Public JS/TS referenceQuality gate: passWording: Kimi K2.6 · English
Play Next.js SaaS starter
A medium SaaS codebase with identity, email/OTP, content, database, and Stripe boundaries—useful for showing how the report separates several product journeys.
Measured analysis work, not a sample-based AI opinion
These are workload and retained-evidence counts, not defect counts. FlowPreflight inventories source first, then connects the observations into routes, functions, effects, controls, and journeys.
Files inventoried
157
86 supported files parsed
Source facts connected
3,031
Imports, declarations, calls, routes, data operations, and other source observations
Functions analyzed
128
Static behavior analysis; not proof of runtime execution
Dependency candidates
620
Checked for advisory evidence; production reachability remains separate
Artifacts retained
94
Reports, diagrams, evidence, validation, and traceability records
WHAT WE DID
From repository to validated report
01
Pinned the public repository and scanned its application, route, schema, and integration source.
02
Resolved authentication, registration, password-reset, content, database, and payment-related paths where static evidence closed.
03
Separated detected controls from review boundaries and dependency reachability questions.
04
Reconciled four customer-facing journeys with thirteen independent follow-up checks and their Prompt Pack tasks.
WHAT THE RESULT ESTABLISHED
A useful review without invented certainty
Recovered account registration, account/session, and payment journeys while retaining blog and MDX evidence outside the primary customer-flow count.
Kept Stripe and authentication follow-up scoped to their actual routes and evidence.
Kept one open analysis boundary explicit while preserving the ordered account and recovery paths.
PUBLICATION CHECKS
Deterministic analysis first. Controlled AI wording second.
FlowPreflight selected the evidence, journeys, decisions, priorities, and tasks without an LLM. Kimi K2.6 received only bounded report sections plus the minimum canonical context needed to improve the English wording. It did not receive the repository, analysis databases, full dossier, or full canonical report, and it could not add or remove a finding.
Schema and reference validation
Canonical counts, IDs, and claim levels preserved
English-only output validation
Public-output and secret-safety checks
Customer Report and Prompt Pack quality gates passed
Report publishedNo confirmed release blocker was established from the available evidence. Follow-up work remains attached to the exact evidence boundaries.
Artifact quality checks passed
BEFORE YOUR NEXT DEPLOY
Get the same evidence trail for your codebase.
See the flows AI generated, the controls source evidence supports, and the exact checks that still need a human or runtime signal.