Results for “talent-review”

Draft performance reviews, self-assessments, peer reviews, and upward feedback in your own voice using WorkIQ to surface actual contributions and structure them into impact-focused writing.

Audit an existing processkit skill against the 5 Skill Killers, the Agent Skills standard, and Anthropic's troubleshooting playbook, producing a categorized findings report and draft Gotchas.

Lightweight ContentShake AI self-check the /draft stage can call before saving. Returns just SEO + Quality scores (no full optimization) so the writer knows whether the draft is in winning territory before /quality-check runs. Fails soft when SEMRUSH_API_KEY is unset.

Transforms uploaded course materials into exam-oriented study notes, practice questions, and scoring-focused explanations.

依据竖屏短剧评估标准，从核心爽点、故事类型等维度评估打分。适用于评估故事改编为竖屏短剧的潜力、分析市场竞争力

Iteratively reviews and fixes Claude Code skill quality issues by running automated fix-review cycles using the skill-reviewer agent until they meet standards.

严格细致判断与评分故事文本，从市场潜力、创新属性、内容亮点维度分析质量。适用于小说初筛选、多维度评估打分

Review MetaSkill skills before publication for privacy, public-safe examples, frontmatter and folder standards, truthful capability claims, and resource consistency.

Analyze the available skill set and recommend candidate groups that could be consolidated into sub-skill bundles. Read-only — proposes a plan, does not move files.

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Forge reviews its own skill updates, review history, and research outputs before publishing them.

通用跨模型审查：Review LLM 对任意研究制品进行独立评审，输出结构化评分、wiki 实体映射与改进建议

Iteratively improve a Claude Code skill using the skill-reviewer agent until it meets quality standards. Use when improving a skill with multiple quality issues, iterating on a new skill until it meets standards, or automated fix-review cycles instead of manual editing.

Use an independently assigned `review-agent` for post-authoring review of changed rd-skills routing registries, fixtures, mappings, or owner conflicts without repair. Skip product work and in-task global rerouting.

`analysis-agent`/`task-agent`/`review-agent`: use when code needs correctness, security, performance, maintainability, or hallucinated-API review; skip when no review is needed.

帮助用户撰写高质量的文献综述类论文。提供从选题、文献检索、评估筛选、结构规划到最终写作的全流程指导。适用于需要撰写独立文献综述论文或学术论文中文献综述部分的用户。

Evaluate scientific manuscripts and grant proposals with structured, checklist-based peer review covering methodology, statistics, reproducibility, ethics, and reporting standards.

Spec Craft

The art of reviewing code that improves both the codebase and the developer - sharing knowledge, maintaining standards, and building cultureUse when "code review, PR review, pull request, merge request, review comments, LGTM, review feedback, approve PR, request changes, review checklist, code quality, review standards, code-review, pull-request, PR, quality, standards, feedback, collaboration, mentoring" mentioned.

任意のリポジトリ（アプリ/ライブラリ/運用スクリプト/コンテンツ等）の種別を判定し、 種別に応じた評価軸（品質・テスト・依存、または検証ゲート等）で**実測ベース**評価して優先度付き改善案を出すスキル。 言語非依存（Python は AST 詳細・その他は近似と明記）。ベンダーコード混入・除外の空振り・偽の成功終了コードなど、 「黙って間違った数値を出す」失敗を構造的に封じる。 「リポジトリレビューして」「コード品質を評価して」「このプロジェクトを診断して」「包括レビュー」「repo-review」 「アーキテクチャ評価して」等で発火。/repo-review でも起動。

Review a ticket or PR through focused specialist lenses: scope, architecture, security, tests, AC coverage, and PR metadata.

Loop feature-interviews over a brainstorm idea set and consolidate survivors into the roadmap

Comprehensive code review using specialized agents — orchestrates code, comments, tests, errors, types, and simplify agents sequentially.

Generate one high-value follow-up workflow proposal when MoonMind execution quality issues are detected in a run.

Use when a paper is complete or near-complete and a holistic pre-submission audit is needed. Cross-cuts text, code, tables, figures, results, citations, and reproducibility in a single pass and produces a persistent audit report. Works standalone on papers written outside the plugin.

Evaluate a paper's contribution novelty, identify best-fit SSCI journal fields and ABS star rating, and recommend 20 target journals. Trigger when user says "paper submission" / "paper-submission" / "投稿评估" / "期刊推荐" / "target journal" / "选刊".

Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.

Review AI agent skills using a dual-axis method: deterministic code-based checks and LLM deep review, with weighted scoring and improvement recommendations.

Professional code review with auto CHANGELOG generation, integrated with Codex AI

Create new skills, modify and improve existing skills, and measure skill performance through iterative evaluation and benchmarking.

`analysis-agent`/`task-agent`/`review-agent`: primary-Skill-selected for races, locks, optimistic conflicts, or worker overlap; never task owner; skip without concurrency impact.

Eng manager-mode plan review. (gstack)

`analysis-agent`/`task-agent`/`review-agent`: use when authoring SKILL.md, triggers, decisions, references, registry, routing, or validation; skip when no Skill content changes.

Seven-role depersonalised panel review of framework artefacts (KUD, criterion bank, LT definition, crosswalk, scope-and-sequence) in sequential-isolation mode. Gate rule mean>=88 AND no role<70.

>- Skill Refiner, the eval-guided improvement loop for SKILL.md files. Runs the bootstrap, score, propose, apply, and status cycle as a thin wrapper over the published @intentsolutions/refiner CLI, proposing safe, minimal, bounded SKILL.md edits and accepting an edit only when a held-out eval score strictly improves with no regression on any other case. Ships a 3-layer cost-tiered hook architecture (sinker, line, hook) that gates skill quality at edit time, end of turn, and commit time. Use when improving an existing skill, refining a SKILL.md against measured behavior, bootstrapping an eval set for a skill, or gating skill edits before they ship. Trigger with "/j-rig", "refine this skill", "bootstrap an eval set", "propose a skill edit", "promote the candidate", or "skill refiner status".