registry_get_skill
Fetch everything an agent needs to adopt a Registry skill: the full SKILL.md (agentskills.io standard — frontmatter name/description + body), its classification (prompt-shaped vs scripted vs mcp), and required binaries. To install: save the returned skill_md as SKILL.md inside a folder named afte...
This record as markdown: /tools/ai-rokha-rokha/registry-get-skill.md
What registry_get_skill does on Rokha
AI agents call registry_get_skill to retrieve information from Rokha without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
slug | string | Yes | The skill's slug from registry_search (e.g. 'ui-design') |
provider | string | — | Registry provider from registry_search (e.g. 'rokha', 'clawhub', 'smithery'). Omit to auto-resolve: first-party 'rokha' listings are tried first, then 'clawhub' |
Parameters from the server's own tool schema.
Why registry_get_skill is rated Low
Tool retrieves skill metadata and documentation without modifying data or triggering execution.
From the tool's definition Fetch everything an agent needs to adopt a Registry skill: the full SKILL.md, classification, required binaries.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs registry_get_skill safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Rokha, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For registry_get_skill, this is the rule to start with:
registry_get_skill is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Rokha, apply this rule, and every registry_get_skill call is checked against it from then on.
Questions about registry_get_skill
Fetch everything an agent needs to adopt a Registry skill: the full SKILL.md (agentskills.io standard — frontmatter name/description + body), its classification (prompt-shaped vs scripted vs mcp), and required binaries. To install: save the returned skill_md as SKILL.md inside a folder named after the slug in your agent's skills directory. It is categorised as a Read tool in the Rokha MCP Server, which means it retrieves data without modifying state.
registry_get_skill accepts 2 parameters: slug, provider. Required: slug. The full parameter table on this page comes from the server's own tool schema.
Register the Rokha MCP server in PolicyLayer and add a rule for registry_get_skill: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Rokha. Nothing to install.
registry_get_skill is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the registry_get_skill rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for registry_get_skill. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
registry_get_skill is provided by the Rokha MCP server (https://rokha.ai/mcp/jsonrpc). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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