Results for “prose-review”

Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.

Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.

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

Rewrites and polishes prose in Chinese or English, removes AI-like wording, and reviews product localization copy while preserving intent for drafts, docs, release notes, launch copy, and social posts. Use when users ask in any language to draft, rewrite, proofread, localize, polish release notes, remove AI-like wording, or prepare launch and social copy. Not for code comments, commit messages, or inline docs.

Simulates a NeurIPS/SC/ICSE-style peer review with five reviewer personas (HPC, ML, Stats, Reproducibility, Devil's Advocate) that verify every claim against actual result data before submission.

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

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。

Publication Specialist - Writing, Review, Pre-registration & Quality Assurance Light VS applied: Avoids template-based writing + audience-specific message design Absorbed G3 (Peer Review Strategist), G4 (Pre-registration Composer), F1-F3 (Quality functions) capabilities Use when: writing abstracts, creating summaries, peer review response, pre-registration, reporting checklists, reproducibility Triggers: abstract, plain language, press release, summary, communication, peer review, revision, pre-registration, OSF, PRISMA, CONSORT, reproducibility

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.

Review pull requests against repository standards using automated validation and manual content review.

Analyzes state merit review for non-covered securities offerings, applying NASAA Statements of Policy to cheap stock, promoter equity investment, voting rights, and promoter compensation. Produces examiner-ready comment responses with cap table analysis and negotiation strategy. Use when filing Reg A, Rule 504, intrastate, or direct public offerings in merit review states, responding to Blue Sky examiner comments, structuring offerings to avoid conditioning, or analyzing NASAA SOPs. Also trigger on cheap stock analysis, promoter equity tests, unequal voting rights review, state examiner correspondence, or phrases like "merit review issues" or "the state examiner sent comments."

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

Turn interactive commit reviews back on for the current herdr workspace.

Runs a multi-perspective review of a pull request, including code quality, tests, and potential silent failures, then reports findings ranked by severity.

Review an exact PR head in isolation using trusted-base instructions and execution evidence

Readability Review

Routes quality reviews to specialized critic agents based on file type or flags, covering peer review, code review, and manuscript polish.

Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:review or asks what has been learned and what should be promoted or pruned.

Use this skill for code review and PR review tasks. Covers review methodology, what to flag, what to skip, and output structure.

Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.

Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.

Reviews code diffs, PRs, issue queues, release readiness, commits, pushes, publishing, and project audits. Use when users ask in any language for code review, issue or PR triage, release gates, publishing follow-through, or project audits. Not for debugging root causes or prose review.