calibrating-thresholds-and-baselines

Plugin calibrating-thresholds-and-baselines from marketplace dev-skills in wdm0006/python-skills. Commands read from the repo's manifest — 5 days ago.

Skills (41)

• building-accessible-interfaces

  Makes web and app UIs usable by keyboard, screen-reader, low-vision and motion-sensitive users — semantic HTML before ARIA, labelled controls, visible focus, WCAG AA contrast measured rather than eyeballed, touch targets, reduced motion, and automated axe checks plus a manual keyboard pass in CI or

• wiring-application-config

  Load, merge, and validate layered application configuration (defaults plus a user YAML/TOML/JSON file or a stored settings object) so a mis-wired or misspelled key fails loudly instead of silently reverting to the default — sections the code reads that exist nowhere, sections that exist but nothing

• shipping-build-artifacts

  Make the build step a real gate on what you actually distribute — build scripts that warn and exit 0 on a missing input, size checks with only an upper bound, hand-maintained file lists that drift from the entrypoints they must cover, committed bundles that go stale when only the source changes, GNU

• permissioning-ci-workflows

  Give a CI job exactly the credentials it needs and know when it has none — declaring `permissions:` explicitly because the default GITHUB_TOKEN scope is a repo setting, reading the 403's x-accepted-github-permissions header instead of guessing the missing scope, one API call needing two scopes, a fo

• concurrent-branches

  Resolve conflicts and merges when several branches are open against one repo at the same time — the hotspot files every change must touch (registry manifests, a single version field, shared tool config, one aggregated test module, tracked build output), union-vs-recompute-vs-rebuild as three differe

• shipping-across-surfaces

  Land a change everywhere the same fact is stated — enumerating the full surface inventory (landing copy, docs, machine-readable summaries, changelog badges repeated across every page, sitemap, README, descriptions embedded in code, and untyped frontend consumers of typed responses), generating a sur

• writing-defect-reports

  Establish a finding before you publish it, and correct it after — headlines that overstate what actually reproduces at the layer a user sees, reporting code that no entry point can reach or that is already dead, filing a caveat the project's own records already answered, re-verifying your prior note

• reporting-derived-metrics

  Compute statistics, scores, and flags from samples that may be too small to support them — undefined dispersion returned as 0.0 and tripping a minimum threshold, sentinel choice (None vs 0 vs NaN), threshold blocks gated on "was this measured", reports that narrate findings from absent data, nullabi

• guarding-destructive-operations

  Add and review preconditions on operations that delete, overwrite, rewrite history, or resolve a caller-supplied name to a filesystem path — refusing instead of warning, placing the guard ahead of the first mutation, structural classification rather than string-prefix matching, name validation plus

• keeping-git-repos-clean

  Prevents, detects, and remediates files that should never be committed — secrets (.env, API tokens, hardcoded credentials) and dev artifacts (build output, scratch databases, editor/OS files). Covers .gitignore (and why it does not untrack), git rm --cached, auditing tracked files, history scrubbing

• running-github-actions-efficiently

  Cut GitHub Actions minutes and wall-clock time without losing coverage — the OS billing multiplier (macOS 10x / Windows 2x / Linux 1x), trigger hygiene that stops push+pull_request double-firing, concurrency that cancels superseded runs, dependency caching keyed on lockfiles, matrix discipline, and

• designing-interaction-states

  Designs the states screens actually spend their time in — first-run and empty states, loading and skeletons, inline validation and error messages, success feedback, destructive confirmations, and the microcopy for each — so a product feels finished instead of only working on the happy path. Use when

• designing-marketing-pages

  Designs landing, pricing, comparison and product pages that explain the product fast and convert honestly — one-sentence value proposition above the fold, a single primary call to action, real product screenshots instead of stock art, proof, a clear pricing table, fast responsive pages, and no dark

• rendering-untrusted-content

  Renders stored, authored, or imported content into HTML without shipping XSS — auditing every autoescape bypass (|safe, Markup, innerHTML), sanitizing Markdown output with an allowlist, escaping on both the server and the DOM, and writing sanitization tests that assert on the right copy of the strin

• reproducing-ci-locally

  Run the CI gate on your machine so it agrees with the runner — deriving the exact command, paths, markers, and env from the workflow file instead of the Makefile, unblocking gate steps that short-circuit and hide the next failure, pinning the linter version CI resolves, building the interpreter/tool

• running-resumable-sync-jobs

  Design and review long-running batch or sync jobs that process many items against a remote API and persist checkpoint state — exit codes that report partial failure, checkpoints that are safe to resume and written atomically, per-item tolerance vs. fatal abort, telling "zero" apart from "couldn't fe

• normalizing-text-for-measurement

  Strip, parse, and segment a document before something else measures it — normalizers that fuse two blocks into one word because a close-token emits no separator, the two metric classes failing on different residue — character-based ones (reading time, token budgets, size limits) inflated by leftover

• calibrating-thresholds-and-baselines

  Check that a score-threshold-flag pipeline actually separates anything before you trust or tune it — reference constants that are hand-authored but formatted as measurements, a computed feature whose units do not match the constant it is compared against, per-class fire rates that expose a flag firi

• designing-interfaces

  Makes a product's UI look deliberate and current instead of dated or improvised — auditing a screen against hierarchy, type scale, spacing scale, color tokens, layout and component consistency; introducing design tokens before restyling anything; and verifying every change visually with before/after

• verifying-external-behavior

  Confirms what a third-party library, remote API, build backend, or scraped document actually does before writing code that depends on it — throwaway probes that run in seconds, permissive clients that forward wrong arguments instead of rejecting them, per-endpoint docs that don't generalize, respons

• building-go-projects

  Sets up and maintains Go projects with a CI gate that actually gates — module-path correctness, golangci-lint config that matches the installed major version, deterministic gofmt, a pinned toolchain, and meaningful test/lint jobs. Use when creating a Go module, wiring GitHub Actions for Go, debuggin

• building-browser-extensions

  Builds and tests Manifest V3 browser extensions — service-worker message channels that survive teardown, chrome.storage read-modify-write safety, settings validation in the popup, and a Jest chrome mock that can actually fail. Use when writing or reviewing a background service worker, a popup that r

• designing-python-apis

  Designs intuitive Python library APIs following principles of simplicity, consistency, and discoverability. Handles public re-exports, API evolution, deprecation, breaking changes, and error handling. Use when designing or reviewing a library API, exposing a symbol from a package __init__, or managi

• building-python-clis

  Builds command-line interfaces for Python libraries using Click or Typer. Includes command groups, argument handling, progress bars, shell completion, and CLI testing with CliRunner. Use when adding CLI functionality to a library or building standalone command-line tools.

• improving-python-code-quality

  Improves Python library code quality through ruff linting, mypy type checking, Pythonic idioms, and refactoring. Use when reviewing code for quality issues, adding type hints, configuring static analysis tools, or refactoring Python library code.

• building-python-communities

  Builds and manages open source Python library communities including CONTRIBUTING.md, CODE_OF_CONDUCT.md, issue/PR templates, contributor recognition, and GitHub automation. Use when setting up community infrastructure, improving contributor experience, or managing project governance.

• documenting-python-libraries

  Creates comprehensive Python library documentation including Google-style docstrings, Sphinx setup, API references, tutorials, and ReadTheDocs configuration. Use when writing docstrings, setting up Sphinx documentation, or creating user guides for Python libraries.

• deferring-heavy-dependencies

  Keep expensive resources — ML models, spellcheck dictionaries, embedded databases, large third-party imports — off code paths that never use them. Covers constructor work paid by every caller, one-size factories that load the heaviest member for the cheapest request, load-and-unload-per-call masquer

• reviewing-python-libraries

  Comprehensively reviews Python libraries for quality across project structure, packaging, code quality, testing, security, documentation, API design, and CI/CD. Provides actionable feedback and improvement recommendations. Use when evaluating library health, preparing for major releases, or auditing

• building-llm-backed-features

  Builds application features on top of an LLM API in Python — prompt surfaces that drift apart, structured outputs, context budgeting, model/config wiring, filtered evaluator sets, keeping live-model calls out of default CI, evaluating stochastic output, and presenting model output truthfully. Use wh

• building-python-mcp-servers

  Builds robust Python MCP (Model Context Protocol) servers with FastMCP — tool design, error contracts, event-loop-safe blocking work, subprocess/CLI wrapping, single-file vs packaged distribution, global-state-free testing, and prompt-injection awareness. Use when writing an MCP server, exposing a t

• packaging-python-libraries

  Packages and distributes Python libraries using modern pyproject.toml, build backends (setuptools, hatchling), PyPI publishing with trusted publishing, and wheel building. Use when packaging libraries for distribution, publishing to PyPI, or troubleshooting packaging issues.

• optimizing-python-performance

  Optimizes Python library performance through profiling (cProfile, PyInstrument), memory analysis (memray, tracemalloc), benchmarking (pytest-benchmark), and optimization strategies. Use when analyzing performance bottlenecks, finding memory leaks, or setting up performance regression testing.

• setting-up-python-libraries

  Sets up professional Python library projects with modern tooling (pyproject.toml, uv, ruff, pytest, pre-commit, GitHub Actions). Use when creating new Python libraries, modernizing existing projects to pyproject.toml, configuring linting/testing/CI, or setting up Makefiles and pre-commit hooks.

• managing-python-releases

  Manages Python library releases including semantic versioning, changelog maintenance (Keep a Changelog format), release automation with GitHub Actions, and deprecation workflows. Use when planning releases, writing changelogs, automating release pipelines, or communicating breaking changes.

• auditing-python-security

  Audits Python libraries for security vulnerabilities using Bandit, pip-audit, Semgrep, and detect-secrets. Identifies SQL injection, command injection, hardcoded credentials, secrets exposed through tracebacks, weak cryptography, and insecure deserialization. Use when reviewing library security, set

• testing-python-libraries

  Designs and implements pytest test suites for Python libraries with fixtures, parametrization, mocking, Hypothesis property-based testing, and CI configuration. Use when creating tests, improving coverage, setting up testing infrastructure, or implementing property-based testing.

• building-python-web-apps

  Provides an opinionated reference architecture for production Python web apps — FastAPI + async SQLAlchemy + Postgres, pydantic-settings config, Stripe billing, server-rendered Jinja or a decoupled SPA, deployed as a single Docker image on a managed platform via Terraform. Use when starting a new Sa

• building-rust-crates

  Sets up, tests, and publishes Rust crates — Cargo project layout, a fmt/clippy/test CI gate that actually gates, MSRV pinning, feature-flag hygiene, and crates.io publishing with cargo-release. Use when creating a Rust crate, wiring GitHub Actions for Rust, debugging a clippy or MSRV CI failure, or

• building-swift-apps

  Builds, tests, and ships native Swift/SwiftUI apps for Apple platforms (macOS/iOS) reliably in CI and locally — unsigned CI builds, the hand-maintained pbxproj, SwiftPM-module vs app-target test boundaries, SourceKit false positives, gitignored base xcconfig, Keychain vs UserDefaults for secrets (OA

• shipping-swift-apps

  Ships native Swift/SwiftUI apps to TestFlight and the App Store with fastlane and xcodebuild — one App Store Connect API key for both, fastlane lanes scoped to metadata/pricing/subscriptions, headless `xcodebuild archive` + `-exportArchive destination=upload`, build numbers read from App Store Conne