build_research_digest
Generate a digest of new (unseen) articles from RSS feeds. Compares against previously seen articles via SQLite. Returns only new items grouped by category. After generating, articles are marked as seen so the next digest only shows truly new content. Output formats: markdown (default), json, or ...
This record as markdown: /tools/io-github-homenshum-nodebench/build-research-digest.md
What build_research_digest does on Nodebench
AI agents invoke build_research_digest to trigger actions in Nodebench. 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.
Why build_research_digest is rated High
build_research_digest 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.
Attacks that exploit this kind of access
The rule that runs build_research_digest safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Nodebench, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For build_research_digest, this is the rule to start with:
build_research_digest 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 Nodebench, apply this rule, and every build_research_digest call is checked against it from then on.
Questions about build_research_digest
Generate a digest of new (unseen) articles from RSS feeds. Compares against previously seen articles via SQLite. Returns only new items grouped by category. After generating, articles are marked as seen so the next digest only shows truly new content. Output formats: markdown (default), json, or html (ready for send_email). It is categorised as a Execute tool in the Nodebench MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Nodebench MCP server in PolicyLayer and add a rule for build_research_digest: 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 Nodebench. Nothing to install.
build_research_digest 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 build_research_digest 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 build_research_digest. 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.
build_research_digest is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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