--- name: predict version: "1.0" description: > Pre-implementation multi-persona adversarial analysis for gflow-cli proposals. Five expert personas independently evaluate a proposed change before a single line of code is written, then converge on a GO / CAUTION / STOP verdict. Invoke before any high-stakes decision: new transport, auth change, selector redesign, schema migration, API surface change, or backlog item requiring an investigation gate. --- # `predict` — Pre-Implementation Multi-Persona Analysis Structured pre-implementation review. Five expert personas assess the proposal **independently**, then debate, then converge on a verdict with a confidence score. Surfacing architectural, security, performance, and UX flaws before the first commit is the cheapest place to catch them. --- ## When to invoke Use before implementing any of: - A new transport strategy (`sapisidhash`, `cdp_attach`, `official_veo`) - Auth flow changes (new strategy, G12 bypass technique, cookie extraction) - Selector cascade redesigns affecting `ONBOARDING_SELECTORS`, `NEW_PROJECT_SELECTORS`, `FRAME_SLOTS_STRUCT` - Schema migrations in `gflow_cli/data/` - New CLI surface or exit-code changes - Any backlog item with an "investigation gate" in PLAN.md before coding Skip for: trivial bug fixes (< 10 lines, isolated, no boundary cross), already-approved PLAN.md tasks entering EXECUTE, pure doc changes. --- ## Invocation ``` /gflow:predict ``` `` is a short description of what you intend to build or change — one paragraph is enough. Examples: - "Wire SAPISIDHASH auth header into `_post_json` for all `aisandbox-pa` routes (Issue #15)" - "Add CDP-attach transport as opt-in `--transport cdp_attach` alongside `ui_automation`" - "Redesign `gflow video batch` to use a local manifest ledger for skip-already-done" - "Add `AuthBrowserBlockedError` to `internal_chromium.py` when Google rejects bundled Chromium" --- ## Protocol ### Phase 1 — Persona briefings (parallel) Dispatch five personas simultaneously. Each reads `AGENTS.md`, `PLAN.md`, `KNOWN_ISSUES.md`, and the relevant source files for the proposal. Each assesses **independently** — no persona sees another's output during Phase 1. #### Persona 1 — Architect *Scope: hexagonal target, modular-monolith current shape, dependency direction, module boundary rules.* Asks: - Does this proposal respect the dependency rule (`interfaces → application → domain ← infrastructure`)? - Which module does this live in? Does it fit cleanly or does it need a new module, and if so, is that justified? - Will this make the eventual DDD graduation harder or easier? - Are there hidden coupling risks (e.g., a transport leaking into `cli.py`, a domain model importing from `infrastructure`)? - Does the proposed shape match the existing pattern (Protocol-based ports, frozen dataclasses for value objects, `structlog` for all logging)? Output: structured analysis, confidence `0–10`, architectural risks. #### Persona 2 — Security / reCAPTCHA *Scope: Google's anti-bot stack, SAPISIDHASH, G12 block, WAF scoring, profile isolation, secret storage.* Asks: - Does this touch auth headers, cookie extraction, or token minting? If yes, what's the trust boundary? - Could this trigger WAF score inflation on a per-profile basis? - Does the Chrome profile isolation guarantee (`SecurityError` if profile_dir outside `GFLOW_CLI_HOME`) remain intact? - Are any auth secrets (SAPISID, bearer tokens, reCAPTCHA tokens) at risk of leaking to logs? (`show_locals=False` is mandatory on exception renderers.) - Could this bypass the G12 stealth flag mechanism or reintroduce `navigator.webdriver=true`? - What's the attack surface against a third party who controls the Flow UI (XSS / selector injection)? Output: structured analysis, confidence `0–10`, security risks with severity. #### Persona 3 — Performance / Playwright *Scope: Page pool, `asyncio.gather`, reCAPTCHA mint latency, headless detection, BrowserContext lifecycle.* Asks: - Does this add latency to the hot path (per-generation or per-poll)? - Does it interact with the Page pool (`_checkout_page` / `_checkin_page`)? Is there a `QueueFull` risk? - Does it require additional `page.evaluate` calls? What's the latency budget vs the 200 ms/page threshold? - Does it affect `GFLOW_CLI_CONCURRENCY`? Could it reduce or increase the safe ceiling? - Could running this in a headless context trigger reCAPTCHA detection or WAF scoring? - Does it add any persistent state that's not cleaned up when `FlowApiClient.__aexit__` runs? Output: structured analysis, confidence `0–10`, performance bottlenecks. #### Persona 4 — CLI **and MCP** UX / Cross-platform *Scope: exit codes (RFC 9457), `structlog` events, Windows/macOS/Linux path handling, `--help` text, error recovery UX, **and the MCP tool surface that mirrors all of it**.* Asks: - **Does this change land on the MCP surface too, and what breaks if it does not?** gflow ships every capability twice — as a CLI command and an MCP tool — and the automated parity gate is command-level only, so an unmirrored option or a docstring that still describes removed behaviour passes every check. Name the affected MCP tool, the payload keys on the queued `worker/codec.py` path, and any docstring claim that becomes false. If the proposal genuinely has no MCP surface, say so explicitly — silence here is what let #626 ship a CLI unlock with `mcp/tools.py` still telling agents the combination was rejected. - What exit code does failure produce? Is it in `EXIT_CODE_MAP`? Is it distinct from existing codes? - What `structlog` events does this introduce? Are `error_raised` / `error_unhandled` paths handled? - Are new env vars or flags introduced? Do they follow `GFLOW_CLI_*` convention and have a `.env.template` entry? - Does the UX degrade gracefully if the new feature fails (remediation hint in error message)? - On Windows: are path separators, `platformdirs` paths, and `PYTHONUTF8=1` requirements respected? - If this is a new subcommand or flag: is the `--help` text self-contained and accurate? - Does this change touch DOM selectors? If yes, are selectors strictly locale-invariant (Tier 1 structural/ARIA/icon/href anchors + Tier 2 multi-locale text cascades across EN, PT, ES, DE, FR, IT, JA, ZH, KO), rejecting single-language English-only selectors? Output: structured analysis, confidence `0–10`, UX friction points. #### Persona 5 — Devil's Advocate *Scope: YAGNI, simpler paths, interaction with KNOWN_ISSUES, backlog sequencing.* Asks: - Is there a simpler way to achieve the same user outcome (fewer files, less Playwright surface, existing code reuse)? - Does PLAN.md already have an ADR that contradicts or defers this work? - Is there a known issue in `KNOWN_ISSUES.md` that makes this approach risky or likely to fail? - If this fails in production (WAF score spike, reCAPTCHA regression, selector drift), what's the rollback story? - Is the timing right? Does something else need to land first (e.g., Issue #14 before Issue #15)? - What's the simplest experiment (smoke test, `scripts/` script, isolated spike) that could prove/disprove the core assumption before committing to a full implementation? Output: structured analysis, confidence `0–10`, alternative paths, blocking concerns. --- ### Phase 2 — Conflict resolution After all five personas return: 1. **Tally signals.** Identify any dimension where 2+ personas flag the same concern — those surface as high-confidence risks. 2. **Resolve conflicts.** If Architect says "fits cleanly" but Devil's Advocate says "ADR #13 defers this" — surface the conflict explicitly. Do NOT silently suppress one view. 3. **Score overall confidence** as the average of the five persona confidence scores, then apply modifiers: - Any STOP condition from any persona → overall **STOP** regardless of average. - Devil's Advocate identifies a simpler approach the others missed → downgrade confidence by 2. - All five personas agree on the approach → upgrade confidence by 1. --- ### Phase 3 — Verdict **GO** (confidence ≥ 7, no STOP conditions): all personas aligned or concerns are mitigated within the proposal. Safe to proceed to PLAN mode. **CAUTION** (confidence 4–6, or one unresolved STOP candidate): proceed but explicitly address the flagged concerns in the PLAN before EXECUTE. Surface the specific mitigations needed. **STOP** (confidence < 4, or any hard STOP): one or more of: - A security bypass that cannot be fixed within the proposal scope - A fundamental architectural incompatibility with the hexagonal target - A performance regression that violates the 200 ms/page threshold at N=16 - A PLAN.md ADR that explicitly defers this work - An existing KNOWN_ISSUES entry that makes the approach likely to fail - Devil's Advocate found a simpler approach that makes this one wasteful On STOP, output the specific blocking concern and the minimum change required to convert to CAUTION. --- ## Output format ``` # Predict: ## Verdict: **Confidence:** /10 ## Summary <2-3 sentences. What the five personas collectively found.> ## Persona findings ### Architect — (/10) ### Security / reCAPTCHA — (/10) ### Performance / Playwright — (/10) ### CLI UX / Cross-platform — (/10) ### Devil's Advocate — (/10) ## High-confidence risks (flagged by 2+ personas) 1. … ## Conflicts resolved - ## Required mitigations before EXECUTE (CAUTION only) 1. … ## Recommended next step ``` --- ## Integration & Pipeline Continuation (Next Step Handoff) - **After GO:** Proactively announce: **"Predict GO. Next step: Phase 3 BDD Scaffolding (`/gflow:scenario `) or Phase 4 Implementation Plan (`/gflow:plan `)."** - **After CAUTION:** Address required mitigations in the PLAN spec, then announce: **"Predict CAUTION. Next step: Address mitigations in Phase 4 Implementation Plan (`/gflow:plan `)."** - **After STOP:** Address blocking concern or file an investigation gate task before moving to Phase 4. --- ## Provenance Adapted from `vc-predict` in [vibecode-pro-max-kit](https://github.com/withkynam/vibecode-pro-max-kit) (assessment 2026-05-28). Personas re-scoped to gflow-cli surfaces: Google anti-bot stack, Playwright Page pool, RFC 9457 exit codes, hexagonal architecture target.