Unverified50% confidenceFactExact time
agent-audit-mcp provides three tool methods: audit_agent_step (audit a single step), audit_agent_session (audit an entire session trajectory), and encode_state (convert between nine-dimensional vectors and enumeration keys/balance values and compute Hamming distance).
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/18/2026
First Seen
Valid until: 1/16/2027
Sources
Related Entities
Related Claims
Unverifiedagent-audit-mcp describes each decision step with 9 observation dimensions (structure, function, relation, attribute, time, context, causality, value, evolution), with each dimension taking one of three states: ⊕(+1), 0, ⊖(-1).73% similarUnverifiedA complete Agent typically consists of multiple components including prompts, MCP Server configurations, Skills, and policies, making it a composite entity rather than a single weight file.69% similarUnverifiedAgent Seer performs scenario inference along three dimensions—single-tool usage patterns, multi-tool combination patterns, and multi-turn dialogue iteration processes—based on a tool's function name, description, and parameter schema.69% similarUnverifiedThe author of agent-audit-mcp plans next to use the cumulative change in Hamming distance to detect Agent decision drift in long sessions.69% similarUnverifiedAgents are particularly good at three types of tasks that require judgment and action: multi-source information integration, multi-step correlated operations, and continuous status monitoring.68% similar
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