io.github.Kromatic-Innovation/neumann

Purchases credits using a payment method already saved from a prior Stripe Checkout session. Use this when an authenticated account is running low on credits and needs more to keep submitting runs or analyses, without a human re-entering card details. See GET /billing/pricing for the current per-credit price. Example: {"credits":100}

Sends feedback, a feature request, or a bug report straight to the Neumann team, CC'ing your sender_email so you keep a copy. Use this when something about the service is wrong, missing, or confusing and you want a human to see it directly rather than guessing at a workaround. Anonymous submissions are allowed. Example: {"feedback_type":"feature_request","message":"Add CSV export for run results.","sender_email":"agent@example.com"}

Pre-flight-sizes a graph without running it: estimated peak memory, engine complexity, which tier (small/large) it would run as, and the credit cost. Use this when you want to know what a run will cost or how heavy it is before committing to it, especially for a large or unfamiliar graph. Free; no credits debited. Example: {"graph":{"root_nodes":[{"id":"root","distribution_type":"normal","distribution_params":{"mean":100,"std":15}}],"calc_nodes":[{"id":"out","formula":"{e1}"}],"edges":[{"id":"e1","source":"root","target":"out"}],"run_params":{"trials":1000,"time_periods":12}}}

Runs a one-at-a-time tornado sensitivity analysis: sweeps each root node over a set of quantiles (others held at baseline) and measures how the target node responds, ranked by impact. Use this when you need to know which uncertain input most drives an outcome, so you know what to de-risk or estimate more carefully first. Debits one credit for authenticated callers. Example: {"graph":{"root_nodes":[{"id":"root","distribution_type":"normal","distribution_params":{"mean":100,"std":15}}],"calc_nodes":[{"id":"out","formula":"{e1}"}],"edges":[{"id":"e1","source":"root","target":"out"}],"run_params":{"trials":1000,"time_periods":12}}}

Runs a Monte Carlo simulation over a graph of probabilistic root and calculated nodes, returning the full output distribution instead of one guessed number. Use this when you need the range and likelihood of outcomes for a plan driven by uncertain inputs, not just its average case. Both tiers run to completion and return the full result in this same call, never a run_id to poll. Example: {"graph":{"root_nodes":[{"id":"root","distribution_type":"normal","distribution_params":{"mean":100,"std":15}}],"calc_nodes":[{"id":"out","formula":"{e1}"}],"edges":[{"id":"e1","source":"root","target":"out"}],"run_params":{"trials":1000,"time_periods":12}}}

Runs a simulation once and summarises a target node's worst/median/best outcomes (any percentiles), each paired with a best-effort driving input per root node. Use this when you need a quick worst-case/median/best-case narrative for a plan rather than the full distribution. Debits one credit for authenticated callers. Example: {"graph":{"root_nodes":[{"id":"root","distribution_type":"normal","distribution_params":{"mean":100,"std":15}}],"calc_nodes":[{"id":"out","formula":"{e1}"}],"edges":[{"id":"e1","source":"root","target":"out"}],"run_params":{"trials":1000,"time_periods":12}}}

Creates (or fetches the existing) public share link for a PERSISTED run from the stored-graph flow, renderable as HTML/JSON/SVG. Use this when you want to hand a result to someone without giving them API access -- only for a run saved via the stored-graph flow: a run_simulation result is ephemeral and has no usable run_id. Requires authentication (api_key argument or an Authorization: Bearer token) to CREATE the link; the resulting share_url itself needs no credential to view. Example: {"run_id":"run_8f3c2a"}

Converts a human-style estimate (a min/max range at a stated confidence, or a most-likely value) into the distribution_params a root node needs. Use this when you have a rough verbal estimate like 'between 80 and 120, 90% confident' and need engine-ready parameters rather than guessing them yourself. Free; no credits debited. Example: {"distribution_type":"normal","min_estimate":80,"max_estimate":120,"percentile_range":0.9}

Fetches the status and, once available, the summarised result for a previously-submitted run by its run_id. Use this when you want to re-check or re-fetch a run you already submitted (e.g. via run_simulation) without resubmitting the graph -- run_simulation itself already blocks until done and returns the full result directly, so this is not a poll-until-ready step for it. Example: {"run_id":"run_8f3c2a"}

Checks a graph for structural problems (cycles, dangling edges, unknown distributions, missing refs) before you run it, returning a list of issues by rule and severity. Use this when you built or edited a graph by hand and want to catch mistakes before spending a run on it. Free; no credits debited. Example: {"graph":{"root_nodes":[{"id":"root","distribution_type":"normal","distribution_params":{"mean":100,"std":15}}],"calc_nodes":[{"id":"out","formula":"{e1}"}],"edges":[{"id":"e1","source":"root","target":"out"}],"run_params":{"trials":1000,"time_periods":12}}}