfnzero/mantis-mcp-server/system-overviewgit clone --depth 1 https://github.com/kfnzero/mantis-mcp-serverWhat 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 | $0.00009 | $0.01838 |
| Opus 5 | $0.00005 | $0.00919 |
| Sonnet 5 | $0.00002 | $0.00368 |
| Haiku 4.5 | $0.00001 | $0.00184 |
Grade A, and why
system-overview 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 2d 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 — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADAPTIVE MEMORY BANK SYSTEM OVERVIEW
TL;DR: This system uses structured documentation as AI memory across sessions. It offers four complexity levels that scale from quick bug fixes to complex systems, adapting the process while maintaining documentation quality. Tasks.md serves as the single source of truth for task tracking.
🎯 SYSTEM PURPOSE
The Adaptive Memory Bank System creates persistent memory for AI assistants through structured documentation that scales based on task complexity. It addresses the fundamental limitation of LLMs forgetting context between interactions.
🧠 CORE PRINCIPLES
- Documentation as Memory - Documentation is mission-critical infrastructure
- Adaptive Process Scaling - Process complexity matches task requirements
- Single Source of Truth - Tasks.md is the only place for task status tracking
- Strategic Content Organization - Balance between core files and detailed examples
- Verification Steps - Explicit checks prevent steps from being skipped
- Reference Triggers - Force documentation consultation at critical points
- Processing Efficiency - Optimized structure for LLM comprehension
- Structured Creative Thinking - Creative phases as dedicated thinking spaces for complex problem-solving
📏 ADAPTIVE PROCESS LEVELS
Level 1: Quick Bug Fix
- Focus: Simple errors, UI glitches, minor issues
- Process: Streamlined with minimal documentation
- Task Updates: 2-3 updates (start/end)
- Memory Bank Impact: Targeted updates to relevant files
Level 2: Simple Enhancement
- Focus: Small features, minor improvements
- Process: Basic with essential documentation
- Task Updates: 4-6 updates at key milestones
- Memory Bank Impact: Updates to related files
Level 3: Intermediate Feature
- Focus: Complete features, significant changes
- Process: Standard with full section tracking
- Task Updates: 8-12 updates at defined points
- Memory Bank Impact: Comprehensive updates to most files
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.
- 2d ago First seen · 219 lines · 9 tokens per session scan A fb1082e38c75
system-overview is a cursor rule published in the GitHub repository kfnzero/mantis-mcp-server (10 stars, last pushed 12mo ago), licensed MIT. It adds 9 tokens to every session and 1,838 once invoked, about $0.0000 per session on Opus 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.
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