调试
定位并修复问题，分析错误
debug-cli
antinomyhq
Use when users need to debug, modify, or extend the code-forge application's CLI commands, argument parsing, or CLI behavior. This includes adding new commands, fixing CLI bugs, updating command options, or troubleshooting CLI-related issues.
process-modeling
melodic-software
Process modeling using BPMN notation and flowchart patterns. Creates process diagrams with activities, gateways, events, swimlanes, and decision points for workflow documentation.
bpmn-workflow
WellApp-ai
Generate and maintain BPMN 2.0 diagrams linked to Gherkin scenarios
state-machine
WellApp-ai
Document UI component states (current vs expected) with transitions
qa-commit
WellApp-ai
Verify implementation against QA Contract (G#N, AC#N), auto-invoke debug on RED
code-review
WellApp-ai
Review code changes against hard rules and conventions
test-hardening
WellApp-ai
Convert passed QA Contract criteria to automated tests
autonomous-loop
WellApp-ai
Iterate until success or limit, composing existing skills with Jidoka integration
debug
WellApp-ai
Systematic debugging with MCP integration, auto-invoke from qa-commit, Phase 7 Harden
slack-announce
WellApp-ai
Generate formatted Slack messages for team communication
git-commit-specification
TencentBlueKing
Git 提交规范，涵盖 commit message 格式（feat/fix/refactor）、Issue 关联、分支命名、PR 提交准备、rebase 使用。当用户提交代码、编写 commit message、创建分支或准备 PR 时使用。
pixel-asset-gen
xuiltul
ドット絵ワークスペース用のキャラクタースプライトを、codexのimage_genに指示して生成する手順。 承認済みシートを土台にしたidentity差し替え、10行の意味的一貫性、実画面プレビュー、 runtime反映前の承認までを扱う。Animaのpixel_sheet.pngを新規作成・差し替え・修復するとき、 Pixel Workspaceのキャラクターが細い、潰れる、行ごとに別人化する問題を直すときに使う。
analyzing-time-series
https-deeplearning-ai
Comprehensive diagnostic analysis of time series data. Use when users provide CSV time series data and want to understand its characteristics before forecasting - stationarity, seasonality, trend, forecastability, and transform recommendations.
software-evaluation
ymd38
Evaluate code quality across five pillars (Architecture, Reliability, Observability, Security, DX) and produce a 1-10 scorecard with a strategic improvement roadmap. Use when you want a comprehensive quality review of a directory or module. Triggers on requests like "evaluate code quality", "review architecture", "score my code", "code audit", "/software.evaluation", or when asked for a quality assessment of a directory from a CTO or architect perspective.
code-pattern-extractor
ArabelaTso
Analyze codebases to identify reusable code patterns, duplications, and implementation patterns for future development. Use when refactoring code, identifying technical debt, finding opportunities for abstraction, or documenting common patterns in a directory or module. Outputs pattern catalogs, refactoring suggestions, and reusable template code.
bug-to-patch-generator
ArabelaTso
Generate code fixes and patches from bug reports, failing test cases, error messages, and stack traces. Use this skill when debugging code, fixing test failures, addressing GitHub issues, resolving runtime errors, or patching security vulnerabilities. Analyzes the bug context, identifies root causes, and generates precise code patches with explanations and validation steps.
brainstorming
vudovn
Socratic questioning protocol + user communication. MANDATORY for complex requests, new features, or unclear requirements. Includes progress reporting and error handling.
code-repair-generation-combo
ArabelaTso
Automatically repair buggy code and generate comprehensive tests for Python, Java, and C++ programs. Use when users need to fix logic errors or runtime errors in functions, modules, or repositories. Accepts specifications via natural language descriptions, existing test cases, or input/output examples. Generates corrected code, creates or updates tests to verify correctness and prevent regressions, and produces a detailed report explaining the bug, fix, and testing strategy. Triggers on requests like "fix this bug", "repair this code", "debug this function", or "this code is broken".
ambiguity-detector
ArabelaTso
Detects and analyzes ambiguous language in software requirements and user stories. Use when reviewing requirements documents, user stories, specifications, or any software requirement text to identify vague quantifiers, unclear scope, undefined terms, missing edge cases, subjective language, and incomplete specifications. Provides detailed analysis with clarifying questions and suggested improvements.
bug-history-summarizer
ArabelaTso
"Summarizes the complete lifecycle of a bug across code versions, tracking its introduction, detection, fixing attempts, and regression history. Use when users need to: (1) Understand how a bug evolved over time, (2) Trace when and how a bug was introduced, (3) Analyze fix attempts and their effectiveness, (4) Identify regression patterns, (5) Generate bug lifecycle reports for documentation or post-mortems. Takes a repository, bug identifier, and version history as input."
counterexample-to-test-generator
ArabelaTso
Automatically generates executable test cases from model checking counterexample traces. Translates abstract counterexample states and transitions into concrete test inputs, execution steps, and assertions that reproduce property violations. Use when working with model checker outputs (SPIN, CBMC, NuSMV, TLA+, Java PathFinder, etc.) and needing to create regression tests, validate bug fixes, or reproduce verification failures in executable test suites.
abstract-state-analyzer
ArabelaTso
Performs abstract interpretation over source code to infer possible program states, variable ranges, and data properties without executing the program. Reports potential runtime errors including out-of-bounds accesses, null dereferences, type inconsistencies, division by zero, and integer overflows. Use when analyzing code for potential runtime errors, performing static analysis, checking safety properties, or verifying program behavior without execution.
bug-reproduction-test-generator
ArabelaTso
"Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories. Use when users need to: (1) Create a test that reproduces a bug described in an issue report, (2) Generate failing tests from bug descriptions, stack traces, or error messages, (3) Validate bug reports by creating reproducible test cases, (4) Convert issue reports into executable regression tests. Takes a repository and issue report as input and produces test code that reliably triggers the reported bug."
assertion-synthesizer
ArabelaTso
Generate test assertions from existing code implementation. Use when the user has implementation code without tests or incomplete test coverage, and needs assertions synthesized by analyzing the code's behavior, inputs, outputs, and state changes. Supports Python (pytest/unittest), Java (JUnit/AssertJ), and JavaScript/TypeScript (Jest/Chai). Handles equality checks, collections, exceptions, and state verification.