Layer Index

Operational Steps

1. 确认输入参数完整
2. 执行核心操作（参考本目录下的 scripts/ 或 references/）
3. 验证输出符合契约
4. 保存结果并报告

Pitfalls

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Verification

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1. 2. 3.

Core Research Stack — 核心科研栈

Purpose

Navigation index for the core research stack: 7 cognitive atoms, paper pipeline, research methodology, and AI/ML tools.

Skills in this Layer (88 total)

• academic-diagram: Directory index for academic-diagram: academic-diagram
• adhd-eye-tracking-review: Directory index for adhd-eye-tracking-review: adhd-eye-tracking-review
• akne-knowledge-manager: AKNE 知识管理系统的双向整合审计、Synthos-桥接诊断、知识流分析、内容级审计。与 akne-maintenance 不同，专注两系统间的连接质量及知识内容质量而非内部运维。
• akne-maintenance: 维护个人知识库系统AKNE — 图谱诊断、修复、向量填充、源文件覆盖、Wiki清理、自动进化守护。覆盖AKNE仓库的完整运维生命周期。
• architecture-diagram: Directory index for architecture-diagram: architecture-diagram
• argument-expression: Directory index for argument-expression: argument-expression
• arxiv: arXiv论文搜索 — 按关键词/作者/类别/ID检索。支持Tor SOCKS代理访问。
• association-discovery: Directory index for association-discovery: association-discovery
• audiocraft: Comprehensive guide to using Meta's AudioCraft for text-to-music and text-to-audio generation with MusicGen, AudioGen, and EnCodec.
• autonomous-execution-threshold: ≥80%置信度 = 闭嘴执行。 不输出推测文案、不给选项、不喊"开始自主执行"口号。用户看到的是执行结果，不是选择题。
• bib-integrity-audit: Audit .bib reference files across a paper library for:
• biomechanical-regulation-ode: Class-level skill for building computational dynamical models of physiological regulation systems using 2-ODE systems with PINN training. Covers model formulation, bifurcation analysis, Sobol sensitivity, and ablation studies.
• biorxiv: Directory index for biorxiv: biorxiv
• bppv-expert: Structured BPPV (Benign Paroxysmal Positional Vertigo) medical knowledge version: 1.0.0 extracted from AKNE knowledge graph. Covers diagnosis techniques (Dix-Hallpike, supine head flexion test), repositioning maneuvers (Epley, Gufoni, Semont, Barbecue, roll-over), canalith conversion mechanisms, 3D biomechanical simulation, and clinical decision workflows. Source: AKNE wiki (126 nodes, 137 edges, proven correctness via falsification testing).
• citation-bib-crossref: Scan paper directories for mismatches between \\cite{key} calls in .tex files and @type{key} entries in .bib files. Produces D8 (bib count) and D10a (match percentage) metrics, plus orphan/zombie classification.
• citation-integrity-fix: ```python
• cognitive-atom-architecture: Methodology for transforming operational skill sets into independent cognitive atoms with strict DAG dependencies, input/output contracts, and Synthos framework alignment. v4.0.0 syncretic framework: Eastern ontology (格物通理/取象通变/天人合一) + Western epistemology (经权度信/墨证求真/庄周观模) + 熵减律·生生之谓易 (ultimate purpose) + 大道至简 (cross-cutting razor).
• comfyui: Directory index for comfyui: comfyui
• competition-submission: End-to-end preparation of AI/tech/innovation competition submissions. Extract requirements, map to scoring criteria, generate documents, produce submission checklist. Covers medical AI, tech innovation, academic conferences, Chinese government grants.
• conversation-to-memory: ⚡ P0 辅助技能。从会话中提取高价值信息，在2,200字符限制内最大化记忆ROI。动灵记忆三问(生长方向?框架维度?发酵潜力?)+宪法护栏(记忆不能覆写CONSTITUTION)+凝练压缩策略。防记忆膨胀同时保留高信号事实。每条记忆标注生长方向和发酵潜力。
• crispdm-helix-experiment: CRISP-DM Helix methodology — strict CV-fold-isolated preprocessing for clinical ML experiments on public datasets. Generates real, traceable L0.5-compliant data.
• data-driven-hypothesis: 从公开数据出发→数据探索→文献调研→发现gap→提出可验证假设。与"先有假设再找数据"相反，适合公开数据集方向探索。
• dataset-discovery: | Platform | REST API | Scraping | Auth Required | Notes |
• dspy: Use DSPy when you need to:
• emerging-field-landscape-scan: Skill: emerging-field-landscape-scan
• evolution: ⚡ P0 自进化引擎。Synthos evolution engine v2.20 — 四态决策+硬收敛+GEPA反射分析+自动基准+Pareto优化+外部吸收+教训学习+黄金验证+自扩关键词+漂移检测+渐进披露+Git即记忆。Hooks注入+置信度评分+并行Agent审计+会话上下文注入+Prompt Snippets。
• experiment-recipes: ML训练配方与预设——架构选择、训练循环、优化器、调度器、混合精度、内存优化、调试。 提炼自实战经验，非外部代码搬运。每个配方记录原理而非逐行代码。
• falsification-validation: Systematic approach to validating AI agent skills through falsification
• golden-test-methodology: Methodology for creating, maintaining, and evaluating golden test suites version: 1.0.0 across all skills. Defines: three-file golden structure (GOLDEN_SET.md + cases/ + expected/), weighted verification criteria, coverage scoring, and DIAGNOSE integration. Covers the systematic gap where golden coverage is the weakest dimension in a multi-skill system.
• gradient-alignment-loss: Skill: gradient-alignment-loss
• hcs-3wt-breast-cancer-diagnosis: HCS-3WT (Hybrid Cascade-Stacking Three-Way Triage) breast cancer diagnostic
• healthcare-dataset-discovery: Public healthcare dataset discovery — known accessible sources, dead sources, and API patterns for medical AI research.
• huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.
• hypothesis-generation: Directory index for hypothesis-generation: hypothesis-generation
• inference: Directory index for inference — mlops/inference 模型推理服务与优化
• journal-selection-medical-ai: Systematic methodology for evaluating and ranking SCI journals as publication
• kg-bridge: Knowledge Graph — Agent Bridge. 将大型知识图谱接入 Agent 记忆层的方法论，覆盖查询分层、环境隔离、语义搜索增强、脚本化接口。
• knowledge-acquisition: 多源学术论文检索：Semantic Scholar / PubMed / Crossref / OpenAlex / arXiv / bioRxiv。
• knowledge-base-audit: Audit and maintain personal knowledge management systems (AKNE, NotebookLM,
• knowledge-extraction: Directory index for knowledge-extraction: knowledge-extraction
• latex-output: Directory index for latex-output: latex-output
• literature-monitor: Directory index for literature-monitor: literature-monitor
• llama-cpp: Use this skill for local GGUF inference, quant selection, or Hugging Face repo discovery for llama.cpp.
• metacognition: 元认知 — 自主执行阈值、记忆增强、记忆优化系统。
• models: Directory index for models — mlops/models 模型架构
• nano-pdf: Edit PDFs using natural-language instructions. Point it at a page and describe what to change.
• nature-paper2ppt: Nature-style Chinese PPTX from academic papers — argument-driven slide
• nsfc-grant-audit: Directory index for nsfc-grant-audit: nsfc-grant-audit
• obliteratus: 9 CLI methods, 28 analysis modules, 116 model presets across 5 compute tiers, tournament evaluation, and telemetry-driven recommendations.
• ode-simulation-tuning: When building 2-ODE computational models for SCI papers, the simulation rarely passes all quality gates on first run. Metrics that commonly fail: R² (needs smooth fit), AUC (needs proper distribution comparison), ablation (needs dominant coupling), accuracy (needs clean transitions). This skill captures the systematic tuning methodology used across papers 90–140+.
• openalex: Directory index for openalex: openalex
• outlines: Use Outlines when you need to:
• paper-citation-health: Scan all papers in outputs/papers/ for citation bibliographic health metrics D8 (bib entries) and D10a (cite-to-bib match %).
• paper-cron-scan: Cron job 不是完整的论文管线执行，而是轻量级扫描：验证白空间稳定、发现新竞争、推进管线状态。
• paper-pipeline: 主skill | SCI论文全流程编排器。v3.18.10新增Trap#42跨项目参考文献污染检测（Synthos Paper ID后缀/占位符键名/空条目/Prose提及无cite）。v3.18.9新增Trap#41 paper-queue.json幽灵条目逆方向。v3.18.5-8: D10a批量扫描+natbib盲区+注释过滤+路由修复。v3.18: Track A晋升协议。v3.16: 队列自愈+ABSOLUTE WHITE独立验证。v3.15: 轨道B四步工作流。
• paper-quality-deep-review: 论文质量深度审查引擎 — 从文献下载→内容分析→研究空白验证→科学假设评估→解决方法评估→文献引用质量评分→综合评分。
• paper-queue-audit: Directory index for paper-queue-audit: paper-queue-audit
• paper-references-scanning: Scan paper library for citation health: D8 (bib entry count), D10a (cite-to-bib match rate), orphans, zombies. Class of tasks: LaTeX reference integrity auditing.
• patent-disclosure: 该技能以Synthos仓库为主版本。Hermes镜像为查找索引，执行时请加载Synthos路径版本。
• pdf-download-racing: 并行竞速PDF下载引擎 — curl_cffi TLS指纹绕过 + Sci-Hub域轮换 + LibGen + MedData。依赖 tools/paper-manager/src/。
• pdf-to-md-notebooklm: PDF→Markdown→NotebookLM 全流程管线。支持批量上传、自动类型检测、大文件处理。
• political-proposal: 参政议政提案全流程(民进/政协/人大) — 三段式: 基本情况→问题→对策。
• project-experience-distillation: ⚡ 最高优先级技能。From project experience to reusable skill — extract workflow patterns, design principles, and pitfalls from completed project work, abstract them into general form, and formalize as SKILL.md. Also: philosophical implementation gap analysis to drive mechanism-level improvements. The reflexive learning engine of Synthos: self-evolution through self-observation.
• pubmed: Deep PubMed/MEDLINE search via NCBI E-utilities — query construction, MeSH terms, batch retrieval, clinical query refinement.
• quality: 质量保障 — 伪证验证、黄金测试、SCI论文质量评审。
• quality-score-assignment: Paper satisfies current_step in steps_completed AND len(steps_completed) >= 8.
• research: 直接调用子类别/技能名称即可。例如：arxiv、bib-integrity-audit、research-ideation。
• research-ideation: 研究创意发散与认知引擎（RIF+CCF）。三层架构：Layer 1（10操作框架）→ 产出研究方向候选； Layer 2（8认知引擎）→
• research-paper-search: 主skill | 多源论文检索+全文下载编排器。入口：Semantic Scholar (API Key), PubMed, OpenAlex, arXiv (Tor), Crossref。调用子skill: arxiv, pubmed, openalex。
• research-skill-audit: Audit and enhance research skill coverage. Process for identifying gaps, testing existing skills, and creating/enhancing missing capabilities.
• researcher-portrait: Directory index for researcher-portrait: researcher-portrait
• scc-bppv-kinematics: Skill: scc-bppv-kinematics
• sci-paper-quality-review: Directory index for sci-paper-quality-review: sci-paper-quality-review
• sci-paper-standard-structure: Directory index for sci-paper-standard-structure: sci-paper-standard-structure
• scientific-database-lookup: Directory index for scientific-database-lookup: scientific-database-lookup
• segment-anything: Comprehensive guide to using Meta AI's Segment Anything Model for zero-shot image segmentation.
• skill-absorption: 双循环进化：内部反思(P0) + 外部吸收(P1)。Cross-project absorption methodology — multi-round cross-project comparison, active project tracking, self-expanding keyword discovery. 动灵驱动吸收(Entelechy-Driven Absorption v4.3).
• skill-integrity-audit: | 概念 | 文言 | 义 |
• synthos: >
• synthos-akne-bridge: Synthos 与 AKNE 之间双向桥接 — 论文目录规范化、技能连接、逆向边创建、Wiki 清理、自动守护重启、内容摘要注入、向量化补全。与 akne-maintenance（内部运维）和 akne-knowledge-manager（审计诊断）不同，本技能管具体的桥接操作。
• system-bridging: 跨系统连接模式 — 两个独立系统（知识图谱/论文管线/技能库/监控系统）之间的双向桥接。覆盖连接协议、数据注入、反向查询、同步守护、重叠检测。
• systematic-review: 系统综述与Meta分析工作流助手 — PRISMA流程、搜索策略设计、研究选择、质量评估、数据提取和综合支持。
• task-router: Synthos系统入口。路由用户查询到正确的认知原子链或执行模式。 四模式：标准链 / 探索循环 / 研究双循环 / 并行执行。 Agent-native执行，纯skill驱动零Python。
• training: Directory index for training — mlops/training 模型训练与微调
• v32-multi-direction-scan: Every cron run of autonomous-core-researcher after v31 API fix. Standardized pattern for scanning 5 rotation + 5 new directions per run.
• viewpoint-verification: Directory index for viewpoint-verification: viewpoint-verification
• vllm: Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
• writing: 写作辅助 — 引用完整性修复、LaTeX输出、政治提案、标准论文结构。

IO_CONTRACT

• input: layer: str, query: str, context: dict — Layer name, search query, and context
• output: skill_list: list[dict] — Filtered list of skills matching the query

验证清单 · VERIFICATION

• 核心层导航索引是否准确映射全部 88 个技能（7 认知原子 + 论文流水线 + 研究方法 + AI/ML 工具），无遗漏或重复条目
• 输入参数 layer、query、context 是否完整且符合 IO_CONTRACT；执行核心操作前是否已参考本目录下 scripts/ 或 references/ 确保操作依据准确（LAYE-002）
• 输出 skill_list: list[dict] 结构是否符合契约，结果是否已保存并报告以闭环质量保障（LAYE-003）
• 认知原子架构是否遵循严格 DAG 依赖及输入/输出契约，方法论基础是否融合东西方认识论（如格物通理/墨证求真）（LAYE-004）
• 置信度 ≥80% 时是否执行「闭嘴执行」策略，仅输出执行结果而非推测文案或选项，避免干扰用户决策（LAYE-005）
• 记忆提取是否在字符限制内最大化记忆 ROI，每条记忆是否标注生长方向与发酵潜力，防止记忆膨胀（LAYE-006）
• 大型知识图谱接入时是否实施查询分层、环境隔离及语义搜索增强，通过脚本化接口完成 KG-bridge 高效记忆层集成（LAYE-007）

约束规则 · RULES

1. 输入约束: 参数类型、范围、格式必须校验
2. 输出约束: 返回值结构、编码、命名必须一致
3. 异常约束: 错误信息必须包含上下文和恢复建议
4. 安全约束: 不执行未验证的任意代码，不暴露内部状态

违反规则的操作视为不安全，必须拒绝或隔离。

每项验证必须可执行、可记录、可复现。验证失败时记录原因和修复。

对应原则：P3（人机分层 — 路由器负责路由，原子负责执行）

Layer Index---

(P032 去重: 以下为合并前第二份中的 1 行独有内容, 保留以防丢失)

Layer Index

Genes (策略基因)

紧凑策略表示。条件→策略。需要深度时参考完整文档。

• [LAYE-008] 当系统包含大量技能（如88个）时 → 建立分层导航索引（Layer Index）以映射认知原子、论文流水线及工具链，实现快速检索与定位。
• [LAYE-009] 当执行核心操作前 → 必须确认输入参数完整，并参考目录下的 scripts/ 或 references/ 以确保操作依据准确。
• [LAYE-010] 当操作执行完毕后 → 验证输出是否符合契约（Contract），并保存结果进行报告，以闭环质量保障。
• [LAYE-011] 当构建认知原子架构时 → 采用严格 DAG 依赖关系及输入/输出契约，融合东西方认识论（如格物通理与墨证求真）以确立方法论基础。
• [LAYE-012] 当置信度达到 ≥80% 时 → 执行“闭嘴执行”策略，直接输出执行结果而非推测文案或选项，避免干扰用户决策。
• [LAYE-013] 当进行记忆提取与管理时 → 在字符限制内最大化记忆 ROI，通过标注生长方向和发酵潜力来防止记忆膨胀并保留高信号事实。
• [LAYE-014] 当处理大型知识图谱接入 Agent 时 → 实施查询分层、环境隔离及语义搜索增强，通过脚本化接口实现 KG-bridge 的高效记忆层集成。