check_run
Run all pre-deployment checks (typecheck, lint, format, tests, build, bundle size, security audit, env vars, git clean).
This record as markdown: /tools/io-github-kivanccakmak-yaver/check-run.md
What check_run does on Yaver
AI agents invoke check_run to trigger actions in Yaver. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
fix | boolean | — | Auto-fix lint/format issues |
skip | array | — | Check names to skip |
Parameters from the server's own tool schema.
Why check_run is rated High
This tool executes multiple external processes (type checking, linting, formatting, test runners, build system, bundle analysis, security audit, git commands). These are active executions with potential side effects such as filesystem modifications, network calls during security audits, and spawning subprocesses.
From the tool's definition 'Run all pre-deployment checks (typecheck, lint, format, tests, build, bundle size, security audit, env vars, git clean)' — explicitly runs multiple processes including builds, tests, and audits
Attacks that exploit this kind of access
The rule that runs check_run safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For check_run, this is the rule to start with:
check_run stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Yaver, apply this rule, and every check_run call is checked against it from then on.
Questions about check_run
Run all pre-deployment checks (typecheck, lint, format, tests, build, bundle size, security audit, env vars, git clean). It is categorised as a Execute tool in the Yaver MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
check_run accepts 2 parameters: fix, skip. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for check_run: 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 Yaver. Nothing to install.
check_run is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the check_run 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 check_run. 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.
check_run is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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