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 hybridlabor-api/bdb-dev-optimized-agent-skills --skill memb-skillgit clone --depth 1 https://github.com/hybridlabor-api/bdb-dev-optimized-agent-skillsWrote 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/hybridlabor-api/bdb-dev-optimized-agent-skills/memb-skill)<a href="https://agentmods.dev/skills/hybridlabor-api/bdb-dev-optimized-agent-skills/memb-skill"><img src="https://agentmods.dev/badge/skills/hybridlabor-api/bdb-dev-optimized-agent-skills/memb-skill.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.01904 |
| Opus 5 | $0.00018 | $0.00952 |
| Sonnet 5 | $0.00007 | $0.00381 |
| Haiku 4.5 | $0.00004 | $0.00190 |
Grade A, and why
memb-skill 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 4d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memB: Local Long-Term Memory Skill
This skill allows agents to access and maintain a persistent, offline-first long-term memory bank using the memb-mcp server. It manages user preferences, project structures, and complex developer workarounds.
🔒 Memory Safety & Secret Filtration
[!IMPORTANT] Secret Ingestion Rule: Under no circumstances should raw credentials, passwords, API keys (e.g.
GEMINI_API_KEY,POSTGRES_PRISMA_URL), or raw environment configurations be written to memory. Ensure all inputs are scrubbed of high-entropy strings before calling memory tools.
🛠️ Memory Categorization (Dynamic Flower-Like Graph Layout)
memB implements a dynamic, project-agnostic hierarchical layout that structures memories into clusters automatically without hardcoded categories:
- "God Mode" / General Knowledge Hub (Center):
- Mapped using
category="godmode"(withproject_id=None). - Holds universal developer preferences, coding philosophies, global style sheets, and general core commands.
- Mapped using
- Dynamic Project Leaves (Petals):
- Mapped using a specific
project_id(e.g.project_id="VisualSelect_By_BDB"orproject_id="litha-gathering"). - Isolates facts, custom configurations, and files routing patterns to the specific workspace project, preventing context pollution.
- System Integration: The agent dynamically resolves the basename of the active workspace directory to scan and bind project memories automatically.
- Mapped using a specific
🔌 Using Memory Tools
When working on tasks, query memory at the start of your turn to retrieve relevant developer context, and add critical decisions at the end.
1. Ingestion (add_memory)
Use add_memory to commit a new fact, style preference, or design decision.
- Args:
text(string),user_id(string, default: "bdb_developer"),category(string, default: "godmode"),project_id(string, optional) - Usage Guidelines:
- General Preferences: "Alice prefers to use absolute import paths globally." ->
add_memory({ text: "Prefers absolute import paths globally", category: "godmode" }) - Project Learned Facts: "In project VisualSelect, we must bypass the Firebase Auth login on localhost." ->
add_memory({ text: "Bypass Firebase Auth login on localhost", category: "project_node", project_id: "VisualSelect_By_BDB" })
- General Preferences: "Alice prefers to use absolute import paths globally." ->
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.
- 4d ago First seen · 136 lines · 36 tokens per session scan A 9af1cdbb9704
memb-skill is a skill published in the GitHub repository hybridlabor-api/bdb-dev-optimized-agent-skills (6 stars, last pushed 3d ago), licensed Apache-2.0. It adds 36 tokens to every session and 1,904 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 2026-09-03.
Other skills, from other repositories
mem0-integration
Mem0 memory layer integration for AI agents. Implement persistent, semantic memory for long-term context retention and personalization.
context-preservation
State capture and restore across context window compactions. Monitors usage thresholds and serializes quality, task, and spec state for seamless continuation.
persistent-memory
Observation capture and retrieval across sessions. Stores decisions, discoveries, and bugfix patterns. Searchable via tags and relevance scoring.
context-management
Project context loading, isolation, and persistent state management across CCPM sessions.
moai-foundation-context
Manages context window optimization, session state persistence, and token budget allocation for multi-agent workflows. Use for token budget management, context limits, or session handoff across agents.
session-memory
Mandatory memory persistence system across session resets using three markdown surfaces in .claude/cc10x/. Iron law - every workflow must load at start and update at end.