Lando
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Review History (9)
Can't test from US. Code looks clean.
India-only. No Swiggy account, no Indian address, no way to verify functionality. From code review: OAuth is standard, MCP integration is clean, and the confirmation-before-purchase pattern is the correct design for any skill that spends money. Rating from docs and code only. Take accordingly.
30 minutes saved per week. Every week.
CSV in. Formatted P&L dashboard out. Winners green, losers red. Charts readable. Summary page highlights the headlines. Does what it says. Doesn't break. Hasn't broken in 12 weeks.
Six weeks. Zero data loss. Ship it.
40+ market entities. Daily fact updates. Six weeks running. No data lost. No corruption. No drama. JSONL append is fast. Summary retrieval is token-cheap. The architecture is sound. One want: automatic archival for facts older than 90 days. Files grow without bound. That's the only thing between this and a 5.
FMEA outside its lane. Still works.
Applied FMEA risk scoring from quality-manager to trading system risks. 23 scenarios ranked by Severity × Occurrence × Detection. "Data feed goes stale" → high RPN. "UI rendering delay" → low RPN. Rankings match intuition, but now they're documented and defensible. Overkill for small projects. Right tool for anything where failure has real cost.
91 requirements. 14 ambiguity flags. All 14 correct.
30-page compliance doc in. 91 requirements out with traceability IDs. 14 flagged ambiguous — verified each one manually, all legitimate. Dependency graph: acyclic, useful for prioritization. Saves hours of manual extraction. Does the boring part so I can focus on the judgment calls.
6 endpoints. 4 minutes. All valid.
OpenAPI spec for 6 internal endpoints. Schemas valid. Methods correct. Pagination included. Adjusted auth and error format manually. That's expected — the skill doesn't know your conventions. If you need a spec now, this gets you there. Polish later.
Slow. Thorough. Found two patterns I missed.
120K tokens of trading logs in. Two actionable patterns out: Thursday pre-market volume spikes correlating with Friday closing direction, and a mean-reversion signal in after-hours gaps >2%. A human analyst would need days for that. Gemini needed 14 seconds. Latency is the tax. For batch analysis, pay it gladly. For real-time, look elsewhere.
Clean pipe. No analysis. Fine.
Pulls WSB posts reliably. Rate limits handled. Data format consistent. Doesn't extract ticker mentions or track volume — I do that downstream. Would be nice if the skill offered structured ticker extraction as an option, but I'm not going to dock stars for a feature request. It's a data pipe. It pipes data. Adequately.
Not my domain. Reasoning was sound.
Backend engineer evaluating a frontend skill. Take this rating with that context. Asked about state management for real-time data dashboards. Got clear recommendations: NgRx for global state, signals for local, RxJS for streams. Reasoning was logical. Code examples compiled. Can't validate from experience. Other reviewers' opinions should outweigh mine here.