Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature.
日本語の概要は準備中です。原文の説明を表示しています。
tensology/decisionsai☆ 172026年10月13日 更新
Regression check — diff a live page's web accessibility (a11y) violations against a baseline. By default it compares your uncommitted changes (stash-based); pass `--branch [<name>]` to compare against a branch. Reports the new WCAG violations introduced, the ones fixed, and the count of pre-existing ones. Use it for 'did my change break accessibility', 'what a11y issues did this PR add', or as a CI gate. For a full scan of one page use `accessibility-scan`; for a whole site use `accessibility-audit`.
日本語の概要は準備中です。原文の説明を表示しています。
tensology/decisionsai☆ 172026年10月13日 更新
Remediation only — repair web accessibility (a11y) violations against WCAG 2.2 with a baseline, edit, and verify loop. Takes a target (URL, files, directory) or a findings worklist from `accessibility-scan`/`accessibility-inspect`/`accessibility-audit`, applies mechanical fixes as given, leaves TODOs for visual or contextual judgment, and verifies by re-running the baseline check. It only fixes. To find issues use `accessibility-scan` (one page, automated), `accessibility-inspect` (one page, manual), or `accessibility-audit` (whole site, WCAG-EM); to check for regressions use `accessibility-diff`. Use it for 'fix the a11y issues in X', 'make this accessible', 'add missing alt text and labels', 'apply these accessibility fixes', 'remediate these violations'.
日本語の概要は準備中です。原文の説明を表示しています。
tensology/decisionsai☆ 172026年10月13日 更新
Coordinates code quality: ln-511 metrics, ln-512 cleanup, inline agent review (Codex + Gemini), ln-513 regression, ln-514 log analysis. Returns quality_verdict + aggregated results.
日本語の概要は準備中です。原文の説明を表示しています。
tensology/decisionsai☆ 172026年10月13日 更新
QA a change by driving the running dev app like a real QA engineer - start the server and a real browser session, write a checklist from the agreed requirements and the diff, execute every item with evidence, then go looking for anything that looks off even where the diff did not touch. Reports findings by severity and separates regressions from pre-existing problems. Use after a change is implemented and the gates pass, when the user asks to "QA this", "test it in the app", or "check it actually works".
日本語の概要は準備中です。原文の説明を表示しています。
michaelst/spendable☆ 172026年9月5日 更新
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
日本語の概要は準備中です。原文の説明を表示しています。
manu14357/zskills☆ 162026年7月24日 更新
Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.
日本語の概要は準備中です。原文の説明を表示しています。
manu14357/zskills☆ 162026年7月24日 更新
Trigger when: (1) the user mentions "manim", "scene", "video", "EN/KO render", "GEODE_HERO_LANG", "1080p60", or (2) editing files under `scripts/visualizations/` ending in `.py`, or (3) the user asks to render, re-render, or extend any of the four validated scenes (`geode_hero.py`, `autoresearch_filewalk.py`, `autoresearch_compare.py`, `critical_floor.py`). GEODE Manim Scene authoring standard. Locks the patterns the four validated scenes already share — Anthropic-style palette, Helvetica Neue + Pretendard font pairing with weight=NORMAL, EN/KO multilingual lang via `GEODE_HERO_LANG` env, `_dashed_arrow_with_head` stage-coupled tinting, `verify_hero_layout.py` ratchet — so the next scene does not re-discover the kerning / padding / transition regressions catalogued in [[viz-frame-audit]].
日本語の概要は準備中です。原文の説明を表示しています。
mangowhoiscloud/geode☆ 152026年10月13日 更新
法外功夫 — Non-legal business skills for lawyers. Decision analysis, game theory, contract design, accounting, finance, microeconomics, law & economics, statistics, and regression analysis distilled into deep, actionable frameworks for legal practice. Each domain includes formulas with LaTeX notation, worked examples, adversarial checklists, and book-aligned structure. | 律师必备的非法律商业技能深度参考:决策分析、博弈论、合同设计、会计、金融、微观经济学、法经济学、统计分析、多元回归。每章都包含完整公式推导、worked examples、对抗清单与经典判例。当用户涉及和解谈判、合同激励、财务尽调、企业估值、损害赔偿计算、反垄断分析、统计证据评估、歧视诉讼回归分析、hold-up、效率违约、Daubert 动议等场景时触发。
日本語の概要は準備中です。原文の説明を表示しています。
CSlawyer1985/legal-skillhub☆ 152026年9月23日 更新
Use when autonomously improving a measurable scalar metric through bounded, git-tracked iterations: modify one scoped change, verify, keep or revert. Triggers on /mk:loop, 'optimize coverage/bundle size/lint count', 'iterate until the metric improves'. NOT for subjective cleanup (see mk:cook), known-root-cause bugs (see mk:fix), behavioral grading (see mk:evaluate), or shipping (see mk:ship).
日本語の概要は準備中です。原文の説明を表示しています。
ngocsangyem/MeowKit☆ 152026年7月28日 更新
Investigate reviewed Grafana APM evidence for request rate, error rate, and operational latency. Use when an application is slow, erroring, dropping traffic, regressing against a baseline, or needs a bounded request-rate, error, and p95 latency health assessment.
日本語の概要は準備中です。原文の説明を表示しています。
openai/community-plugins☆ 152026年10月13日 更新
Reflect subskill for simmer. Records iteration results in trajectory table, tracks best candidate, handles regression rollback, and passes ASI forward to the next round. Supports both single-file and workspace modes. Do not invoke directly — called by simmer orchestrator after each judge round.
日本語の概要は準備中です。原文の説明を表示しています。
2389-research/simmer☆ 152026年7月7日 更新
Verifies build output integrity after code changes. Runs builds, validates artifact structure, checks for regressions in bundle size, asset references, and static export completeness. The last line of defense before a bad deploy ships.
日本語の概要は準備中です。原文の説明を表示しています。
curiositech/windags-skills☆ 142026年10月12日 更新
Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill, PWP, WLW), and interval-censored data. Use when analyzing time-to-event endpoints (OS, PFS, DOR, TTR, TTNT) in oncology or other clinical trials.
日本語の概要は準備中です。原文の説明を表示しています。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Performs subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine claims.
日本語の概要は準備中です。原文の説明を表示しています。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
日本語の概要は準備中です。原文の説明を表示しています。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Design, implement, and evaluate risk-based software tests across unit, integration, contract, end-to-end, and regression layers. Use when adding tests, reproducing bugs, improving coverage, diagnosing flaky tests, or defining a test strategy; do not use to change production behavior unless the user also requests implementation.
日本語の概要は準備中です。原文の説明を表示しています。
Phelan164/codex-howto☆ 132026年10月10日 更新
Review code changes for correctness defects, regressions, security risks, data-integrity problems, concurrency hazards, and missing meaningful tests. Use for pull requests, branches, commits, patches, or working-tree reviews; do not use for implementation unless the user separately requests fixes.
日本語の概要は準備中です。原文の説明を表示しています。
Phelan164/codex-howto☆ 132026年10月10日 更新
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
日本語の概要は準備中です。原文の説明を表示しています。
kevinnft/ai-agent-skills☆ 132026年8月1日 更新
Review local git changes before opening a PR or merging. First review all local tracked and untracked files; if none exist, review the current branch against a requested base branch or the Git Town parent branch. Use zero to three review subagents only when risk, diff size, language specificity, or uncertainty justifies the token cost, then report high-confidence bugs, regressions, risky assumptions, and missing tests. Use when the user asks for code review, local review, branch sanity check, pre-PR review, or review of work-in-progress changes.
日本語の概要は準備中です。原文の説明を表示しています。
rijkvanzanten/rolling-wave-engineering☆ 132026年8月18日 更新
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
日本語の概要は準備中です。原文の説明を表示しています。
youranreus/note☆ 122026年8月6日 更新
Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.
日本語の概要は準備中です。原文の説明を表示しています。
aiopshwang/data-analysis-ml-agent-skills☆ 122026年8月27日 更新
Cloud guardrails for any vendor workload — Google Cloud (GCP, Vertex AI, GKE), AWS (IAM, EKS, Bedrock), Azure (Entra ID, Policy, AKS), Alibaba Cloud (RAM, mainland/international residency). Enforces identity least-privilege, mechanical policy, data boundaries, residency, cost caps, network egress and observability, with official-source validation before any claim. Trigger on any cloud infrastructure design, review, Terraform plan, or LLM/agent deployment; the-architect routes here.
日本語の概要は準備中です。原文の説明を表示しています。
jpantsjoha/ai-native-developer-experience☆ 122026年10月13日 更新
Re-audit code changes to identify side effects, regression risks, and unhandled edge cases before merging or deploying. Use after a change is complete and before merging to a shared branch, before deploying a hotfix, after complex multi-module refactoring, or when a previous review may have missed side effects in async, state-mutating, or security-sensitive code paths.
日本語の概要は準備中です。原文の説明を表示しています。
comsky/remy-skill-recipes☆ 122026年7月15日 更新