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Engra

Agent Skills open standard

Engra ships a cross-agent SKILL.md verified on Cursor, Claude Code, OpenClaw, VS Code Copilot, Windsurf, Cline, and OpenCode. Pair it with Memory MCP for a durable memory workflow.

Integration versions v1.9.0

REST API
v1.6.0
MCP
v1.9.0
Agent Skill
v1.9.0
Memory engine
v0.5.0

Declared in skills/engra-memory/SKILL.md frontmatter (version field).

What is an Agent Skill?

Agent Skills follow the open Agent Skills standard: YAML frontmatter (name, description) plus markdown instructions. Hosts match skills by description and load them on demand. The same SKILL.md works across many coding agents; Engra Memory also requires Memory MCP in your client to call tools like memory_search.

Recommended (Skill + MCP)

AgentPersonalProject
Cursor~/.cursor/skills/.cursor/skills/
Claude Code~/.claude/skills/.claude/skills/
OpenClaw~/.openclaw/skills/.openclaw/skills/
VS Code + Copilot.github/skills/
Windsurf~/.windsurf/skills/.windsurf/skills/
Cline~/.cline/skills/.cline/skills/
OpenCode~/.config/opencode/skills/.opencode/skills/

Official skill: skills/engra-memory/SKILL.md. Copy the entire engra-memory directory to the path for your agent. See the Memory MCP guide for MCP setup.

skills/engra-memory/SKILL.md

More SKILL.md-compatible tools

These tools also support the Agent Skills standard — reuse skills/engra-memory/SKILL.md as-is. MCP setup varies by client; configure the Streamable HTTP endpoint per tool docs: OpenAI Codex CLI (~/.codex/skills/), Gemini CLI, Roo Code, Goose, Amp, JetBrains Junie, and others. See agentskills.io for the full list.

Installation

  1. Create an API key in the console (/dashboard/keys) with memory:read; add memory:write for saves
  2. Add MCP config to your client (see example below or skills/engra-memory/mcp.example.json)
  3. Copy skills/engra-memory/ to your personal or project agent skills directory
  4. Restart the agent or reload skills; verify memory_list_libraries is available
  5. On new sessions the agent should follow the skill and call memory_wake_up / memory_search

MCP configuration (skill prerequisite)

The skill teaches how to use memory tools; the tools themselves come from Memory MCP. Configure both: MCP for connectivity, the skill for workflow and trigger timing.

{
  "mcpServers": {
    "engra-memory": {
      "url": "https://mcp.engra.ai/api/v1/memory/mcp",
      "headers": {
        "Authorization": "Bearer inf_xxxxxxxx",
        "Accept": "application/json, text/event-stream",
        "Content-Type": "application/json"
      }
    }
  }
}

OpenClaw / Claude plugin bundle layout

OpenClaw loads Claude-format bundles natively: skills/ roots become skills, and .mcp.json merges into embedded MCP settings. Package the Engra skill with MCP config for team distribution.

your-team-bundle/
├── skills/engra-memory/SKILL.md
├── skills/engra-memory/TAXONOMY.md
└── .mcp.json

Recommended workflow (in skill)

  1. memory_list_libraries → obtain memoryLibraryId (use a separate library for sensitive domains)
  2. New session → memory_wake_up (pass the user's opening message)
  3. Need prior context → memory_search / memory_recall
  4. Durable knowledge emerges → proactively memory_save_atom (one fact per atom; self-contained body; search first to dedupe; set scope/topic)
  5. Outdated search hits → memory_correct_atom (avoid duplicate saves; keep revisions)
  6. Write tools default to async (202 + job.id): fast ack, background persist; do not expect immediate search hits
  7. Task done or session ending → save decisions and lessons learned

OpenClaw notes

  • Claude commands/ and Cursor .cursor/commands/ map to additional OpenClaw skill roots
  • When migrating from Claude, skills with SKILL.md copy into the OpenClaw workspace skills directory
  • Imported Claude commands default to disable-model-invocation: true — edit frontmatter for auto-invocation
  • See OpenClaw docs: Plugin bundles and Migrating from Claude

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