AgentOps: diagnose MCP tool shadowing before a production action
A production runbook for detecting MCP tool collisions, proving which tool the agent actually selected and validating a canary catalog before any sensitive action.
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27 articles connected to this technical signal.
A production runbook for detecting MCP tool collisions, proving which tool the agent actually selected and validating a canary catalog before any sensitive action.
Read articleA production runbook for separating source, tracking, skillset and document failures in Azure AI Search before rerunning, targeting recovery or resetting the indexer.
Read articleA production runbook for bounding a leak in agent traces, locating the unsafe field, canarying redaction and restoring useful observability.
Read articleA production runbook for proving that an agent fallback model preserves structured outputs, tool boundaries, refusals and traceability before routing live traffic.
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Read articleA production runbook for separating agent regression from evaluator drift by freezing outputs, replaying an adjudicated anchor set, measuring disagreement and keeping promotion rollbackable.
Read articleA production runbook for separating blocked prompts, filtered outputs, application errors and policy drift before changing Microsoft Foundry guardrails.
Read articleA production runbook for qualifying circuit breakers, Retry-After, Microsoft Foundry backend pools, canary traffic, observability and rollback before enabling AI API failover.
Read articleA production runbook for bounding evidence age across retrieval, telemetry and tool results before an AI agent proposes, executes or rolls back an operational action.
Read articleA production runbook for qualifying an AI agent regional failover across model deployment, state, retrieval, tools, identity, traces, canary traffic, validation and rollback.
Read articleA production runbook for detecting and revalidating stale human approval across state drift, request fingerprints, expiry, traces, refusal tests and rollback before an AI agent resumes an action.
Read articleA production runbook for reconstructing an AI agent's context, isolating history, retrieval and tool outputs, then validating compaction or rolling back.
Read articleA production runbook to test a Toolbox version, its MCP tools, identities, approvals and traces before promotion, then return to the previous version without redeploying agents.
Read articleA production runbook for qualifying structured AI agent tool output with schema, sources, diff, idempotence, policy, traces, human validation and rollback before writing to production.
Read articleA production runbook for qualifying AI agent permission drift with the real identity, RBAC, tool scopes, traces, expected denials, human validation and rollback before widening access.
Read articleA production runbook for qualifying the handoff from a Microsoft Foundry agent to Azure Automation, AWX, Azure DevOps or an MCP tool with contract, identity, traces, dry run, human validation and rollback.
Read articleA production runbook for qualifying a failed AI agent tool call with trace evidence, idempotence, identity, backend state, approvals, validation and rollback before retrying.
Read articleA production runbook for qualifying AI agent memory with sources, traces, aging, permissions, evaluations, guardrails, human validation and rollback before it influences real actions.
Read articleA production runbook for qualifying an AI agent evaluation set with business cases, retrieval, tool calls, traces, thresholds, human validation and rollback before promotion.
Read articleA production runbook for qualifying Microsoft Foundry agent guardrails with sources, refusals, tools, identity, traces, canary, human validation and rollback before user exposure.
Read articleA production runbook for qualifying suspected prompt injection in an AI agent retrieval corpus with sources, traces, evaluation, tools, guardrails, validation and rollback.
Read articleA production runbook for qualifying an agent approval policy change with action scope, identity, traces, evaluation cases, guardrails, human validation and rollback.
Read articleA production runbook for qualifying Azure OpenAI or Microsoft Foundry throttling with quota, deployment capacity, agent traces, retries, fallback, validation and rollback before changing models.
Read articleA production runbook for rotating or revoking an AI agent runtime identity with scoped permissions, dry-run tool calls, traces, approvals, validation and rollback before breaking production actions.
Read articleA production runbook for qualifying a new AI agent tool with contract review, scoped identity, dry run, traces, approvals, evaluation cases and rollback before enabling real actions.
Read articleA production runbook for qualifying a retrieval index update with source diff, metadata, chunking, evaluations, traces, human validation and rollback before changing an AI agent's answers.
Read articleA runbook for validating an AI agent before real action by separating sources, tools, identity, evaluation cases, human approvals, logs and rollback.
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