Coding & Dev Tools

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Use for writing, reviewing, debugging, or testing Python terminal presentation built with Rich, including Console streams, Text and markup safety, tables, trees, panels, progress, status, Live displays, render protocols, and deterministic output capture. Do not use for CLI argument parsing, structured logging design, browser UI, or machine-readable protocol output that must remain plain.

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Use for writing, reviewing, debugging, testing, or optimizing Python SymPy symbolic mathematics. Trigger on Symbol, assumptions, Expr, Eq, solve/solveset, simplify, factor, expand, calculus, matrices, exact arithmetic, lambdify, code generation, or symbolic-to-numeric conversion. Do not use for NumPy-only arrays, mpmath-only arbitrary-precision numerics, CVXPY optimization models, or parsing untrusted mathematical text.

Use for writing, reviewing, debugging, or testing Python command-line interfaces built with Typer, including typed arguments and options, command groups, callbacks, contexts, exit behavior, help, and CliRunner tests. Do not use merely for terminal styling, arbitrary business logic, a Click-only CLI, shell scripts, or invoking an existing command.

Use for writing, reviewing, debugging, testing, or validating Python mpmath arbitrary-precision numerical code. Trigger on mpf, mpc, mp.dps, workdps, interval arithmetic, high-precision quadrature, root finding, special functions, matrices, inverse transforms, or precision/convergence failures. Do not use for ordinary NumPy vectorization, SymPy symbolic manipulation, decimal currency arithmetic, or machine-float code with no precision requirement.

Write, review, debug, test, or optimize pandas Series, DataFrame, Index, groupby, merge, reshape, dtype, missing-value, and time-series code.

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Design, review, debug, and test Python static types including Protocol, generics, variance, overloads, TypedDict, ParamSpec, TypeGuard, and narrowing.

Write, review, debug, or test Python Xarray workflows for labeled N-dimensional DataArray and Dataset operations, including coordinates, alignment, indexing, groupby, resample, rolling, weighted reduction, Dask-backed execution, and NetCDF/Zarr I/O.

Write, review, debug, and test Python FastAPI applications with path operations, dependencies, Pydantic models, lifespan, middleware, background tasks, exception handling, and ASGI tests.

Create, review, debug, test, or reproduce Python Jupyter notebooks by inspecting format, executing cells top-to-bottom in a clean kernel, and verifying outputs.

Write, review, debug, or test Python code that parses, inspects, transforms, builds, qualifies, optimizes, formats, or transpiles SQL with SQLGlot.

Produces NetworkX code with explicit graph kind, node identity, edge multiplicity, direction, attribute schema, weight semantics, and algorithm preconditions, including testing.

Write, review, debug, test, or optimize Python code using the rustworkx graph library, with explicit handling of graph kind, index lifecycle, payload semantics, and algorithm result mapping.

Use for writing, reviewing, debugging, or testing Python Streamlit apps, especially rerun behavior, widget identity and callbacks, session_state, cache_data/cache_resource, forms, fragments, containers, multipage navigation, uploads/downloads, and Streamlit-hosted chart/table interaction. Do not use for standalone Plotly/Altair figure design, generic backend services, Dash apps, or deployment configuration without app code.

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Write, review, debug, or interpret Python statistical models using statsmodels, including formulas, regression, GLM, time series, robust covariance, diagnostics, prediction intervals, and inference.

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Use for designing or reviewing resilient asynchronous HTTP call paths that combine HTTPX, Tenacity, and asyncio: client lifetime, time budgets, retry eligibility, backoff, concurrency, cancellation, and idempotency. Do not use for generic HTTPX, retry, or asyncio questions that do not cross these boundaries.

Creates, reviews, debugs, and modernizes Python project structure with deterministic tooling including pyproject.toml, uv, Ruff, Pyright, and pytest.

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Use when FastAPI request, dependency, response, or OpenAPI behavior interacts with Pydantic v2 models, validation, aliases, serialization, generics, or error contracts. Do not use for standalone FastAPI routing or standalone Pydantic models with no ASGI boundary.

Use when symbolic mathematics must cross into NumPy vector evaluation or SciPy numerical algorithms: lambdify contracts, domains, dtypes, parameters, residuals, tolerances, and symbolic-versus-numeric verification. Do not use for work confined entirely to one of those libraries.

Sync main, rebase active worktrees, and clean up merged branches safely.

Run interactive design reasoning and create .pen files using Pencil.

Refine a ticket interactively until it is ready for planning.

> **Client dispatch**: In Codex, read `codex-runtime` and `maintain/codex.md`, execute that native procedure, and do not continue into the Claude procedure below.

Analyze a codebase with specialized agents and propose refactoring tickets.

Configure cenci's neutral project core and generate Claude/Codex adapters.

Address PR review comments by fetching, evaluating, fixing, replying, pushing, and re-requesting review.

Resolve a paused PR supervisor decision with explicit human input.

Decide which pull-request review comments are actionable. Use when addressing review feedback, monitoring a PR, or filtering already-handled comments.

Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")

Expert patterns for Clerk auth implementation, middleware, organizations, webhooks, and user sync Use when: adding authentication, clerk auth, user authentication, sign in, sign up.

Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.