Results for “fix”

Composite skill — safely refactor a module end-to-end with sequencing, parallel implementation, post-refactor cleanup, and rationale capture. Chains refactor-plan (phased plan + rollback) → three-man-team (architect/builder/reviewer in parallel) → fix-the-suite post-refactor → adr-write → docs-sync. Use for non-trivial refactors that need both careful sequencing and durable record.

Run fb.ai's full SEO site audit — discover the real competitors, benchmark the brand's site against them, and report the page-level and sitewide issues with concrete fixes. The audit is the most expensive single fb.ai action (0.75 quota), so it is always priced and confirmed first. Run on demand or monthly.

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments. Triggers Greptile review, fixes all actionable comments, pushes/re-shelves, re-triggers review, and repeats. Use when the user wants to fully optimize a PR/MR/CL against Greptile's code review standards.

Use to set up or fix quality assurance for voice/phone support, including transcript-based and AI-graded call QA. Trigger for "QA our calls", "score phone conversations", call transcription accuracy for QA, diarisation or speaker attribution problems, word error rate, grading calls from transcripts, or adapting a chat/email QA scorecard to voice.

Use when asked to fix, build, refactor, review, verify, or release software and the work is non-trivial — including delivering a change request (issue, ticket, or request) from intake through planning, gates, implementation, review, verified PR, and authorized post-merge release. neckbeard routes the change through framing, discovery, design, implementation, review, verification, delivery, and learning — choosing the smallest *safe* intervention, proving it at the real delivery boundary, and leaving an inspectable evidence ledger. For change-request / issue-to-PR work, conditionally loads a 9-phase journey with gates, delivery packet, and lifecycle integration. Composes specialist catalog skills rather than replacing them. Not a persona, not a '10x developer' prompt, not a LOC-minimizer. The journey is not loaded for plain fixes, refactors, or reviews that lack an issue/ticket trajectory.

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

Use when a task is well-defined, has an automatic way to verify success (tests, linter, build), and is tedious or large enough to benefit from unattended iteration - e.g. "get all tests passing", "implement this spec end to end", "fix every lint error". Not for one-shot changes or work that needs human judgment mid-stream.

Composite skill — take a PR from "I think it's ready" to merged with full gate verification. Chains pr-merge-readiness (verdict) → ci-watch / gh-fix-ci (if blockers) → gh-address-comments (if review needed) → ship (when verdict is MERGE). Use as the one-call answer to "can I merge this?" instead of running 4 skills sequentially.

Audit a directory of multilingual blog content for completeness, consistency, hreflang correctness, meta-tag parity, and freshness. Builds a translation coverage matrix, flags stale translations, validates hreflang and schema, and emits a prioritized report with runnable fix commands. Use when user says "locale audit", "blog locale-audit", "check translations", "multilingual audit", "translation check", "hreflang check", "Uebersetzungen pruefen".

Use to design or fix a customer support survey — CSAT, NPS, or CES — and to diagnose response bias. Trigger for "design a CSAT survey", "our CSAT doesn't match reality", "should we use NPS", survey response rate, non-response bias, survey timing or scale choice, comparing satisfaction across teams or channels, or interpreting a satisfaction trend.

Composite skill — diagnose, repair, and validate a test suite end-to-end. Chains test-health (diagnose) → config-drift-detect (gate compatibility) → test-cleanup (prune + add integration tests) → mutation-test (validate survivors) → adr-write (capture decisions) → docs-sync. Use when "the test suite is bad" or you've hit the test-cleanup-bails-at-the-gate failure mode.

Audit a repository, vet and prioritize evidence-backed findings, write drift-aware implementation plans, delegate bounded work, and independently verify results. Use when asked to improve, audit, modernize, harden, review, plan fixes for, or systematically reduce risk in a codebase. Use native isolated agents for implementation; use OpenRouter/free only for narrow advisory audit slices under its safety limits.

Use CircleCI Chunk for AI-assisted CI/CD work through either the Chunk web UI or the chunk-cli. Trigger this skill when users ask to set up Chunk, troubleshoot or fix failing builds with Chunk, configure Chunk environments, schedule/proactively run Chunk tasks, or use chunk-cli commands such as init, validate, build-prompt, auth, sandbox, task, and skill install.

Generate or improve MATLAB help text (documentation comments) for a function, class, or script file following MathWorks standards (H1 line, syntax paragraphs, See Also, 75-char lines). Read BEFORE writing MATLAB help — default patterns (Inputs:/Outputs: lists, block comments, uppercase See Also) produce non-conforming output. Use when writing, rewriting, fixing, or reviewing MATLAB help comments or function documentation.

In-session iterative loop — keeps Claude running in the current session until a task is done. Unlike /loop (which spawns background workers), /iloop stays in the current session and re-prompts each iteration via Stop hook. Use for: 'keep fixing until tests pass', 'iterate until this feature works', autonomous debugging. Triggers on: '/iloop', 'in-session loop', 'keep iterating', 'loop until done'.

Econometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "staggered DID", "event study regression", "two-way fixed effects DID", "callaway santanna", "sun and abraham", "双重差分", "倍差法", "平行趋势", "处理组", "对照组", "政策评估", "事件研究", "交错DID", "渐进处理"

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Use to quantify the revenue exposed by unresolved support failures, complaints and escalations without inflating the number. Trigger for "how much revenue is at risk", "what are these support failures costing us", "revenue behind our open escalations", building a business case for fixing a support problem, or a revenue-at-risk figure that looks too large to believe.

Use to design support career progression with IC and lead tracks, skill gates instead of tenure alone, and paths that do not treat leaving the phones as the only promotion. Trigger for "career pathing", "progression framework for support", "IC track", "how do agents get promoted", "support ladder", "team lead vs senior agent", or fixing promotion bottlenecks and title inflation.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Econometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "staggered DID", "event study regression", "two-way fixed effects DID", "callaway santanna", "sun and abraham", "双重差分", "倍差法", "平行趋势", "处理组", "对照组", "政策评估", "事件研究", "交错DID", "渐进处理"

BARRACUDA v1.0.1 — Funding Decay Collector. Finds assets where extreme funding has persisted for 6+ hours, confirmed by SM alignment from Hyperfeed and 4H trend structure. Enters to collect funding while riding the trend. Double edge: price appreciation + funding income from trapped traders on the other side. Fixes Croc's -42.7% failure by requiring SM and trend confirmation before entering.

Deterministic LLM-first SEO audits for websites, blog posts, and GitHub repositories. Use this when the user asks to "perform SEO analysis", "run SEO audit", "analyze SEO", "check technical SEO", "review schema", "Core Web Vitals", "E-E-A-T", "hreflang", "GEO", "AEO", or GitHub repository SEO optimization. For full/page/repo audits, run bundled scripts for evidence and return prioritized, confidence-labeled fixes.

Diagnose and remove FPS caps so the editor and game run uncapped (or at a target FPS). Use when the user says the editor/game is "locked", "capped", or "stuck" at a frame rate (commonly 60 FPS), asks to "unlock"/"uncap"/"raise" FPS, or wants to set a max FPS. Covers t.MaxFPS, VSync, fixed/smoothed frame rate, and background CPU throttling (EngineSettingsService).

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Checks a GitHub, GitLab, or Perforce (p4) pull request (or merge request, or shelved changelist) for unresolved review comments, failing status checks, and incomplete PR descriptions. Waits for pending checks to complete, categorizes issues as actionable or informational, and optionally fixes and resolves them. Use when the user wants to check a PR/MR/CL, address review feedback, or prepare a change for submission.

This skill should be used when the user wants to implement features or fix bugs using test-driven development. Enforces the RED-GREEN-REFACTOR cycle with vertical slicing, context isolation between test writing and implementation, human checkpoints, and auto-test feedback loops. Uses multi-agent orchestration with the Task tool for architecturally enforced context isolation. Supports Jest, Vitest, pytest, Go test, cargo test, PHPUnit, and RSpec.

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Measure pleasur.ai's AI-citation share across ChatGPT / Perplexity / Gemini / Google AI Overviews for the tracked query list, using SemRush (data API for AIO-presence screening + AI Toolkit via browser for share-of-voice / mention + citation gaps) and direct engine queries. Scores each query into the GEO ledger and surfaces the highest-leverage gaps to fix. The GEO Lead's core measurement loop.

Turn a GitHub pull request (a PR URL, owner/repo#N, or 'this PR' in a checked-out repo) into a code-change explainer video — changelog, feature reveal, fix, or refactor walkthrough built from the diff, commits, and files: the input is a code change, not a website. Not a product promo (/product-launch-video) or a no-PR topic explainer (/faceless-explainer). Unclear → /hyperframes.

Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use `improve-animations` or `review-animations` instead. Source: github.com/emilkowalski/skills.

Review a code file or directory and produce an evidence-backed GitHub or Jira issue proposing bug fixes, performance improvements, modularity improvements, DRY refactors, file splitting, reusable helpers, and architecture-alignment work. Use when a user asks for a code review, technical-debt proposal, refactor proposal, quality audit, bug-risk review, architecture-alignment review, or issue creation. This skill proposes work; it does not modify code.