What Flows just did
Based on your request to build Memory Recall: Ranking and Relevance, Flows created 4 implementation stages and 12 checks.
You asked for: Build hybrid recall: BM25-style lexical search plus embedding similarity, fused rankings, recency/confidence boosts, and explainable results.. Flows generated 4 stages because the application requires Lexical search (exact and keyword matching) over memory entries; Semantic search via embeddings over the same entries; Rank fusion (reciprocal rank fusion or equivalent) combining both. Each stage tells your AI builder what to do, tests whether it actually worked, and gives a repair instruction when it fails. These checks are designed to catch: Vector-only recall that cannot find an exact error string; Lexical-only recall that misses every paraphrase; Unbounded result lists stuffing recall noise into context.
Example failure
The form reported success, but no database record was created.
What Flows does
Flows detects the failure, generates a repair instruction, reruns the test, and stores the passing evidence.
Stages — Plan → Build → Test → Fix → Prove → Ship
4 stages · 12 checks · progressive disclosure — open a stage for details
Copy to external builder
Copies a prompt for Claude/Cursor/etc. Records prompt_copied only — not execution, commits, or checks.
Execute through Oort
Requires Sign in with Oort + a provider connection (BYOK). Keys stay on Oort. A model name in the dropdown is not the same as a live connection.
Next
Check off: Identifier-aware tokenization
Add a proof note on each check — a checkbox alone is weak proof.
Probes & advanced tools are under “More verification tools”. Experience level: Settings.
Project (saved with proof)
Project binding: Unbound — complete project binding before trusting this run · missing repositoryUrl, repositoryStartCommit, environment, stack
More verification tools (probes, timeline, adapters)Show
App persistence (create → read → assert token)
Body template: {"probe":"{{token}}","title":"flows-probe-{{token}}"}. Needs CORS-readable public create/list endpoints (or inconclusive). Badge only when create→read→refresh finds the token (detects false success).
Two-account authorization (User B cannot see/change User A)
Authorization evidence source: Cross-account ownership test (trust level 5/6). These are not equivalent. Unauthenticated probe alone is weaker (source: unauthenticated API probe). Tokens stay in this browser session only — not uploaded to Flows servers.
Generated edge-case tests (review / approve)
- api_probe Submitting the form empty is rejected with a clear error
- api_probe Each required field can be omitted and fails validation
- api_probe Malformed email is rejected
- api_probe Logged-out users cannot open protected pages
- api_probe Protected API rejects requests without credentials
Generated from this route’s signals — you approve; you do not invent security tests.
Content probe (GET body contains text)
In-product content probe reads response text when CORS allows — not full DOM/click automation. Playwright script is optional and external.
Proof strength
thin · 0/100
Heuristic from notes + probes + gates — not a production certification.
Verification adapters
- ● Deploy URL probe · idle
- ● API path probe · idle
- ● Authz probe (unauth → 401/403) · idle
- ● Browser persistence · idle
- ● App persistence (create→read) · idle
- ● Content / body text probe · idle
- ○ In-product Playwright DOM · not embedded (download external script)
Filled circles = available here. Empty = not shipped. Probes are not a production audit. Adapter docs
Step 1 of 4
Not startedBuild the lexical layer
Exact matches are the floor of trustworthy recall.
Flows keeps plan, checks, failures, and next steps connected
Your AI tool writes or changes the code
Repository grounds the plan only after inspect
Checks always carry a validation tier
How this plan was created
Plan from project details
Flows creates steps using the goal, requirements, stack, platform, and details you provide.
- Project description
- Selected template / route
- User-entered stack
- Constraints and notes
- Memory Recall: Ranking and Relevance
No repository inspection implied. Connect and inspect a codebase to ground steps in real files.
Codebase access
Checking GitHub…
Or paste a repository URL manually
Use these instructions in Claude, ChatGPT, Cursor, Emergent, or another builder.
Implement lexical search over memory entries. Requirements: tokenize entries and queries (lowercase, split identifiers on common separators so auth_handler matches 'auth handler'); score with BM25 (use SQLite FTS5 or a small library - do not hand-roll unless trivial); support quoted exact-phrase matching for error strings; return top-K with matched terms highlighted per result. Test with queries that MUST work lexically: an exact file name, an exact error message substring, and a specific command flag - all should hit their entries at rank 1.
Project context
Copies the project goal, technical details, current step, previous progress, and checks so your AI tool understands what it is working on.
Expected after this step
BM25 lexical search passing the exact-match tests.
Should not happen
- ✕Vector-only recall that cannot find an exact error string
- ✕Lexical-only recall that misses every paraphrase
- ✕Unbounded result lists stuffing recall noise into context
- ✕Opaque retrieval nobody can debug when the wrong memory surfaces
Verify gate — prove this step works before continuing
Do not move on until every check is true. Add proof notes — a checked box alone is weak proof. Checks are manual by default; deploy/API probes live under “More verification tools” and do not auto-check boxes.
Do not continue if…
- !Vector-only recall that cannot find an exact error string
- !Lexical-only recall that misses every paraphrase
- !Unbounded result lists stuffing recall noise into context
- !Opaque retrieval nobody can debug when the wrong memory surfaces
Repair path — if this step fails
Use the Repair Prompt when a verify gate fails. Loop: Detected → Diagnosed → Repair issued → Changed → Retested → Resolved
Show repair prompt textShow
Exact file names miss. Check tokenization of paths and identifiers - index both the raw token (auth_handler.py) and its split parts (auth, handler, py).
Your notes for this step
Definition of Done
Final route-level requirements. Manual checks — separate from per-step verify gates. Completing step gates does not auto-check these. Route completion is not a production-ready claim.