hybridmind: Skill for Claude Code

.agents/skills/hybridmind-mcp-use/SKILL.md

hybridmind-mcp-use is a skill for Claude Code, Codex from a3ro-dev/hybridmind. It costs 50 tokens per session (742 once invoked), scanned A, original, MIT.

Instructions for an AI assistant to use HybridMind, a memory server that stores and retrieves facts across chat sessions.

In plain words
What is it for?
Saving, finding, connecting, and deleting long-term conversation memories.
Why use it?
It helps the assistant remember useful user preferences and project details instead of treating every conversation as new.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is a3ro-dev/hybridmind's own configuration. It tells Claude Code and Codex how to work on hybridmind itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything hybridmind configures →

Reuse

Borrowing it

Nothing to install: this file belongs to a3ro-dev/hybridmind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/a3ro-dev/hybridmind/main/.agents/skills/hybridmind-mcp-use/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/a3ro-dev/hybridmind

Made for: Claude Code, Codex.

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Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 742 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.00742
Opus 5 $0.00025 $0.00371
Sonnet 5 $0.00010 $0.00148
Haiku 4.5 $0.00005 $0.00074

Measured 10d ago against content hash f3752cf6d401, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

hybridmind-mcp-use 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 10d 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.

.agents/skills/hybridmind-mcp-use/SKILL.md · 49 lines

How it starts

The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Using HybridMind MCP Memory Server

As an AI assistant connected to HybridMind, you have access to four tools to maintain long-term memory across chat sessions.

Available Tools

  1. remember(text: str, metadata: dict = None)

    • When to use: Whenever the user shares a fact about themselves, their preferences, project details, or other important episodic memories.
    • Metadata recommendation: Always tag memories with {"session_id": "current_session_id"} and a category like {"type": "user_preference"} or {"type": "project_fact"} to make retrieval cleaner.
    • Example: remember(text="Alice prefers Python over TypeScript for data science scripts", metadata={"session_id": "sess_123", "type": "user_preference"})
  2. recall(query: str, top_k: int = 10, mode: str = "hybrid")

    • When to use: At the beginning of a conversation or when the user asks a question about past interactions or stored facts.
    • Modes:
      • hybrid (default): Combined vector and graph proximity retrieval. Best for most queries.
      • vector: Pure semantic search.
    • Example: recall(query="What are Alice's programming language preferences?")
  3. relate(source_id: str, target_id: str, relationship: str = "related_to", weight: float = 1.0)

    • When to use: When storing a new memory that is directly connected, caused by, or contradicts an existing memory.
    • Common relationship types:
      • caused_by / led_to: Causal chains of events.
      • contradicts: When a new memory invalidates or conflicts with an old one.
      • supports: Evidentiary links.
      • supersedes: When a new memory replaces an old one (e.g. updating an address or preference).
    • Example: relate(source_id="new_node_id", target_id="old_node_id", relationship="supersedes")
  4. forget(node_id: str)

    • When to use: When the user explicitly requests to delete a specific memory, or when a memory is completely superseded and no longer relevant.
    • Note: This performs a soft-delete (the node is marked as deleted but stays in the DB until the next compact operation).

Read the full file on GitHub · 49 lines

Changes

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.

  1. 10d ago First seen · 49 lines · 50 tokens per session scan A f3752cf6d401

Subscribe to this mod's changes

hybridmind-mcp-use is a skill published in the GitHub repository a3ro-dev/hybridmind (5 stars, last pushed 14d ago), licensed MIT. It adds 50 tokens to every session and 742 once invoked, about $0.0003 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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