Curated code proof

Code

The useful signal is not raw repo count. It is whether the code shows product judgment, systems constraints, and shipped interfaces. This page leads with curated proof across GitHub and GitLab, then includes a live GitHub index with cached fallback data.

Curated repos
5

Highest-signal code surfaces first

Source hosts
GitHub + GitLab

No more GitHub-only blind spot

Primary stack
TS / Python / Rust

Product UI, AI tooling, trading systems

Daniel Silva Perez

@daniel-silva-perez
47 repos
3 followers
Miami, FL
https://danielsilvaperez.com

Start here

Repositories selected for recruiter and engineering-review signal.

GitHub

Daniel Search

repo ↗

This portfolio. A personal search experience: Spotlight meets Google meets project gallery.

Why this matters

Shows product taste, search UX, structured content modeling, static routes, source-grounded assistant behavior, and recruiter conversion thinking in one shipped surface.

Next.jsTypeScriptSearch UXPortfolioTesting
Search-first navigation
Grounded /ask endpoint
Static RSS/sitemap/LLM routes
GitLab

orcha

repo ↗

A multi-agent orchestration layer that distributes work across Codex, Claude, Gemini, and Kimi so parallel model effort becomes a usable execution workflow.

Why this matters

Proves Daniel is building around real agent workflow problems: dispatch, shared context, synthesis, and human-visible execution boundaries.

AI agentsTypeScriptOrchestrationLLM systems
Parallel model dispatch
Cross-model synthesis
Operator-oriented workflow
GitLab

voltage-kalshi

repo ↗

A live Kalshi volatility stack built around streaming BTC data, feature engineering, and model-driven execution with real capital on the line.

Why this matters

Demonstrates systems work under real constraints: live WebSocket data, model signals, execution gates, and capital-aware operator controls.

PythonLightGBMWebSocketsKalshiTrading infra
Live market ingestion
Feature pipeline
Execution/risk boundary
GitLab

air-runtime

repo ↗

An inference runtime for constrained hardware that combines speculative decoding, smart routing, and KV-cache compression to make smaller devices more useful.

Why this matters

Shows AI infrastructure thinking below the UI layer: runtime routing, memory pressure, latency, speculative decoding, and KV-cache tradeoffs.

Edge AIInferenceRuntime systemsPython
Speculative decoding framing
KV-cache compression
Routing under constraints
GitLab

council-cli

repo ↗

A multi-agent coding roundtable that turns model disagreement into a visible review process for architecture, implementation planning, and technical critique.

Why this matters

Turns model disagreement into a deliberate engineering review surface instead of hiding multiple opinions behind one fluent response.

AI agentsCode reviewCLIDecision systems
Specialist roles
Decision records
Repeatable critique loop

Supporting code surfaces

Smaller tools and code-adjacent work from the structured portfolio index.

Automation Scripts & CLIs

Collection of small Python and shell tools: file pipelines, scrapers, and personal infrastructure.

PythonBashCLI

Want the fastest review path?

Start with Daniel Search for product polish, orcha/council-cli for AI systems, voltage-kalshi for live systems constraints, and air-runtime for inference infrastructure thinking.