145 tools: 106 deterministic engines (stats, survival, bioinfo, primers) + 39 AI writers.
Scored across 108 tools
Despite generally rich descriptions, several clusters are near-duplicates: toxicity_predict vs toxicology_assess (both hERG/DILI risk), kaplan_meier vs survival_cox vs animal_survival_km (all KM/log-rank), go_kegg_enrichment vs protein_enrichment vs metabolite_pathway, sample_size_calculator vs animal_sample_size, and tumor_volume_curve vs tumor_growth_inhibition. Overlap also exists between stats_toolbox (97 bundled tests) and a dozen dedicated statistics tools. An agent must read aliases and caveats carefully to avoid misselection.
Nearly all names are snake_case and most carry a domain prefix (animal_, scrna_, metabolite_, protein_, pk_, citation_, dataset_), which gives a predictable grouping. Minor deviations exist: sanyu_job_status / sanyu_list_actions are platform-infrastructure names, and some tools use noun_noun (kaplan_meier, stats_toolbox, dna_translate) instead of verb_noun. No camelCase mixing, so the set remains readable.
108 tools is an extreme surface for a single server and far beyond what an agent can reliably choose from; it is really a bundle of many sub-products (statistics, omics pipelines, animal experiments, clinical pharmacology, writing aids). The presence of sanyu_list_actions as a catalogue is a partial mitigation but does not fix the scale problem. Many narrow single-purpose tools (e.g. dunn_posthoc, tukey_hsd, species_dose_convert) could be folded into the toolbox entry point.
Coverage across statistics, omics analysis, animal/in-vivo pharmacology, clinical epidemiology, literature/evidence handling, and manuscript reporting aids is unusually broad, with CRUD-like lifecycle for jobs via sanyu_job_status. Minor gaps remain: authoring/editing workflows are only implied (generation tools like topic_generate are referenced by sanyu_job_status but not listed), and there is no generic data upload/export or result-retrieval tool. Agents can work around these, so the surface is largely complete.
Animal dose & injection volume / 动物给药量计算 | USE WHEN: compute the dose (mg) and injection volume (mL) for an animal from body weight and mg/kg | ALIASES: 动物给药量, 给药体积, 按体重给药, dose volume, mg/kg, 注射体积, 灌胃体积 | RETURNS: 给药量与体积
Inputs: dose_mg_per_kg (required), animal_weight_g (required).
Animal randomization / 动物随机分组 | USE WHEN: randomly assign animals to groups as required by ARRIVE | ALIASES: 动物随机分组, animal randomization, 分组表, 动物分组 | RETURNS: 分组表
Inputs: n_total (required), seed, groups, method.
Animal sample size (3R) / 动物实验样本量 | USE WHEN: how many animals per group are needed (power-based, ARRIVE/3R wording) | ALIASES: 动物样本量, 动物要多少只, 每组几只, animal sample size, 3R, power animals | RETURNS: 每组动物数
Inputs: effect_size (required), alpha, power, groups.
Animal survival analysis / 动物生存分析 | USE WHEN: Kaplan-Meier and log-rank on animal death/survival times | ALIASES: 动物生存分析, 生存曲线, log-rank, animal survival, KM, 死亡时间 | RETURNS: KM 曲线与 log-rank
Inputs: ctrl_times (required), ctrl_events (required), treat_times (required), treat_events (required).
ARRIVE 2.0 checklist / ARRIVE 2.0 检查 | USE WHEN: check an animal experiment against the ARRIVE 2.0 reporting guideline | ALIASES: ARRIVE, 动物实验规范, 动物伦理报告, animal reporting, ARRIVE 2.0 | RETURNS: ARRIVE 条目核对
Inputs: no named parameters.
ATAC-seq differential accessibility / ATAC 差异可及性 | USE WHEN: differential open regions from ATAC-seq counts | ALIASES: ATAC, 差异可及性, 染色质开放, differential accessibility, peak差异 | RETURNS: 差异 peak
Inputs: data_json (required).
Bioequivalence (BE) / 生物等效性评价 | USE WHEN: compare test vs reference AUC/Cmax and judge 80-125% bioequivalence with 90% CI | ALIASES: 生物等效性, BE, AUC Cmax, 90%CI, 等效性判定, bioequivalence | RETURNS: 90%CI 与等效性判定
Inputs: test_auc_list (required), reference_auc_list (required).
Calibration curve (prediction model) / 校准曲线 | USE WHEN: assess calibration of a risk model and get the curve plus Brier score | ALIASES: 校准曲线, 校准度, Brier, calibration, 预测模型校准, 可靠性曲线 | RETURNS: 校准曲线与 Brier 分数
Inputs: labels (required), scores (required), n_bins.
Cell assay calculator / 细胞实验通用计算 | USE WHEN: CCK8 / wound healing / Transwell / colony formation calculations (pick tool_id: cck8, wound-healing, transwell, colony) | ALIASES: CCK8, 划痕实验, Transwell, 克隆形成, 细胞增殖, 迁移实验, cell viability, wound healing | RETURNS: 计算结果
Inputs: tool_id (required), params.
ChIP-seq peak calling / ChIP-seq Peak calling | USE WHEN: call peaks from ChIP-seq reads | ALIASES: ChIP-seq, peak calling, 峰识别, 转录因子结合, ChIP | RETURNS: peak 清单
Inputs: data_json (required).
Citation formatting / 引文格式化 | USE WHEN: reformat references to Vancouver / APA / GB-T 7714 | ALIASES: 参考文献格式, 引文格式, Vancouver, APA, GB/T 7714, citation, 文献格式 | RETURNS: 格式化后的引文
Inputs: references (required), style.
Verify citation authenticity / 引文真实性核验 | USE WHEN: check whether references are fabricated (existence check against the local corpus) | ALIASES: 核验参考文献, 引用是真的吗, 假文献, citation verify, 参考文献真实性, hallucinated reference | RETURNS: 逐条核验结果
Inputs: text (required), topic.
Classification metrics / 分类性能报告 | USE WHEN: full diagnostic performance set: accuracy, sensitivity, specificity, PPV, NPV, F1 | ALIASES: 分类性能, 准确率, 敏感度, 特异度, PPV, NPV, confusion matrix, 诊断指标 | RETURNS: 分类指标全套
Inputs: labels (required), predictions (required), threshold.
Clinical ↔ basic translation bridge / 临床↔基础转化配对 | USE WHEN: from a clinical finding propose mechanistic hypotheses and experiments (or the reverse) | ALIASES: 转化研究, 临床到基础, 机制假说, bench to bedside, Bridge, 实验方案建议 | RETURNS: 转化研究假说与实验方案
Inputs: finding (required), direction.
Molecular cloning design / 克隆方案设计 | USE WHEN: design a plasmid construct: homology arms, primers, assembly strategy | ALIASES: 分子克隆, 构建质粒, 同源臂, cloning, Gibson, 酶切连接, 引物设计克隆 | RETURNS: 克隆方案与引物
Inputs: insert_seq (required), vector_seq (required), method.
CONSORT flow diagram / CONSORT 流程图 | USE WHEN: draw a CONSORT participant flow diagram from screening/randomization/loss counts | ALIASES: CONSORT流程图, 流程图, 入组流程, flow diagram, 筛选失访 | RETURNS: CONSORT 流程图
Inputs: title, screened, randomized, allocated_control, +4 more.
CRF / SDTM validation / CRF 数据校验（SDTM） | USE WHEN: check whether CRF data meets CDISC SDTM conventions before export | ALIASES: CRF校验, SDTM, CDISC, 数据合规, 导出前检查, CRF validate, data standards | RETURNS: 校验结果
Inputs: form_id.
Parse pasted data / infer column types / 数据解析与列类型识别 | USE WHEN: the user pasted a CSV/table blob: get shape, column types, missingness before analysis | ALIASES: 解析数据, 列类型, 粘贴表格, CSV解析, parse data, column types, 数据形状 | RETURNS: 行列数、列类型、缺失情况
Inputs: csv_data.
List data columns / 读取数据列名 | USE WHEN: list the variables in an uploaded data file (do this before Table 1 / modeling so you use real column names) | ALIASES: 列名, 有哪些变量, 字段名, columns, variables, 变量清单, 表头 | RETURNS: 列名与类型
Inputs: file_id (required).
Dataset profile / 数据快速画像 | USE WHEN: first look at a data file: distributions, missingness, outliers, data quality overview | ALIASES: 数据长什么样, 描述统计, 缺失情况, 数据质量, data profile, descriptive, summary stats, EDA | RETURNS: 描述统计与质量概览
Inputs: file_id (required), study_design.
DeLong test (compare two AUCs) / 两条 ROC 的 AUC 比较（DeLong） | USE WHEN: compare two ROC AUCs from the same subjects and test whether the difference is significant | ALIASES: DeLong, 两个AUC比较, 哪个指标更好, AUC差异, compare AUC, 曲线下面积比较 | RETURNS: 两 AUC 及差值 P 值
Inputs: labels (required), scores1 (required), scores2 (required).
Design gate rules / 方案设计闸门规则 | USE WHEN: explain why a design step is blocked, or what the platform requires for each step (hard gates G1/G2/G3) | ALIASES: 方案设计闸门, 为什么不让过, 硬性要求, gate rules, validation rules, why blocked | RETURNS: 每步是否有硬闸门、三道跨步闸门 G1/G2/G3 的原文规则
Inputs: no named parameters.
Design step context / 取某一步的上下文 | USE WHEN: load what the user already answered for a design step (PICO / design type / population) before drafting the next step | ALIASES: 方案设计上下文, 上一步内容, 已经填过的信息, design context, previous step, project context | RETURNS: 该步骤可用的前序上下文（pico / design_type / population / topic）
Inputs: step (required), project_id (required).
Differential expression (limma-style) / 差异表达分析 | USE WHEN: differential genes from an expression matrix (with volcano plot input) | ALIASES: 差异表达, 差异基因, DEG, differential expression, 火山图, 表达矩阵, limma | RETURNS: 差异基因清单
Inputs: group_a, group_b, gene_names, pval_threshold, +1 more.
DNA → protein translation / 序列翻译 | USE WHEN: translate a nucleotide sequence into amino acids in all three frames | ALIASES: 序列翻译, 核酸转蛋白, 翻译, translate, DNA to protein, 氨基酸序列, ORF翻译 | RETURNS: 氨基酸序列
Inputs: sequence (required).
Drug-drug interaction check / 药物相互作用检查 | USE WHEN: can these two drugs be used together? interaction severity and mechanism | ALIASES: 药物相互作用, 能不能一起用, 配伍禁忌, DDI, drug interaction, 相互作用 | RETURNS: 相互作用等级与机制
Inputs: drug_a (required), drug_b (required).
Dunn post-hoc test / 多组非参数两两比较（Dunn） | USE WHEN: pairwise comparisons after Kruskal-Wallis (nonparametric, multiple groups) | ALIASES: Dunn, 非参数两两比较, Kruskal-Wallis后续, post hoc, 多重比较 | RETURNS: 两两比较 P 值
Inputs: groups (required).
Egger's test (publication bias) / Meta 发表偏倚（Egger） | USE WHEN: test publication bias in a meta-analysis and get funnel-plot inputs | ALIASES: Egger, 发表偏倚, 漏斗图, publication bias, meta回归, funnel plot | RETURNS: Egger 检验 P 与截距
Inputs: log_or (required), se_log_or (required).
Evidence follow-up Q&A / 证据追问（多轮） | USE WHEN: multi-turn follow-up on an evidence card (causal judgement) | ALIASES: 证据追问, 继续追问, 证据卡, evidence followup, 因果判断 | RETURNS: 追问答复
Inputs: title (required), question (required), round, abstract.
Structured evidence intake / 文献证据分级录入 | USE WHEN: decompose a paper into a structured evidence card by evidence level (Decision OS) | ALIASES: 证据分级, 证据卡, 文献拆解, evidence level, GRADE, 证据录入 | RETURNS: 结构化证据卡
Inputs: title (required), doi, abstract, literature_type.
Evidence report narrative / 证据报告叙述 | USE WHEN: turn evidence cards into a readable report | ALIASES: 证据报告, 证据综述, evidence report, 证据叙述 | RETURNS: 证据报告正文
Inputs: result (required), lang.
Liver fibrosis staging / 纤维化分期 | USE WHEN: map fibrosis scores to Ishak / METAVIR stage | ALIASES: 纤维化分期, Ishak, METAVIR, 肝纤维化, fibrosis stage, 病理分期 | RETURNS: 分期结论与解读
Inputs: stage, method.
Figure legend writer / 图注生成 | USE WHEN: write a figure legend for a given chart type | ALIASES: 图注, Figure legend, 图片说明, 图例, 写图注 | RETURNS: 图注文本
Inputs: chart_type (required), context.
Flow cytometry clustering / 流式细胞聚类 | USE WHEN: unsupervised clustering of flow cytometry data into cell populations | ALIASES: 流式聚类, 无监督分群, flow clustering, 细胞群, FlowSOM | RETURNS: 细胞群与比例
Inputs: events, grid_size, n_clusters.
Flow cytometry gating / 流式门控分析 | USE WHEN: gating / population percentages from flow cytometry data | ALIASES: 流式门控, 圈门, gating, 阳性比例, flow cytometry | RETURNS: 门控比例
Inputs: events, method, params.
Forest plot / 森林图 | USE WHEN: forest plot from HR/OR/RR with confidence intervals | ALIASES: 森林图, forest plot, HR OR RR, 置信区间图, meta森林图 | RETURNS: 森林图（矢量）
Inputs: data (required), title, x_label.
Gene information lookup / 基因信息检索 | USE WHEN: what a gene does: full name, aliases, function, location | ALIASES: 基因信息, 这个基因是干什么的, gene function, 别名, gene info, 基因全称 | RETURNS: 基因信息
Inputs: query (required).
Gene → pathway → disease network / 基因-通路-疾病网络 | USE WHEN: from a gene list, find pathway / disease / drug associations and build a mechanism network | ALIASES: 基因通路, 机制网络, gene pathway, 疾病关联, 药物靶点, network, 通路疾病 | RETURNS: 通路/疾病/药物关联
Inputs: genes (required).
GEO dataset pipeline / GEO 数据全流程 | USE WHEN: end-to-end on a GEO accession: DEG → enrichment → immune infiltration | ALIASES: GEO, GSE, 数据集分析, GEO编号, geo dataset, public data reanalysis | RETURNS: 差异基因、富集结果
Inputs: geo_id (required), species, pval_cutoff, logfc_cutoff.
Gleason grade group / Gleason 分级分组 | USE WHEN: Gleason score → Grade Group and risk stratum (prostate cancer) | ALIASES: Gleason, 前列腺癌分级, Grade Group, 格里森评分, 前列腺病理 | RETURNS: Grade Group 与风险分层
Inputs: primary_grade (required), secondary_grade (required).
GO / KEGG enrichment / 通路富集（GO/KEGG） | USE WHEN: pathway enrichment for a gene list (GO biological process, KEGG) | ALIASES: 富集分析, GO, KEGG, 通路富集, enrichment, 通路, 功能注释 | RETURNS: 富集通路与 P 值
Inputs: gene_list (required), db_filter, project_id.
IC50 curve fitting / IC50 曲线拟合 | USE WHEN: fit a dose-response curve and report IC50 with 95% CI | ALIASES: IC50, 半数抑制浓度, 剂量效应曲线, dose response, 抑制率拟合, GI50 | RETURNS: IC50 值与 95%CI
Inputs: responses (required), concentrations (required), model, direction.
IHC scoring (H-score / Allred) / IHC 免疫组化评分 | USE WHEN: immunohistochemistry scoring from staining intensity percentages (H-score, Allred, positive rate) | ALIASES: 免疫组化评分, H-score, Allred, IHC, 阳性率, 染色评分, ER PR HER2 | RETURNS: H-score / Allred / 阳性率
Inputs: stain_type (required), intensity_0_pct, intensity_1_pct, intensity_2_pct, +1 more.
IPTW inverse probability weighting / IPTW 逆概率加权 | USE WHEN: propensity-score weighting (ATE/ATT) for observational comparisons | ALIASES: IPTW, 逆概率加权, 倾向评分加权, propensity weighting, 加权后效应, ATE | RETURNS: 权重与加权后效应
Inputs: treatment (required), propensity_scores (required).
Journal recommendation / 智能选刊 V3 | USE WHEN: recommend target journals from title/abstract, in reach / match / safe tiers | ALIASES: 选刊, 投哪个期刊, 期刊推荐, journal, submission target, 冲稳保, 投稿建议 | RETURNS: 候选期刊与三档策略
Inputs: title (required), design, abstract, keywords, +2 more.
Kaplan-Meier curve / Kaplan-Meier 曲线 | USE WHEN: KM curve and median survival only (no multivariable model) | ALIASES: KM曲线, Kaplan-Meier, 中位生存, 生存曲线, 生存率, log-rank | RETURNS: KM 曲线与中位生存
Inputs: times (required), events (required), groups.
Linear mixed model (repeated measures) / 线性混合模型（纵向/重复测量，公式模式） | USE WHEN: same subject measured repeatedly (pre/post, multiple follow-ups): compare trajectories over time, group×time interaction; modern replacement for repeated-measures ANOVA (handles missing, no sphericity assumption) | ALIASES: 混合模型, 重复测量, 纵向数据, LMM, mixed model, 交互作用, 多次随访, 每人测多次, repeated measures | RETURNS: 固定效应系数/SE/Wald z/P/95%CI（按真实变量名，不是 X1/X2）、各项整体检验 omnibus、交互项检验、primary_test、ICC、方差成分、n_subjects/n_obs、组间例数、缺失与收敛告警
Inputs: data (required), formula (required), subject (required), reml, +4 more.
Literature search (1.53M PMC full texts) / 文献检索（站内 153 万篇 PMC） | USE WHEN: search the in-house PMC corpus for literature / evidence / state of the art | ALIASES: 找文献, 文献检索, 检索文献, literature search, PMC, 证据, 研究现状, PubMed替代 | RETURNS: 文献列表（含 PMCID）
Inputs: q (required), limit.
Metabolite heatmap / 代谢组热图 | USE WHEN: clustered heatmap of metabolites | ALIASES: 代谢热图, 聚类热图, heatmap, metabolite heatmap | RETURNS: 聚类热图
Inputs: data_json (required).
Metabolite pathway enrichment / 代谢物通路富集 | USE WHEN: pathway enrichment for differential metabolites | ALIASES: 代谢物通路, 代谢富集, metabolite pathway, KEGG代谢, 差异代谢物 | RETURNS: 代谢通路富集
Inputs: metabolites (required), fdr_threshold.
Metabolite PCA / 代谢组 PCA | USE WHEN: sample separation / outliers in metabolomics (unsupervised) | ALIASES: 代谢组PCA, PCA, 样本分组趋势, 离群, unsupervised, 得分图 | RETURNS: PCA 得分与解释度
Inputs: data_json (required), groups.
Metabolite PLS-DA / 代谢组 PLS-DA | USE WHEN: supervised discrimination and VIP for differential metabolites | ALIASES: PLS-DA, 有监督判别, VIP, 代谢组判别, 判别分析 | RETURNS: PLS-DA 模型与 VIP
Inputs: data_json (required), groups.
Metabolite volcano plot / 代谢组火山图 | USE WHEN: volcano plot of differential metabolites | ALIASES: 代谢火山图, volcano, 差异代谢物火山图 | RETURNS: 火山图
Inputs: data_json (required).
Multiplex IF phenotyping / 多重免疫荧光表型 | USE WHEN: assign cell phenotypes and proportions from multiplex immunofluorescence markers | ALIASES: 多重免疫荧光, mIF, 细胞表型, phenotype, marker组合, 亚群比例 | RETURNS: 细胞亚群表型与比例
Inputs: cd3_pos, cd8_pos, foxp3_pos, pd_l1_pos.
Multi-omics integration / 多组学整合 | USE WHEN: integrate mRNA / protein / metabolite layers and find cross-layer associations | ALIASES: 多组学, 整合分析, multi-omics, 转录组蛋白组代谢组, cross-omics | RETURNS: 多组学关联结果
Inputs: mrna, protein, metabolite, pathway_map.
Nomogram / 列线图 Nomogram | USE WHEN: turn a logistic or Cox model into a nomogram figure for clinical use | ALIASES: 列线图, Nomogram, 评分图, nomogram, 风险评分图 | RETURNS: 列线图 SVG
Inputs: csv_data.
Nuclei segmentation & counting / 细胞核分割与计数 | USE WHEN: cell density / positive rate from a tissue section (nuclei segmentation) | ALIASES: 细胞核分割, 细胞计数, 密度, nuclei count, segmentation, 阳性细胞率 | RETURNS: 分割统计结果
Inputs: stain_type, cell_density, positive_rate.
ORF prediction / ORF 预测 | USE WHEN: find open reading frames in a nucleotide sequence | ALIASES: ORF, 开放阅读框, 找编码区, open reading frame, 翻译起始 | RETURNS: ORF 列表与位置
Inputs: sequence (required).
Organ coefficient / 脏器系数 | USE WHEN: organ weight / body weight ratio (脏器系数) | ALIASES: 脏器系数, 器官系数, organ coefficient, organ index, 脏器重量比 | RETURNS: 脏器系数
Inputs: label, body_weights, organ_weights.
PCR primer design / PCR 引物设计 | USE WHEN: design PCR primer pairs from a DNA sequence or gene (Tm, GC, product size) | ALIASES: 引物设计, PCR引物, primer, 设计引物, 扩增引物, primer pair | RETURNS: 候选引物对与 Tm/GC
Inputs: gene, sequence.
Permutation test / 置换检验 | USE WHEN: exact/permutation test when t-test assumptions fail or n is tiny | ALIASES: 置换检验, 随机化检验, permutation, 精确检验, 小样本非参数, resampling | RETURNS: 置换 P 值
Inputs: group1 (required), group2 (required), n_perm.
PICO refinement / PICO 精炼 | USE WHEN: turn a vague clinical question into a structured PICO (Population / Intervention / Comparator / Outcome) | ALIASES: PICO, 把问题拆开, 研究问题怎么提, refine question, 结构化问题, PICO拆解 | RETURNS: 结构化 PICO
Inputs: pico (required).
Non-compartmental PK (NCA) / NCA 非房室药代分析 | USE WHEN: non-compartmental analysis of concentration-time data: AUC, Cmax, Tmax, t1/2, CL, Vd | ALIASES: NCA, 非房室分析, 药代参数, AUC Cmax T1/2, PK parameters, 血药浓度 | RETURNS: AUC/Cmax/Tmax/T1/2/CL/Vd
Inputs: time_points (required), concentrations (required), dose, dose_unit.
PK/PD assessment / PK/PD 评估 | USE WHEN: pharmacokinetic/pharmacodynamic assessment and dose projection | ALIASES: PK/PD评估, 药代药效, 剂量推算, pkpd assess, 暴露量 | RETURNS: PK/PD 评估结果
Inputs: drug_name (required), pk_params.
PK/PD simulation / PK/PD 模拟 | USE WHEN: simulate concentration-effect time course for a dosing regimen | ALIASES: PK/PD模拟, 给药方案模拟, 浓度时间曲线, simulation, 剂量方案 | RETURNS: 模拟曲线与参数
Inputs: drug_name (required), pd_params, pk_params.
Plasmid map / 质粒图谱 | USE WHEN: draw/describe a plasmid map from a sequence (features, orientation) | ALIASES: 质粒图谱, 载体结构, plasmid map, vector, 质粒构建图 | RETURNS: 质粒图谱
Inputs: sequence (required).
Protein-protein interaction network / 蛋白互作网络 | USE WHEN: PPI network from a protein list, hub identification (STRING) | ALIASES: 蛋白互作, PPI, STRING, hub基因, 互作网络, network | RETURNS: 互作网络与 hub 蛋白
Inputs: protein_list (required), species, confidence_threshold.
Primer Tm & dimers / 引物 Tm 计算 | USE WHEN: Tm, GC% and self/cross dimer check for given primer sequences | ALIASES: Tm, 引物Tm, 退火温度, GC含量, 二聚体, primer dimer, melting temperature | RETURNS: Tm、GC、二聚体
Inputs: sequence (required).
PRISMA flow diagram / PRISMA 流程图 | USE WHEN: PRISMA literature screening flow for systematic reviews / meta-analyses | ALIASES: PRISMA, 文献筛选流程, 系统评价流程图, flow diagram, 检索流程图 | RETURNS: PRISMA 流程图
Inputs: title, records_screened, studies_included, records_identified.
Propensity score matching (PSM) / 倾向性评分匹配 PSM | USE WHEN: match treated and control subjects on baseline covariates (1:1 nearest neighbour within caliper), then report SMD balance | ALIASES: PSM, 倾向性评分, 倾向评分匹配, propensity score, 1:1匹配, 基线可比, 混杂控制, 匹配后均衡 | RETURNS: 匹配后样本与均衡性
Inputs: data, ratio, treatment, covariates.
In-silico protein digestion / 蛋白酶解模拟 | USE WHEN: choose protease and list peptides for mass-spec sample prep | ALIASES: 蛋白酶解, 质谱前处理, 酶解肽段, digest, trypsin, 肽段清单 | RETURNS: 肽段清单
Inputs: sequence (required), enzymes.
Protein enrichment / 蛋白富集分析 | USE WHEN: GO/KEGG enrichment for a protein list | ALIASES: 蛋白富集, protein enrichment, 蛋白GO, 蛋白通路 | RETURNS: 富集通路
Inputs: protein_list (required), species, enrichment_type.
Protein physicochemical properties / 蛋白理化性质 | USE WHEN: molecular weight, pI, GRAVY, instability index etc. from a protein sequence | ALIASES: 蛋白理化性质, 分子量, 等电点, pI, GRAVY, 疏水性, MW, protein properties | RETURNS: MW/pI/GRAVY 等
Inputs: sequence (required), protein_name.
Post-translational modification prediction / 翻译后修饰分析 | USE WHEN: predict phosphorylation / glycosylation and other PTM sites | ALIASES: 翻译后修饰, 磷酸化位点, 糖基化, PTM, phosphorylation, modification sites | RETURNS: 修饰位点预测
Inputs: sequence (required), modifications.
PSI model stability / 模型稳定性 PSI | USE WHEN: population stability index between expected and observed score distributions | ALIASES: PSI, 模型稳定性, 群体稳定性, population stability, 漂移 | RETURNS: PSI 值与稳定性判断
Inputs: expected_probs (required), observed_probs (required), n_bins.
PubMed search / PubMed 检索 | USE WHEN: search PubMed for the latest literature (live NCBI E-utilities) | ALIASES: PubMed, 查pubmed, 最新文献, pubmed检索, NCBI, 最新研究 | RETURNS: PubMed 文献列表
Inputs: q (required), year_start, max_results.
qPCR Bayesian design / 贝叶斯自适应设计（qPCR） | USE WHEN: design a qPCR experiment / digital-twin PCR simulation for a target | ALIASES: qPCR设计, 贝叶斯自适应, digital PCR, 实验设计, target, 扩增效率 | RETURNS: 实验设计方案
Inputs: target (required), constraints.
qPCR 2^-ddCt relative expression / qPCR 相对表达量（2^-ΔΔCt） | USE WHEN: compute dCt, ddCt and 2^-ddCt fold change from target and reference Ct values, with a group test (calibrated on the mean control dCt) | ALIASES: qPCR, 2^-ddCt, 相对表达量, 倍数, dCt, ddCt, fold change, 内参, Ct值, 基因表达 | RETURNS: fc（2^-ΔΔCt 相对倍数，已按对照组 ΔCt 均值校准）、fold_values、p_value、stat_method（welch_ttest_on_dct / student_ttest_on_dct …
Inputs: exp_ct (required), ctrl_ct (required), exp_ref_ct (required), ctrl_ref_ct (required), +2 more.
Randomization / allocation / 随机化分组 | USE WHEN: produce a reproducible randomization list: simple, block, stratified, or minimization, with a fixed seed | ALIASES: 随机分组, 随机数字表, 区组随机, 分层随机, 最小化法, randomization, random allocation, 分组名单, seed | RETURNS: 分组结果表
Inputs: groups (required), n_subjects (required), seed, method, +1 more.
Renal function & dose adjustment / 肾功能剂量调整 | USE WHEN: the user gives age / sex / weight / serum creatinine and asks for creatinine clearance, eGFR, CKD stage, or how to adjust a drug dose in renal impairment (vancomycin, meropenem, metformin, anticoagulants…) | ALIASES: 肾功能剂量, 肌酐清除率, CrCl, eGFR, 肾小球滤过率, 减量, 剂量调整, 肾功能不全, 万古霉素怎么减量, 按肌酐算剂量 | RETURNS: CrCl（Cockcroft-Gault）+ eGFR（CKD-EPI 2021）+ CKD 分期 + 该药的肾剂量分档（含依据与核对提示）
Inputs: age (required), weight_kg (required), sex, crrt, +5 more.
Reporting guideline checklist / 报告规范清单核对 | USE WHEN: check a manuscript against CONSORT / STROBE / PRISMA / TRIPOD / ARRIVE / STARD | ALIASES: 报告规范, CONSORT, STROBE, PRISMA, TRIPOD, STARD, checklist, 投稿前检查, 规范核对 | RETURNS: 逐条核对结果
Inputs: text (required), design_type.
Restriction sites / 酶切位点分析 | USE WHEN: find restriction enzyme sites in a DNA sequence (can it be cut, which enzyme) | ALIASES: 酶切位点, 限制性内切酶, restriction enzyme, 能不能切开, cloning sites | RETURNS: 酶切位点清单
Inputs: sequence (required).
Risk ratio / odds ratio / 相对危险度 RR | USE WHEN: RR, OR and 95% CI from a 2×2 table of counts | ALIASES: 相对危险度, RR, OR, 比值比, 四格表, risk ratio, odds ratio, 95%CI | RETURNS: RR、OR、95%CI
Inputs: exposed_total (required), exposed_events (required), unexposed_total (required), unexposed_events (required).
RNA-seq differential analysis / RNA-seq 差异分析 | USE WHEN: differential genes from RNA-seq count matrix (negative binomial) | ALIASES: RNA-seq, 转录组差异, 差异基因, DESeq, count matrix, RNA测序 | RETURNS: 差异基因清单
Inputs: data_json (required), groups, log2fc, fdr_threshold.
ROC curve & AUC / ROC 曲线与 AUC | USE WHEN: the user has a binary gold standard and predicted scores/probabilities and wants AUC, ROC curve, discrimination, or the best cut-off | ALIASES: ROC, AUC, 曲线下面积, 诊断效能, 最佳阈值, cutoff, discrimination, 敏感度特异度, ROC曲线 | RETURNS: AUC、最优阈值、敏感度特异度
Inputs: labels (required), scores (required).
Sample size & power / 样本量计算（设计口径） | USE WHEN: calculate how many subjects are needed (two means / two proportions / correlation / survival), or solve for power | ALIASES: 样本量, 要做多少例, 需要多少病人, sample size, power calculation, 把握度, 最少例数, n per group | RETURNS: 每组例数与合计
Inputs: sd, alpha, power, effect, +2 more.
Get progress and result of an asynchronous job. 生成类动作（topic_generate / paper_draft_one_click / …）提交后返回 job_id（engine_status=queued），用这个工具轮询：每 3 秒查一次，最多等 300 秒；status=succeeded 取 result，failed 读 error（失败不扣分）。US English: poll a queued generation job until succeeded/failed.
Inputs: job_id (required).
List every tool on this server as a compact catalogue (name / when-to-use / returns / required params / cost). 列出三域医研全部动作摘要。仅在不确定该用哪个工具时调用；已知工具名可直接调用对应工具。
Inputs: no named parameters.
Reproducible SAS/R/Python code / 生成可复现 SAS/R 代码 | USE WHEN: generate the SAS / R / Python code that reproduces a given analysis | ALIASES: SAS代码, R代码, 复现代码, reproducible code, Python代码, 统计代码 | RETURNS: 推荐统计方法与代码
Inputs: design (required), n_groups, outcome_type.
Single-cell type annotation / 单细胞细胞类型注释 | USE WHEN: automatically annotate cell types in single-cell clusters | ALIASES: 细胞类型注释, annotation, 单细胞注释, cell type, 自动注释 | RETURNS: 细胞类型注释
Inputs: data_json (required).
Single-cell clustering / 单细胞分析 | USE WHEN: cluster and embed single-cell data (UMAP) | ALIASES: 单细胞, scRNA, 聚类降维, UMAP, Seurat, single cell | RETURNS: 聚类结果与 UMAP
Inputs: data_json (required), n_pcs, min_genes, max_mito_pct.
Single-cell marker genes / 单细胞 Marker 基因 | USE WHEN: find marker genes per cluster | ALIASES: marker基因, 各群marker, markers, 差异标记, cluster markers | RETURNS: 各群 marker
Inputs: data_json (required).
SHAP single-case explanation / SHAP 单样本解释 | USE WHEN: explain why one patient was predicted high risk (feature contributions) | ALIASES: SHAP, 解释预测, 为什么高风险, 特征贡献, explain prediction, 可解释性 | RETURNS: SHAP 贡献图
Inputs: csv_data, model_type, sample_index.
SMD balance check / SMD 均衡性检查 | USE WHEN: standardized mean differences before/after PSM or IPTW (covariate balance) | ALIASES: SMD, 标准化均数差, 均衡性, balance, 匹配后均衡, 协变量平衡, love plot | RETURNS: 各协变量 SMD 与均衡判断
Inputs: treatment (required), covariates (required).
Species dose conversion / 种属剂量换算 | USE WHEN: convert an animal dose to a human equivalent dose (mg/kg ↔ mg/m², FDA guidance) | ALIASES: 种属换算, 动物剂量换人, 剂量换算, species conversion, HED, mg/m2, 体表面积法 | RETURNS: 换算后剂量与依据
Inputs: source_dose (required), source_species (required), target_species (required).
Statistics toolbox (97 tests) / 统计中心（97 个统计工具统一入口） | USE WHEN: any statistical test not covered by a dedicated tool: Kappa, ICC, Bland-Altman, VIF, PCA, cluster, Friedman, McNemar, runs test, sign test, trend chi-square, meta-analysis pieces — pass tool_id | ALIASES: 统计检验, Kappa, ICC, Bland-Altman, VIF, PCA, 聚类, Friedman, McNemar, 游程 | RETURNS: 该统计工具的完整结果（含统计量、P 值、95%CI、解读）
Inputs: tool_id (required), payload.
Study design advisor / 研究设计向导 | USE WHEN: the user has a research question but does not know which study design to use (RCT / cohort / case-control / cross-sectional / diagnostic accuracy) | ALIASES: 研究设计选哪个, 设计向导, 用什么研究设计, study design, which design, 研究类型, 队列还是病例对照 | RETURNS: 推荐研究设计与理由
Inputs: pico (required), feasibility.
Survival analysis (KM + Cox) / 生存分析（KM/Cox 全流程） | USE WHEN: follow-up time and event data: survival curves, median survival, hazard ratios, log-rank, multivariable Cox | ALIASES: 生存分析, Cox回归, HR, 风险比, log-rank, 中位生存, 随访, 生存率, hazard ratio | RETURNS: 生存曲线、中位生存、HR、log-rank P
Inputs: data (required), time_col, event_col, group_col, +2 more.
Table 1 (baseline characteristics) / 生成 Table 1（基线特征表） | USE WHEN: build the paper's first table: baseline characteristics by group with P values | ALIASES: Table 1, 基线表, 基线特征表, 人口学表, 第一张表, baseline table, characteristics table, 组间比较表 | RETURNS: Table 1 表格 + 可选段落
Inputs: file_id (required), group_variable (required), test_method, generate_paragraph, +1 more.
Subgroup Table 1 / 分组 Table 1（亚组表） | USE WHEN: baseline characteristics split by a subgroup variable (e.g. by sex, by centre) | ALIASES: 亚组基线表, 分层基线表, subgroup table, stratified baseline, 按某变量分层 | RETURNS: 亚组表
Inputs: file_id (required), group_variable (required), subgroup_variable (required), variables_to_include.
Text overlap self-check / 文字重合度自查 | USE WHEN: compare a passage with the user's own previous papers (self-plagiarism check) | ALIASES: 查重, 文字重合度, 重复率, overlap, self plagiarism, 相似文献 | RETURNS: 重合度与相似文献
Inputs: text (required), top_n.
Toxicity prediction (hERG / DILI) / 毒性预测（hERG/DILI） | USE WHEN: cardiac (hERG) and liver (DILI) toxicity risk from a SMILES string | ALIASES: 毒性预测, hERG, DILI, 心脏毒性, 肝毒性, toxicity, SMILES | RETURNS: 毒性风险分级
Inputs: smiles (required), endpoints.
Toxicology assessment / 毒理评估 | USE WHEN: nonclinical toxicology risk: hERG / DILI / genotoxicity, overall risk level | ALIASES: 毒理评估, 毒性风险, 遗传毒, toxicology, nonclinical safety, 安全评价 | RETURNS: 毒性风险分级
Inputs: logP, hERG_IC50_nM, daily_dose_mg, expected_Cmax_nM.
Tukey HSD post-hoc / 多组两两比较（Tukey HSD） | USE WHEN: pairwise comparisons after one-way ANOVA with family-wise error control | ALIASES: Tukey, HSD, ANOVA后续, 两两比较, post hoc, 多重比较 | RETURNS: 两两比较 P 值
Inputs: groups (required).
Tumour growth inhibition (TGI) / 抑瘤率 TGI | USE WHEN: compute TGI (%) from control vs treated tumour volumes, with a group comparison | ALIASES: 抑瘤率, TGI, 肿瘤抑制率, tumour growth inhibition, 抑瘤实验, 药效评价 | RETURNS: TGI 与统计检验
Inputs: ctrl_volumes (required), treat_volumes (required).
Tumour microenvironment / 肿瘤微环境分析 | USE WHEN: assess tumour immune microenvironment from TILs / CD8 / PD-L1 data (typing + prognosis hint) | ALIASES: 肿瘤微环境, TME, 免疫浸润, TIL, PD-L1, CD8, immune microenvironment | RETURNS: 微环境分型与预后提示
Inputs: tils_pct, cd8_count, pd_l1_pos, cancer_type.
Tumour volume & growth curve / 肿瘤体积计算 | USE WHEN: tumour volume from caliper length/width and the growth curve over days | ALIASES: 肿瘤体积, 长短径算体积, 生长曲线, tumor volume, caliper, 生长抑制曲线 | RETURNS: 体积与生长曲线
Inputs: days, widths, lengths, group_name.
Two-way ANOVA / 双因素方差分析 | USE WHEN: two factors: main effects and interaction | ALIASES: 双因素方差分析, two-way ANOVA, 交互作用, 主效应, 两个因素 | RETURNS: 主效应与交互
Inputs: group_a (required), group_b (required), values.
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