Results for “loop”

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

Close the gap between "you corrected me" and "it never happens again." Scan a work session for the corrections you made, the things you approved, and the patterns that held up, then propose specific edits to your skills, playbooks, and docs, high-confidence corrections separated from medium-confidence patterns, with nothing changed until you approve. Trigger on "learn from this session", "what should we update", "turn this into a rule", "close the loop", "improve the playbook", or the end of any session where you corrected or approved the work.

Runs a multi-phase verification pipeline including build, type-check, lint, tests, security scan, and diff review to ensure code quality before creating a PR.

Automates repeated rounds of Copilot code review on GitHub pull requests: triggers review, triages threads, dispatches parallel fix agents, commits, replies, and loops until convergence.

Reviews and repairs risky or unclear code with minimal validated changes, running a fixed-point loop until the diff is clean across two consecutive review cycles.

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Use when profiling, diagnosing, or improving Three.js or WebGL game performance without regressing gameplay—frame-time drops, CPU/GPU pressure, draw calls, texture/geometry budgets, animation loops, adaptive quality, mobile performance, and browser performance verification.

Building interactive experiences that engage, challenge, and delight playersUse when "game, gamedev, game development, phaser, unity, unreal, godot, gameplay, game loop, sprites, collision, physics, player, level, tilemap, games, gamedev, interactive, gameplay, physics, engines, performance, player-experience" mentioned.

PASS/FAIL eval rubrics and alignment loops for Sid Orchestra. Use when the user says sid evals, @sid-evals, grade this, eval gate, alignment score, or wants to stop AI slop with evaluation gates.

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

Generate an interactive bash wizard that walks a human through a manual procedure — third-party setup, a one-off migration, an A→B state transition — opening URLs, capturing values, confirming each step, and writing .env files and GitHub Actions secrets.

Close the PDCA loop on this session's diff. Headed playwright-cli, fix as you go. Use when "test my changes", "PDCA this". Pixel diffs → test-visual-regression. Story CRUD → test-qa. Monkey / guest vs logged-in → test-exploratory.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion to catch O(n²), N+1, and brute-force defaults.

Recognize when you're in a runaway loop and stop yourself. Use when the same tool call has repeated 3× with the same args, when the same error class has fired 3× in a turn, when you've been told the same correction twice, when "let me try one more variation" is the third small variation, or when a refinement loop is orbiting rather than converging. The right move on a trip is to switch from action to inquiry — read events.jsonl, list assumptions, look for contradictions, ask the human, file a chainlink — not to retry harder.

Turns a rough request into working software via a governed build loop: align first, plan, then iterate one task at a time with deterministic backpressure and holdout-scenario judging.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion, catching O(n^2), N+1, and brute-force defaults.

Use when a Claude Code session loops, drifts from scope, claims a fix that CI rejects, hits context, PATH, or permission walls, or fails in a way another retry will not solve and a root cause diagnosis is needed instead.

Prioritize features for an MVP or first release. Use when the team has too many ideas and needs must-have vs later vs never-for-v1 decisions tied to the core value loop, user pain, operational shortcuts, and launch feasibility.

Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker — edges as text in one file per ticket locally, or native blocking links on a real tracker.

BDD-driven test implementation: red-green loop mechanics, seams, mocking, and test quality under BDD Automation. Use when the user wants to write or improve tests during BDD implementation, needs guidance on test structure, or asks about test seams, mocking, or anti-patterns.

Executes Atomic Red Team tests mapped to MITRE ATT&CK techniques, performs coverage gap analysis, and runs detection validation loops to measure blue team visibility.

Human-in-the-loop web studio to tune AI-generated output by eye. Stand up a local interactive studio (sliders, pickers, drag handles) or an inline edit/highlight/comment annotation studio for prose & media, instead of guessing values or shipping a static comparison grid.

Human-in-the-loop web studio to tune AI-generated output by eye. Stand up a local interactive studio (sliders, pickers, drag handles) or an inline edit/highlight/comment annotation studio for prose & media, instead of guessing values or shipping a static comparison grid.

Autonomously runs iterative experiment loops to optimize code against a measurable metric. Use when the user wants to improve execution time, memory usage, test pass rate, or any numeric performance goal across repeated experiments — NOT for one-shot bug fixes or simple code review.

Human-in-the-loop web studio to tune AI-generated output by eye. Stand up a local interactive studio (sliders, pickers, drag handles) or an inline edit/highlight/comment annotation studio for prose & media, instead of guessing values or shipping a static comparison grid.

Automates PR review and CI auto-fix for GitHub and GitLab using the Composio CLI. Pulls diffs, fetches failing job logs, posts review comments, and loops fix commits until checks go green.

Generates a complete mobile test suite for Flutter, React Native, iOS, or Android apps, covering unit, widget, integration, snapshot, accessibility, and platform-specific tests, then runs them with a self-healing loop.

Resolves GitHub issues using isolated worktrees and test-driven development, then delegates PR creation to /github:create-pr so the quality gate and the /github:review-pr loop always run. This skill should be used when the user asks to "resolve an issue", "fix issue

Use when making a forward-looking claim with a checkable outcome (reply within 24h, error rate will drop, this skill will see more use) — record to state/predictions.jsonl with a review horizon so reflection can grade you later. Closes the in-the-moment double-loop.

Builds an interactive in-browser studio for tuning visual parameters (sliders, pickers, drag handles) or editing/annotating text and media, enabling real-time human-in-the-loop refinement instead of static comparisons or chat-based feedback.

Use when designing or auditing AI product human-in-the-loop — write approval, proposal accept/reject, action confirm, spend caps, run detail, memory capture, or any AI action with irreversible blast radius. Trigger on confirmation UX, undo, cost-before-act, show-the-plan, citations, or keeping the owner in control.

PASS/FAIL eval rubrics and alignment loops for Sid Orchestra (global). Use when the user says sid evals, @sid-evals, grade this, eval gate, alignment score, or wants to stop AI slop. Works in any workspace; bootstraps EVALS.md from ~/.cursor/skills/sid-orchestra/templates if missing.

Runs a two-wave validation pipeline (deterministic checks then rule-based checks) before every git commit, writing a sentinel file that a pre-commit hook enforces. Includes optional quick mode (first wave only) and a fix loop with up to three iterations.

Use for writing, reviewing, debugging, or testing bounded retry policies in Python with Tenacity, including retry predicates, stop and wait strategies, jitter, exception propagation, callbacks, Retrying, and AsyncRetrying. Do not use for generic loops, scheduled jobs, domain polling without a retryable operation, or operations whose side effects are not safe to repeat.