Fetch the repo's agent-guidance files (CLAUDE.md, AGENTS.md, AI_ARCH.md, REMOTE_WORKER.md) plus the project's init.md. Every result is prefixed with a stale-docs warning. Use this at the start of a task for context, but remember: the docs may be out of date — always grep the code to verify claims...
AI agents invoke project_context 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 |
|---|---|---|---|
workDir | string | — | Project root (defaults to the agent's active work-dir). |
Parameters from the server's own tool schema.
project_context triggers real processes with real consequences. An agent gone sideways doesn't fire it once — it starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
Fetch the repo's agent-guidance files (CLAUDE.md, AGENTS.md, AI_ARCH.md, REMOTE_WORKER.md) plus the project's init.md. Every result is prefixed with a stale-docs warning. Use this at the start of a task for context, but remember: the docs may be out of date — always grep the code to verify claims before acting on them. 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.
project_context accepts 1 parameter: workDir. 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 project_context: 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.
project_context 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 project_context 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 project_context. 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.
project_context 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.