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data-talk
data-talk contient 19 skills collectées depuis wallfacers, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Use when the user asks for a chart, KPI, trend, report, or multi-widget dashboard. Triggers on phrases like 图表/趋势图/可视化/报表/仪表盘/大屏/多图组合 and chart/visualization/dashboard/KPI/multi-widget/ECharts/grid layout. Covers the inline `chart` fenced code block (default single-chart path), `chart:<artifactId>` for SQL-derived charts, and dashboard schema v1 plus incremental `ui_patch` edits for persistent multi-widget layouts.
Use when an LLM agent edits workbench tabs (query_editor, artifact_preview, er_inspector, er_designer, future report_designer) and encounters version conflicts or must guard against concurrent writes. Triggers on 版本冲突 / 409 / version_conflict / anchor_not_found / anchor_ambiguous / baseVersion / expectedVersion / optimistic locking / multi-edit batch / concurrent edit / 乐观锁 / 并发编辑 / 重试. Defines the optimistic-locking contract for workspace-wide, persisted tabs that any session (including parallel agents) may have mutated since your last read, plus mandatory recovery steps on conflict.
Use when invoking the four UI tools — `datatalk_ui_find` / `datatalk_ui_read` / `datatalk_ui_patch` / `datatalk_ui_exec` — to discover, inspect, edit, or execute actions on stage tabs (workspace / query_editor / er_inspector / er_designer). Triggers on `ui_find` / `ui_read` / `ui_patch` / `ui_exec` / `apply_text_edits` / `set_context` / `操作 UI` / `编辑 tab` / `查找 tab` / `读取 tab 状态` / `修改 SQL 编辑器`. Defines parameter shapes, required fields per action, top-level `object`/`target`/`mode`/`action`/`params` semantics, and the post-edit re-read verification rule.
Premium industrial dashboards from v3 JSON. Use for dashboards, KPI boards, monitoring screens, ops cockpits, big-screen displays, or any multi-metric data visualization. The backend Bezel compiler turns JSON into HTML deterministically — no AI-generated HTML.
企业级汇报文档生成(业务月报、问题复盘、季度总结、事件postmortem)。 与 bezel skill 的边界:bezel 做实时大屏 dashboard(深色科技风、单源 widget、轮询刷新); ledger 做冻结快照报告(白底衬线印刷品风、跨源叙事、PDF 邮件转发与打印归档)。 二者**不可互相替代**:用户说"做大屏"用 bezel,用户说"做汇报/周报/月报/复盘"用 ledger。
Use when the user asks to query, mutate, or change schema against a SQL connection. SELECT/INSERT/UPDATE/CREATE/ALTER...ADD run via `datatalk_execute_sql`; DELETE requires `confirmationId` confirm; destructive DDL (DROP/TRUNCATE/ALTER...DROP/GRANT/REVOKE) returns `redirect_to_editor`. Triggers on 查询/统计/分析/读表/取数/插入/更新/删除/建表/改表/count/select/insert/update/delete/create/alter/drop/aggregate/group by/trend/top N/explore schema/describe table. Covers execute_sql contract, DELETE confirm, DDL redirect, read_schema discovery/describe, and table-not-found probe.
Use when the user mentions a specific database product, asks about supported data source types, picks a connection kind, or asks why a feature (ER / diagnostics / mutation) is unavailable on a given dialect. Triggers on MySQL / PostgreSQL / Oracle / SQL Server / SQLite / DuckDB / ClickHouse / TiDB / MariaDB / OceanBase / StarRocks / Apache Doris / Trino / Presto / Dameng / Apache Hive / GaussDB / 方言 / dialect / 数据库类型 / 数据源类型 / 连接类型. Covers per-dialect connection kind, default port, JDBC driver, schema visibility, SQL splitter family, risk-tier highlights, and ER / diagnostics support status.
Routes uploaded files to appropriate actions based on pre-analysis summary and user intent. Activated when user message contains a file_upload part.
Collect external data via Python/Node.js scripts and write into SQL connections. 数据采集脚本、爬虫脚本、API 数据拉取、抓取网页数据、script runner、Python script、Node.js script、data scraping、web scraping、data fetching.
Use when the user manages saved data source connections or switches the session data context (创建连接 / 测试连接 / 编辑连接 / 选择连接 / 切换数据库 / 切换 schema / use xxx / 数据上下文 / connection / data context / connectionId / confirmable mutation / two-phase confirm / terminate session / optimize table). Owns the 6 session-data-context tools, the 3 connection-lifecycle tools, the confirmable mutation two-phase protocol (`confirm=true` + `confirmationToken`), plus `datatalk_terminate_session` and `datatalk_optimize_table`.
Use when the user asks about ER diagrams, schema visualisation, or schema design / fork / apply. Triggers on ER 图 / ER 设计器 / 实体关系 / 看表关系 / 设计表结构 / fork to designer / generate DDL / ER inspector / ER designer / draw ER / annotate relation. Covers the two ER tab types — er_inspector (read-only ER Diagram Viewer with annotation overlay) and er_designer (independent schema draft producing DDL) — plus dialect support (MySQL/PostgreSQL/H2/MariaDB live; SQLite CREATE-only; DuckDB/ClickHouse/Doris/StarRocks/Oracle/SQL Server unsupported) and the rule that designer DDL is never auto-applied.
Use when a SQL run fails or a performance question arrives. Triggers on SQL 报错 / 表不存在 / 列不存在 / 多候选 / 性能分析 / EXPLAIN / 索引建议 / 锁等待 / 慢查询 / 连接池 / 表空间 / SQL execution failed / table not found / Unknown column / ambiguous candidates / Select a database first / slow query / index hint / lock blocking / pool full / disk usage. Owns the three SQL-failure diagnostic classes (syntax, object-not-found incl. cross-DB probe, ambiguous candidates) and the five diagnostic tools `datatalk_explain_query` / `datatalk_index_hints` / `datatalk_lock_info` / `datatalk_pool_status` / `datatalk_table_space`.
Use when the AI is about to write SQL touching tables it has not yet read — multi-table JOIN / cross-table aggregation / first-time operation on an unfamiliar table — OR when the user's keyword does not yet map to a known table name. Triggers on 分析销售/统计/探索/不知道表名/where is the table for X/which table stores/汇总数据/give me trend of. Defines the Pre-Action Exploration Protocol: ordering get_data_context → schema_search → read_schema → execute_sql, budget 3 misses → question tool.
Use when the user wants to browse table rows, inspect sample data, run a simple table preview or row count, write SQL, open a SQL editor, or execute SQL in the editor. Triggers on SQL 编辑器/查询编辑器/打开 SQL/写 SQL/跑 SQL/查表/看表数据/open query editor/open SQL/write SQL/run query/edit SQL/show rows from. Covers the full query_editor lifecycle (open → set_context → patch /content or apply_text_edits → run_sql → focus), the boundSessionId / source / useSessionContext context model, and the 5 Query Editor Rules.
Use when producing files, deliverables, or large tool outputs in a DataTalk session — covers artifact lifecycle (temporary vs archive candidate), `datatalk_archive_artifact` / `datatalk_supersede_artifact` / `datatalk_pin_artifact` tools, and the `saved file path` continuation protocol for oversized responses. Triggers on 工件 / 产物 / 归档 / 落盘 / saved file path / supersede / pin artifact / large output / archive artifact / 链接旧产物 / 替换工件.
Use when the user asks for a business metric, uses business terms ("销售额" / "GMV" / "客单价" / "复购率" / 自然语言度量名), asks to define/lookup semantic model entities/dimensions/measures/metrics, or asks to record a verified query. Covers 6 Actions (semantic_lookup / verified_query_find / verified_query_record / semantic_propose_change / literal_mapping_add / skill_create), L0-L3 Verified Query routing, when to trigger propose_change vs record verified query. 当用户询问业务指标、使用业务术语、或需要查询/定义语义模型时使用。
Create a new business domain Semantic Model skill (YAML) for DataTalk. Triggered when the user asks to define business metrics, create a semantic model for a new domain, or build a skill for a specific business area. 当用户要求为业务域创建语义模型、定义业务指标、或创建新技能时使用。forked_from: anthropics/skills@<upstream-sha-pending>
Tab 生命周期、复用、持久化与搜索策略。触发词:复用 tab / 新开 tab / 当前编辑器 / 上一条 SQL / 继续编辑 / library vs workset / tab reuse / continuation / search tabs / locate text / inWorkset / archive tab / focus tab。指导何时复用 query_editor、何时新开 tab、library 与 workset 的区别、跨重启持久化、以及 ui_find 三动词(list/search/read)组合策略。
A skill for unit testing the SkillResourceSyncer