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 mehmetdemirci/comb-ai --skill adopt-memory-bankgit clone --depth 1 https://github.com/mehmetdemirci/comb-aiWrote 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/mehmetdemirci/comb-ai/adopt-memory-bank)<a href="https://agentmods.dev/skills/mehmetdemirci/comb-ai/adopt-memory-bank"><img src="https://agentmods.dev/badge/skills/mehmetdemirci/comb-ai/adopt-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/mehmetdemirci/comb-ai/adopt-memory-bank"><img src="https://agentmods.dev/badge/skills/mehmetdemirci/comb-ai/adopt-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 | $0.00042 | $0.01306 |
| Opus 5 | $0.00021 | $0.00653 |
| Sonnet 5 | $0.00008 | $0.00261 |
| Haiku 4.5 | $0.00004 | $0.00131 |
Grade A, and why
adopt-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 12d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adopt Memory Bank — Brownfield Projects
Add a COMB memory bank to the existing $0 project by analyzing its current state.
Unlike
/create-memory-bank(greenfield), this skill reverse-engineers the project's architecture, dependencies, and patterns from the existing codebase.
Process
Step 1 — Analyze the codebase
Explore the project without asking the user first:
- Project structure: Read the directory layout, identify layers (backend, frontend, infra, etc.)
- Dependencies: Read package.json, *.csproj, go.mod, Cargo.toml, requirements.txt, etc.
- Configuration: Read config files, environment setup, CI/CD pipelines
- Existing docs: Check for README.md, CONTRIBUTING.md, architecture docs, ADRs
- Git history: Run
git log --oneline -20to understand recent development focus - Test setup: Identify test frameworks, coverage configuration
Step 2 — Summarize findings to user
Present a summary of what was discovered:
Project Analysis: $0
Structure:
- Backend: [detected tech] at [path]
- Frontend: [detected tech] at [path]
- Infrastructure: [detected setup]
Dependencies: [count] packages ([key ones listed])
Test coverage: [if detectable]
Recent focus: [based on git log]
Existing docs: [list found]
Does this look correct? Anything to add or correct?
Step 3 — Confirm domains with user
Ask the user:
- Are the detected domains correct? Any missing?
- What's the current sprint/phase? (or "no sprints — maintenance mode")
- Are there active blockers or decisions pending?
- Any patterns or conventions not obvious from code?
Step 4 — Create directory structure
Same as greenfield but pre-filled:
memory-bank/
├── INDEX.md ← Pre-filled from analysis
├── core/
│ ├── projectbrief.md ← Extracted from existing docs + analysis
│ ├── productContext.md ← From README/docs or user input
│ ├── active-context.md ← Current state from git log + user input
│ └── sprint-tracker.md ← Current sprint if applicable
├── tech/
│ └── [domain]-stack.md ← Auto-generated from dependency analysis
└── arch/
├── patterns-overview.md ← Inferred from code structure
└── decisions-summary.md ← From existing ADRs or inferred
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.
- 12d ago First seen · 152 lines · 42 tokens per session scan A ae5b2fa6c251
adopt-memory-bank is a skill published in the GitHub repository mehmetdemirci/comb-ai (13 stars, last pushed 6mo ago), licensed MIT. It adds 42 tokens to every session and 1,306 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
pneuma-preferences
Persistent user preference memory across sessions. Consult this skill BEFORE making any design, style, or aesthetic decisions — choosing colors, themes, layouts, fonts, tone of voice, content density, or visual direction. Also consult when starting a new creative task in any mode, when the user corrects your style…
context-engineering
Manage what goes into the AI agent context window for maximum quality and minimum waste.
Vibsync setup
Use when installing or connecting the Vibsync MCP server (the shared team brain for AI coding agents), or troubleshooting why Vibsync tools (onboard, recall, remember) aren't available or a connection isn't showing. Covers the one-time browser OAuth connect, team approval, and verifying the first handoff.
agent-carnet
Use this skill when the user asks to save, recall, find, or organize notes. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check the notebook', 'find in carnet'. Also use proactively when discovering findings worth preserving across sessions.
mnemos
Task-scoped memory lifecycle — typed MnemoGraph prevents lossy context compaction by treating facts/decisions/code-refs/handoffs as distinct node types with per-type eviction policies.
rust-project
Modern Rust project architecture guide for 2025. Use when creating Rust projects (CLI, web services, libraries). Covers workspace structure, error handling, async patterns, and idiomatic Rust best practices.