Translate scoring signals into business language. Map answers onto the SAME keys in
clarify.md Step 3 (do not invent new keys/values).
session_duration: “Does your agent answer in a few seconds, work for a few minutes,
work for hours, or run continuously?” → under_15min / 15min_to_8hr (minutes or hours) /
over_8hr.
traffic_pattern: “Is usage spiky with quiet gaps, or steady all day?” → bursty / steady / idle.
session_state: “Does a person approve the agent’s actions, or does it run on its own?”
→ hitl (approves) / stateful / stateless.
isolation: “Do your different customers’ data need to be strictly separated?” →
required / nice_to_have / not_needed.
memory_needs: “Should the agent remember a user across separate conversations?” →
cross_session / session_only / none.
ops_preference: “How hands-on do you want to be with infrastructure? just push code /
some control / full control.” → minimal / moderate / full_control.
compute_tier: “Does a task do heavy number-crunching (video, large data, ML), or mostly
call an AI model and wait?” → heavy_non_gpu / light; ask about GPU only if heavy.
instance_type_requirement: “Has your team been told the agent must run on a specific
kind of server (a particular machine size, a GPU, or ARM chips)? Most teams answer no.”
→ yes / no; default unknown if unsure.
idle_resume: “If a user steps away and comes back, must the work continue exactly where
it paused?” → process_level / filesystem / none.
launch_concurrency: “At peak, roughly how many new sessions start per second?” → high
(many) / moderate / low.
multi_agent: “One agent, or several working together?” → no / yes.
deployment_preference: “Would you rather AWS fully manage the agent for you (you just
describe it — no code to maintain), bring your own agent code, or let me recommend?” →
harness / framework / either. Ask early. Only affects the AgentCore deployment style, not which
runtime is chosen. Default either.
framework / existing_cluster / multi_cloud / platform_fit: ask in plain terms; default
to unknown if the user is unsure (the engine handles unknown safely).
model_priority: “What matters most for the AI — quality, speed, cost, or balanced?”
model_features: if they need something specific, ask “what’s the ONE most important thing
the AI must do?” in plain terms — e.g. use tools/APIs, read very long documents, deep step-by-
step reasoning, answer from your documents (RAG), understand images, generate images, handle
voice/speech, or produce embeddings. This picks a specialized model when needed (see
${CLAUDE_PLUGIN_ROOT}/skills/agent-advisor/references/decision-refs/model-selection.md). If nothing special →
none. current_model: migrate only (“what model are you on today?”).
region: “Where are your users — one region, a few, or global? Anywhere with data-residency
rules, like the EU?” Used to check the recommended service is available there, and — for EU or
GDPR — to flag the data-residency (CRIS) choice. Doesn’t change which runtime is recommended.