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Forty items across eight surfaces. Score 0 (absent), 1 (partial), 2 (solid) — for a vendor evaluation or an internal build review alike.

Loop & economics (Ch. 1, 4)

  • Per-task step, token, time, and spend budgets, with loop detection
  • Deterministic-rails execution: models select typed actions; code executes
  • Two-engine separation with a measurable promotion seam
  • Cost per resolved incident reportable at reference scale
  • Independent, state-based verification with soak windows and staged rollback

Context (Ch. 2)

  • Automated discovery producing a reviewable system map
  • Change-stream ingestion, time-ordered and attributable
  • Retrieval with re-ranking; context budgets; traceable compaction
  • Memory with provenance, decay, contradiction flags, and a human-curated tier
  • Knowledge and topology refresh with staleness handling

Tools & skills (Ch. 3)

  • Intent-shaped tools; structurally separated read vs. write paths
  • Size-capped, structured tool results with pointers to full data
  • Skills versioned in source control with owners, tests, and changelogs
  • Skill metadata declaring access class, reversibility, and blast radius
  • MCP supply chain: pinned versions, allowlists, contract tests, egress map

Security (Ch. 5)

  • Per-agent identity; short-lived scoped credentials; environment separation
  • Taint-tagged context with delimited untrusted material
  • Sandboxed execution (microVM-class) with no ambient credentials
  • Default-deny egress with allowlists and novel-destination alerts
  • PII/secret tokenization before every model boundary; guarded de-tokenization
  • Injection detection in telemetry and a standing red-team cadence

Policy & approvals (Ch. 6)

  • Two-axis action classification, machine-derivable from skill metadata
  • Versioned policy-as-code with review workflow, per environment and agent
  • One-screen approval artifacts with structured rejection capture
  • Pre-flight checks, staged application, circuit breakers, rate limits
  • Pre-staged executable rollback on every consequential action; drilled kill switch

Evaluation (Ch. 7)

  • Golden set harvested from real incidents; replay harness
  • Layered scoring incl. evidence integrity; state-based mitigation oracles
  • Calibrated judges plus a standing human grading slice
  • Regression gates on every prompt/tool/policy/model change, per class

Observability (Ch. 8)

  • One trace per incident: agent, step, tool, and model spans in an open schema (OTel GenAI)
  • Fleet metrics: quality, latency, cost, drift, security signals
  • SLOs wired to trust-ladder graduation criteria
  • Customer-exportable traces and audit data

Day 2 (Ch. 9)

  • Versioned bundles (prompts, tools, skills, policy, model pins); no invisible change
  • Model migration playbook with per-class diffs and canary lanes
  • Memory hygiene cadence with named ownership
  • Blameless agent postmortems feeding the golden set