752건 · 관련도순
Assigns confidence scores to agent outputs based on multiple factors including source quality, consistency, and reasoning depth. Produces calibrated confidence estimates. Activate on 'confidence score', 'how confident', 'certainty level', 'output confidence', 'reliability score'. NOT for validation (use dag-output-validator) or hallucination detection (use dag-hallucination-detector).
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Implement executable BDI reasoning with explicit negation, paraconsistent revision, trigger-based commitment updates, and abduction. Use for runtime agent semantics and conflicting desires. NOT for purely axiomatic modal logic, black-box planners, or classical logic without operational semantics.
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Develop, challenge, and document Chisel processor microarchitecture designs before implementation. Use when discussing or writing design documents for processor pipelines, queues, issue logic, rename, ROB, LSU, caches, MSHRs, forwarding, wakeup, replay, flush, privilege, exceptions, or other cycle-accurate hardware mechanisms; when converting design conversations into stable Markdown specifications; or when reviewing a proposed Chisel CPU design for correctness, timing, area, verification cost, and cross-document consistency.
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Translate books, documents, AiNiee projects, Unity localization caches, or flat MTool JSON dictionaries end to end on the coding agent itself without the AiNiee app. Use for requests such as "用 agent 翻译这本书", "把 epub 翻译了", "翻译 Unity CSV/cache", "把这个 MTool JSON 翻译了", or "AiNiee-style translation" that need a locked glossary, resumable batches or bounded subagent groups, terminology consistency, source-aware QA, validated cache writeback, and export. For MTool, preserve the left JSON key as immutable source text and write only the right value as translation.
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Assesses the quality and completeness of a genome annotation with BUSCO (conserved single-copy ortholog recovery), OMArk (proteome completeness, consistency, and contamination), CheckM2 (prokaryotic completeness/contamination), and a gene-set sanity panel (gene count, mono-exonic fraction, protein-length distribution, mRNA:gene ratio, coding density). Covers the assembly-BUSCO-vs-proteome-BUSCO diagnostic, what BUSCO-Duplicated really means, why gene count is a vanity metric, and the QC of transferred annotations. Use when judging whether an annotation is good enough to publish or submit, diagnosing a suspect annotation, or comparing annotation completeness across pipelines.
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Comprehensive quality control for CLIP-seq libraries (eCLIP, iCLIP, iCLIP2, PAR-CLIP) covering library complexity (preseq), FRiP, IDR replicate reproducibility, read-distribution metagene, SMInput vs IgG control rationale, rRNA / snoRNA contamination, fragment-length distribution, and ENCODE-compliance thresholds. Use when assessing whether a CLIP library passed, deciding lenient vs stringent peak thresholds, comparing replicates with IDR rescue and self-consistency ratios, or distinguishing failed IP from over-amplified library.
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Build a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.
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Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
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Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm. For QC thresholds, use protein-qc.
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Design and review durable REST, GraphQL, RPC, or event-facing API contracts. Use for public or shared API contracts, endpoint/schema consistency, compatibility, pagination, error semantics, and API documentation. Discovers existing consumers and conventions before recommending a style.
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Cross-consistency review of a drafted spec's diagrams. Verifies that C4 components appear in the dependency graph, class-diagram changes have matching DDL, every AC resolves to a concrete sequence, and the dependency graph is acyclic. Read-only. Run after `/spec-lint` passes and before implementation.
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Generate production-ready manga pages, chapter pages, covers, and panel sequences with strict recurring-character consistency. Use this when the user asks for a manga page, manga scene, chapter page, comic page, storyboard page, or character-consistent page generation. Before generating any page, inspect `img-memory`, create missing character sprites/reference sheets, make those images visible to image generation, then generate the final manga page.
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Multi-angle review of responses before delivery. Audits from 4 perspectives -- factual accuracy, logical consistency, completeness, and safety. Use for high-stakes responses where errors have real consequences.
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Expert-level distributed systems theory covering consistency models, consensus algorithms, fault tolerance, replication, distributed transactions, and the CAP theorem.
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当用户因之前的承诺或表态而感到"必须坚持下去"，或在"明知不对但因说到做到而无法退出"时激活。用于识别承诺如何操控自我认知和行为，并区分机械一致与理性坚持。 不适用于: 纯信息查询、日常惯例性选择、正常的信守承诺行为。
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Use when shaping brand voice — voice attributes, tone-by-context matrix, consistency review. Triggers on 'define our voice', 'why does our copy sound different on every surface'.
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Generate an image from a brief — provider-agnostic blueprint then provider-specific translation, with ref-image/seed reuse for consistency. Use when generating/creating an image.
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Use when a character must stay visually identical across AI video scenes — locks identity tokens (silhouette, palette, wardrobe, prop) in JSON. Triggers 'character lock', 'same character'.
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Audits and realigns UI to match design system standards, spacing, tokens, and patterns. Use when the user mentions consistency, design drift, mismatched styles, tokens, or wants to bring a feature back in line with the system.
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Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.
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Create architecture solution design decisions for AI agent consistency. Use when the user says "lets create architecture" or "create technical architecture" or "create a solution design"
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Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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Manages brand identity, visual design system, and creative quality for MMIND.ai. Generates complete image prompts for Nano Banana Pro (Gemini), enforces the strict 5-color palette, flat-vector SaaS style, and typography standards. Use when user needs graphic prompts, brand consistency checks, visual style guidance, design briefs, or creative QA for any marketing asset.
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