check_skill_freshness
Check if registered skills are stale by comparing current source file hashes
This record as markdown: /tools/io-github-homenshum-nodebench/check-skill-freshness.md
What check_skill_freshness does on Nodebench
AI agents call check_skill_freshness to retrieve information from Nodebench without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why check_skill_freshness is rated Low
This tool performs a read-only comparison operation. It checks the state of skill registrations by comparing hashes, which is intrinsically a data retrieval and analysis task with no side effects. There is no code execution, data modification, deletion, or financial impact. The blast radius of misuse is minimal—at worst, an agent receives stale/false information about skill status.
From the tool's definition Tool description states it 'Check[s] if registered skills are stale by comparing current source file hashes' — this is a comparison/query operation that retrieves hash information and performs analysis without modifying, deleting, or executing external code.
Attacks that exploit this kind of access
The rule that runs check_skill_freshness 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 check_skill_freshness, this is the rule to start with:
check_skill_freshness 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 Nodebench, apply this rule, and every check_skill_freshness call is checked against it from then on.
Questions about check_skill_freshness
Check if registered skills are stale by comparing current source file hashes. It is categorised as a Read tool in the Nodebench MCP Server, which means it retrieves data without modifying state.
Register the Nodebench MCP server in PolicyLayer and add a rule for check_skill_freshness: 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.
check_skill_freshness 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 check_skill_freshness 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_skill_freshness. 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_skill_freshness 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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