record_work_item_criterion_engineering_proof
Record a structured, non-media Engineering verified receipt for one criterion in its current QA dwell. Use this only when the criterion is explicitly routed engineering or both. It records the exact build, environment, outcome, named code/test/configuration/data/runtime references, and the narrow...
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What record_work_item_criterion_engineering_proof does on Adrata
AI agents invoke record_work_item_criterion_engineering_proof to trigger actions in Adrata. 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 record_work_item_criterion_engineering_proof is rated High
record_work_item_criterion_engineering_proof 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 record_work_item_criterion_engineering_proof safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Adrata, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For record_work_item_criterion_engineering_proof, this is the rule to start with:
record_work_item_criterion_engineering_proof 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 Adrata, apply this rule, and every record_work_item_criterion_engineering_proof call is checked against it from then on.
Questions about record_work_item_criterion_engineering_proof
Record a structured, non-media Engineering verified receipt for one criterion in its current QA dwell. Use this only when the criterion is explicitly routed engineering or both. It records the exact build, environment, outcome, named code/test/configuration/data/runtime references, and the narrowest honest runtime smoke. Local CLI or isolated runtime checks must declare local; they do not establish a staging deployment or a product user journey. It does not upload an image or video and must never be described as a visual or user-journey pass. QA2 requires a different authenticated credential from the passing QA1 engineering receipt.${GOVERNED_NOTE}. It is categorised as a Execute tool in the Adrata MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Adrata MCP server in PolicyLayer and add a rule for record_work_item_criterion_engineering_proof: 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 Adrata. Nothing to install.
record_work_item_criterion_engineering_proof 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 record_work_item_criterion_engineering_proof 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 record_work_item_criterion_engineering_proof. 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.
record_work_item_criterion_engineering_proof is provided by the Adrata MCP server (@adrata/adrata-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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