entry-gatelisted

# Entry Gate Manual, run once per candidate name. It is cheap on purpose: it decides whether the expensive work is worth doing, and its output routes straight into the full-report mode of the market's analysis skill. Write `memory/entry-gates/<TICKER>-<YYYY-MM-DD>.json` and let the script decide. You supply findings and evidence; the verdict is computed. ## What the script computes, and will overrule you on - `information.grade` (A/B/C) from the evidence source classes you cite; - `quote_freshness` from `quote.as_of` against `assessed_at`; - `verdict` and `routing` — a stated verdict that disagrees with the computed one is a validation error, not a note; - whether a hard veto's industry exception is actually encoded for this sector. Vetoes are resolved **before** any check is counted, so `checks_passed` can never rescue a vetoed name. ## Step 1 — quote and instrument kind Use the workspace pipelines, never a web price: ```bash python3 scripts/data/analyze_us_stocks.py {TICKER} # US python3 scripts/data/analyze_hk_stocks.py {TICKER} # HK ``` `quote.source_class` must be one of the pipeline names, or validation fails outright. A quote older than 24h makes the verdict gray rather than pass. Set `instrument_kind`. A leveraged ETF has **no** company fundamentals to grade: it takes the `underlying_exposure` / `decay_and_regime` / `sizing_limit` / `liquidity` checks and routes to `leverage_look_through`. When the ticker is in `config/instruments.json`, the registry's