Scaffold a ready-made AI agent harness in one command from the 19 published @metaharness/* example packages — 9 host integrations (Claude Code, Codex, Hermes, pi.dev, OpenClaw, RVM, Copilot, OpenCode, GitHub Actions) + 10 vertical pods (devops, research, trading, support, legal, coding, education, sales, gaming, repo-maintainer).
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ruvnet/metaharness☆ 7162026年10月25日 更新
TripAdvisor Content API for hotel ratings, restaurant search, attraction reviews, rankings, and nearby locations. Use when evaluating hotels or researching destinations. 5K calls/month.
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borski/travel-hacking-toolkit☆ 7122026年10月19日 更新
Mandatory pre-flight-search reference. Contains the Seats.aero workflow (pull ALL programs first), source accuracy hierarchy, Southwest/Companion Pass specifics, small-market caveats, and Duffel limitations.
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borski/travel-hacking-toolkit☆ 7122026年10月19日 更新
Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator delegates Step 1 or when the user asks to "outline a paper from raw materials" or "generate the paper structure".
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Run the four paper-quality autoraters from PaperOrchestra (arXiv:2604.05018, App. F.3) — Citation F1 (P0/P1 partition + Precision/Recall/F1), Literature Review Quality (6-axis 0-100 with anti-inflation rules), SxS Overall Paper Quality (side-by-side), and SxS Literature Review Quality (side-by-side). TRIGGER when the user asks to "score this paper draft", "evaluate against the benchmark", "compare two papers", or "run the autoraters".
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corroborate against Crossref + OpenAlex to flag hallucinated citations, build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules, deterministic 0-100 decision bands (Accept/Minor/Major/Reject) that drive a target-met early stop, and a Devil's Advocate concession-threshold guard that blocks acceptance on unresolved critical findings. Maintains a worklog and snapshots each iteration so revert is real, not symbolic. TRIGGER when the orchestrator delegates Step 5 or when the user asks to "refine the draft", "iterate on the paper", or "run peer review on this paper".
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Reverse-engineer raw materials (Sparse idea, Dense idea, experimental log) from an existing AI research paper to build a benchmark case for evaluating paper-writing pipelines. Replicates the PaperWritingBench dataset construction procedure from arXiv:2604.05018 §3 / App. C. TRIGGER when the user asks to "build a benchmark case from this paper", "reverse-engineer raw materials", or "evaluate my pipeline against PaperWritingBench".
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGGER when the user asks to "write a paper from my experiments", "turn this idea and these results into a paper", "generate a conference submission", "run paper-orchestra on X", or otherwise wants the end-to-end paper-writing pipeline. Coordinates the outline-agent, plotting-agent, literature-review-agent, section-writing-agent, and content-refinement-agent skills.
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.md). TRIGGER when the user says "aggregate my agent logs for paper writing", "extract experiments from my coding agent history", "prepare PaperOrchestra inputs from my cache", "turn my agent logs into a paper", mentions a folder or directory they want to use as the basis for a paper, or wants to run PaperOrchestra but only has scattered agent experiment histories rather than structured inputs. Run this BEFORE paper-orchestra. Also called automatically by paper-orchestra when workspace/inputs/idea.md or workspace/inputs/experimental_log.md are missing.
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Ar9av/PaperOrchestra☆ 6922026年10月12日 更新
Transform ordinary snapshots—including daily moments, portraits, objects, pets, food, interiors, streets, architecture, landscapes, travel, and humanistic scenes—into the restrained Shijing Paper Zine visual style. Use when the user wants any real photo turned into a spacious paper-editorial composition with an irregular photographic fragment, simplified source-derived drawing, one structural print color, tactile torn-paper texture, minimal micro-copy, a consistent multi-image series, or a source-to-poster comparison.
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kangarooking/kangarooking-skills☆ 6832026年9月7日 更新
Stop-motion and craft aesthetics for Blender including claymation, paper craft, and handmade physical-material cues.
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arjun988/blender-skills☆ 6782026年7月11日 更新
Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For US legal or regulatory questions use gov; for papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.
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firecrawl/cli☆ 6672026年10月24日 更新
Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.
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firecrawl/cli☆ 6672026年10月24日 更新
Dung khi can nghien cuu tep truoc khi chay ads — interest va behavior mapping, do rong tep, phan tang cold/warm/hot, va gia thuyet targeting de test. Kich hoat khi user nhac 'nghien cuu audience', 'tep target', 'nham ai', 'interest targeting', 'chon tep chay ads', 'lookalike tu dau'. Khong dung cho — hieu tam ly va ngon ngu khach hang thi dung skill 09-insight-khach-hang; phan bo ngan sach cho tung tep thi dung skill 54-media-plan.
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minhnv0807/ai-business-skills☆ 6282026年9月12日 更新
Use when the user needs to understand competitors — direct, indirect, and substitute tiers, positioning map, SWOT, ad and content benchmark, pricing comparison, and the market gap to attack, using SimilarWeb, Ahrefs, Semrush, and the Meta Ad Library. Trigger on 'competitor research', 'competitive analysis', 'what are competitors running', 'who else sells this', 'why do people pick them over us', 'benchmark us against the market'. Also use when the user sends a competitor link and asks for an opinion. Not for — understanding the customer rather than the rival, see `09-customer-insight-global`; turning difference into a statement, see `58-positioning-global`; paid targeting, see `51-audience-research-global`.
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minhnv0807/ai-business-skills☆ 6282026年9月12日 更新
Use when paid ad AUDIENCES must be researched and defined before launch — target profile, interest and behavior mapping per platform, audience sizing, cold, warm, and hot tiering, lookalike seeds, exclusions, and ranked targeting hypotheses to test. Trigger on 'audience research', 'who should I target', 'interest targeting', 'Meta audience for this product', 'TikTok targeting ideas', 'my targeting is too broad'. Also use when launch is imminent and the ad set targeting is still empty. Not for — persona and JTBD depth for content, see `09-customer-insight-global`; warm retargeting tiers, see `56-retargeting-plan-global`; where the budget goes, see `54-media-plan-global`; the campaign hierarchy, see `52-account-structure-global`.
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minhnv0807/ai-business-skills☆ 6282026年9月12日 更新
Use when the user needs to understand customers deeply enough to write copy and pick targeting — consumer versus shopper, JTBD, layered persona, internal monologue, pain map, objection list, journey map, and a customer language bank pulled from real reviews and DMs. Trigger on 'customer insight', 'buyer persona', 'who is my customer', 'what do they actually want', 'jobs to be done', 'why do they hesitate before buying'. Also use when the user cannot explain who the product is for. Not for — intake questions when an agency signs a new client, see `20-client-intake-brief-global`; paid audience targeting setup, see `51-audience-research-global`; competitor study, see `08-competitor-research-global`.
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minhnv0807/ai-business-skills☆ 6282026年9月12日 更新
Research output templates, distillation workflow, and quality standards for evidence-driven research
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nWave-ai/nWave☆ 6222026年9月16日 更新
Critique dimensions and scoring for research document reviews
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nWave-ai/nWave☆ 6222026年9月16日 更新
Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements
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nWave-ai/nWave☆ 6222026年9月16日 更新
Gathers knowledge from web and files, cross-references across multiple sources, and produces cited research documents. Use when investigating technologies, patterns, or decisions that need evidence backing.
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nWave-ai/nWave☆ 6222026年9月16日 更新
Tool safety protocols, adversarial output validation, error recovery patterns, and I/O contracts for research operations
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nWave-ai/nWave☆ 6222026年9月16日 更新