[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-apache-tsfile-cli":3,"mdc--9wfgl5-key":41,"related-org-apache-tsfile-cli":1200,"related-repo-apache-tsfile-cli":1365},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":22,"repoUrl":23,"updatedAt":24,"license":25,"forks":26,"topics":27,"repo":36,"sourceUrl":39,"mdContent":40},"tsfile-cli","inspect and manage Apache TsFiles","Use when you need to inspect, preview, export, OR import an Apache TsFile (.tsfile) from the command line — list devices\u002Ftables, dump schema, read file\u002Fseries metadata, count rows, sample\u002Fpreview rows, or write CSV\u002FTSV into a new .tsfile — via the project's C++ `tsfile-cli` in cpp\u002Ftools.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"apache","Apache Software Foundation","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fapache.png",[12,16,19],{"name":13,"slug":14,"type":15},"Data Engineering","data-engineering","tag",{"name":17,"slug":18,"type":15},"Data Analysis","data-analysis",{"name":20,"slug":21,"type":15},"CLI","cli",193,"https:\u002F\u002Fgithub.com\u002Fapache\u002Ftsfile","2026-08-23T04:00:19.821403",null,97,[28,29,30,31,32,33,34,35],"big-data","cpp","file","iot","java","python","timeseries","tsfile",{"repoUrl":23,"stars":22,"forks":26,"topics":37,"description":38},[28,29,30,31,32,33,34,35],"Apache TsFile","https:\u002F\u002Fgithub.com\u002Fapache\u002Ftsfile\u002Ftree\u002FHEAD\u002Fskills\u002Ftsfile-cli","---\n# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements.  See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership.  The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); you may not use this file except in compliance\n# with the License.  You may obtain a copy of the License at\n#\n#     http:\u002F\u002Fwww.apache.org\u002Flicenses\u002FLICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing,\n# software distributed under the License is distributed on an\n# \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n# KIND, either express or implied.  See the License for the\n# specific language governing permissions and limitations\n# under the License.\nname: tsfile-cli\ndescription: Use when you need to inspect, preview, export, OR import an Apache TsFile (.tsfile) from the command line — list devices\u002Ftables, dump schema, read file\u002Fseries metadata, count rows, sample\u002Fpreview rows, or write CSV\u002FTSV into a new .tsfile — via the project's C++ `tsfile-cli` in cpp\u002Ftools.\n---\n\n# tsfile-cli\n\nSingle pipe-friendly C++ binary to inspect **and** import `.tsfile` (TsFile's analogue of\n`parquet-cli`\u002F`pqrs`). Source `cpp\u002Ftools\u002F`. Read data → stdout, diagnostics → stderr;\n`write` imports CSV\u002FTSV → a new file.\n\n## Scope\n\nUse this skill for command-line builds and operations. For Java, Python, C++,\nor C SDK integration, schema design, and programmatic tree-model writes, load\nthe sibling `tsfile` skill at `..\u002Ftsfile\u002FSKILL.md`.\n\n## Binary\n\n- Name `tsfile-cli` (CMake target `tsfile_cli`). Find: `ls cpp\u002Fbuild\u002F*\u002Fbin\u002Ftsfile-cli`.\n- Build only if missing: `cd cpp && bash build.sh -t=Debug`.\n\n## Read\n\n`tsfile-cli \u003Ccmd> [opts] \u003Cfile.tsfile>` · `tsfile-cli --help | --version | help`\n\n| cmd | output | scans pages |\n|---|---|---|\n| `ls` | device (tree) \u002F table (table) per line | no |\n| `schema` | `target,measurement,datatype,encoding,compression` | no |\n| `meta` | model, device\u002Ftable\u002Fseries counts, time range, size | no |\n| `stats` | per-series `count,start,end,min,max,first,last,sum` | no |\n| `count` | per-series counts + `total` row | no |\n| `head` | first N rows (default 10, `-n`) | yes |\n| `cat` | all matching rows (streamed; `table` format buffers) | yes |\n| `sample` | reservoir sample (default 10, `-n` + `--seed`) | yes |\n\nPrefer no-scan verbs (`ls\u002Fschema\u002Fmeta\u002Fstats\u002Fcount`) — cheap and never hit the page-decode caveat.\n\nTable model + row verbs (`head\u002Fcat\u002Fsample`): without `-t`, only the **first** table is queried. Pass `-t \u003Ctable>` to target a specific one (`count` covers all tables).\n\n```\nopts: -f csv|tsv|json|table  (default TTY→table, pipe→tsv)\n      -d \u003Cdevice> | -t \u003Ctable>   (mutually exclusive)\n      -m a,b,c (projection) · -n N · --offset N · --start \u003Cms> · --end \u003Cms> (inclusive)\n      --tag-filter C OP V · --tag-between C L U · --tag-not-between C L U (table TAG predicates)\n      --seed N · --no-header · --model tree|table (else auto)\napplies: -m → schema\u002Fstats\u002Fcount\u002Fhead\u002Fcat\u002Fsample · -d\u002F-t → row cmds\u002Fschema\u002Fstats\u002Fcount\n         (-d needs tree model, -t needs table model in head\u002Fcat\u002Fsample\u002Fschema) · --offset ∉ sample\n         tag filters → head\u002Fcat\u002Fsample table model; OP=eq|neq|lt|lteq|gt|gteq|regexp|not-regexp\njson=NDJSON (num\u002Fbool bare, else quoted, null→null, NaN\u002FInf→null) · csv=RFC4180 · ts=raw epoch ms\nexit: 0 ok · 1 usage · 2 file open\u002Fcorrupt · 3 query\u002Fruntime\n```\n\nThe aligned `table` format buffers rows. Prefer `csv`, `tsv`, or `json` for\nlarge dumps and pipelines.\n\n```sh\nB=cpp\u002Fbuild\u002FDebug\u002Fbin\u002Ftsfile-cli\n$B meta data.tsfile; $B count -t table1 -f tsv data.tsfile\n$B cat -t table1 --tag-filter device eq dev_1 -m temp -f tsv data.tsfile\n$B cat -m temp --start 1700000000000 -f csv data.tsfile 2>\u002Fdev\u002Fnull | head\n```\n\n## Write\n\n`tsfile-cli write --table \u003Cname> --columns \u003Cspec> -o \u003Cout> [-f csv|tsv] [--no-header] [--header-match] [-v] [\u003Cinput> | -]`\n\nImports rows into a **new table-model** file (overwritten). Input col 0 = timestamp\n(epoch ms, int); remaining cols declared by `--columns` — **no type inference**.\n\n```\nspec  := col (',' col)*\ncol   := name ':' TYPE ':' ('tag' | 'field')          # TYPE + category case-insensitive\nTYPE  ∈ { BOOLEAN, INT32, INT64, FLOAT, DOUBLE, STRING, TEXT, TIMESTAMP, DATE, BLOB }\ninput := file | '-' | omitted                          # '-' or omitted = stdin\n```\n\n- `-o` required (overwritten, must differ from input); `-f` default csv (json\u002Ftable → usage error).\n- header: first line skipped by default · `--no-header` if none · `--header-match` validates\n  header names vs `--columns` (mutually exclusive with `--no-header`).\n- empty cell = null · `--table` is lower-cased · `DATE` cells are `YYYY-MM-DD`, `TIMESTAMP` epoch ms · each column stored with the engine default encoding\u002Fcompression for its type · success **silent**, `-v` → echoes the resolved config + `wrote N rows to \u003Cout>` on stderr.\n- **timestamps must be strictly increasing per device** (device = tag-column values); rows for\n  different tags may interleave\u002Freuse timestamps. Out-of-order input → error with line number.\n- a failed import deletes its partial output (no half-written `.tsfile` left behind).\n- exit: `1` usage (missing `--table`\u002F`--columns`\u002F`-o`, bad spec, dup column, read-only flag) · `2` IO open · `3` row (field-count \u002F type \u002F overflow \u002F timestamp-order \u002F header mismatch).\n\n```sh\nprintf 'time,id1,s1\\n0,dev,0\\n1,dev,10\\n' \\\n  | tsfile-cli write --table t1 --columns \"id1:STRING:tag,s1:INT64:field\" -o out.tsfile -\ntsfile-cli count -f tsv out.tsfile        # -> t1.dev  s1  2\n```\n\nTree-model \u002F JSON \u002F programmatic writes → C++ SDK `cpp\u002Fexamples\u002Fcpp_examples\u002Fdemo_write.cpp`\n(`TsFileTableWriter`\u002F`TsFileWriter` + `Tablet`); Java\u002FPython writers under `java\u002F`, `python\u002F`.\n\n## Caveats\n\n- `head`\u002F`cat`\u002F`sample` decode pages → may abort (`decode_cur_time_page_data`, exit 134) on\n  some aligned files incl. bundled `cpp\u002Fexamples\u002Ftest_cpp.tsfile`. Storage-engine\u002Ffile issue,\n  not a CLI bug; metadata verbs still work. 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Use a well-formed (e.g. self-written) file for rows.",{"type":47,"tag":146,"props":1142,"children":1143},{},[1144,1146,1152,1154,1160],{"type":52,"value":1145},"table-model ",{"type":47,"tag":68,"props":1147,"children":1149},{"className":1148},[],[1150],{"type":52,"value":1151},"target",{"type":52,"value":1153}," is derived from tag bytes → may show non-printable chars in ",{"type":47,"tag":68,"props":1155,"children":1157},{"className":1156},[],[1158],{"type":52,"value":1159},"stats\u002Fcount\u002Fschema",{"type":52,"value":134},{"type":47,"tag":146,"props":1162,"children":1163},{},[1164,1169,1171,1177,1179,1185,1187,1192],{"type":47,"tag":68,"props":1165,"children":1167},{"className":1166},[],[1168],{"type":52,"value":274},{"type":52,"value":1170}," lists all columns; ",{"type":47,"tag":68,"props":1172,"children":1174},{"className":1173},[],[1175],{"type":52,"value":1176},"meta\u002Fstats\u002Fcount",{"type":52,"value":1178}," count only field series → ",{"type":47,"tag":68,"props":1180,"children":1182},{"className":1181},[],[1183],{"type":52,"value":1184},"series_count",{"type":52,"value":1186}," can be\nfewer than ",{"type":47,"tag":68,"props":1188,"children":1190},{"className":1189},[],[1191],{"type":52,"value":274},{"type":52,"value":1193}," rows (not a bug).",{"type":47,"tag":1195,"props":1196,"children":1197},"style",{},[1198],{"type":52,"value":1199},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":1201,"total":1364},[1202,1221,1236,1250,1266,1279,1292,1305,1322,1333,1343,1354],{"slug":1203,"name":1204,"fn":1205,"description":1206,"org":1207,"tags":1208,"stars":1218,"repoUrl":1219,"updatedAt":1220},"computer-use","Computer Use","operate local desktop applications","Use when the user asks to inspect or operate a local desktop application UI, including reading windows, clicking controls, filling forms, using menus, scrolling lists, moving windows, or waiting for dialogs. Trigger for requests such as \"operate this app\", \"do this in TextEdit\u002FCalculator\u002FSettings\", \"look at the current window\", or \"click\u002Ftype\u002Fscroll\"; prefer Browser tools for web pages and non-GUI tools for files or terminal work.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1209,1212,1215],{"name":1210,"slug":1211,"type":15},"Automation","automation",{"name":1213,"slug":1214,"type":15},"Desktop","desktop",{"name":1216,"slug":1217,"type":15},"MCP","mcp",1580,"https:\u002F\u002Fgithub.com\u002Fapache\u002Fmaka","2026-08-20T03:52:55.588112",{"slug":1222,"name":1222,"fn":1223,"description":1224,"org":1225,"tags":1226,"stars":1233,"repoUrl":1234,"updatedAt":1235},"datafusion-python","write Apache DataFusion Python code","Use when the user is writing datafusion-python (Apache DataFusion Python bindings) DataFrame or SQL code. Covers imports, data loading, DataFrame operations, expression building, SQL-to-DataFrame mappings, idiomatic patterns, and common pitfalls.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1227,1228,1230],{"name":17,"slug":18,"type":15},{"name":1229,"slug":33,"type":15},"Python",{"name":1231,"slug":1232,"type":15},"SQL","sql",593,"https:\u002F\u002Fgithub.com\u002Fapache\u002Fdatafusion-python","2026-07-12T08:36:04.957626",{"slug":1237,"name":1237,"fn":1238,"description":1239,"org":1240,"tags":1241,"stars":1247,"repoUrl":1248,"updatedAt":1249},"flink-agents-dev","build and debug Apache Flink agents","Use when building, scaffolding, modifying, debugging, converting, or verifying Apache Flink Agents applications, including Flink Agents YAML, Workflow Agent, ReAct Agent, Actions, Resources, MCP servers, vector stores, runtime skills, Python, or Java. Do not use for ordinary Flink jobs that do not use Flink Agents.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1242,1245,1246],{"name":1243,"slug":1244,"type":15},"Agents","agents",{"name":1210,"slug":1211,"type":15},{"name":1216,"slug":1217,"type":15},421,"https:\u002F\u002Fgithub.com\u002Fapache\u002Fflink-agents","2026-08-07T05:03:37.315408",{"slug":1251,"name":1251,"fn":1252,"description":1253,"org":1254,"tags":1255,"stars":1263,"repoUrl":1264,"updatedAt":1265},"bydbql","generate and execute BanyanDB BydbQL queries","Generate, validate, and optionally execute read-only BanyanDB BydbQL for STREAM, MEASURE, TRACE, and PROPERTY resources. Use when the user asks to query BanyanDB, translate natural language to BydbQL, inspect BanyanDB schema or data, validate BydbQL, or fetch raw BanyanDB records.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1256,1259,1262],{"name":1257,"slug":1258,"type":15},"Analytics","analytics",{"name":1260,"slug":1261,"type":15},"Database","database",{"name":1231,"slug":1232,"type":15},344,"https:\u002F\u002Fgithub.com\u002Fapache\u002Fskywalking-banyandb","2026-07-12T08:31:01.294423",{"slug":1267,"name":1267,"fn":1268,"description":1269,"org":1270,"tags":1271,"stars":1263,"repoUrl":1264,"updatedAt":1278},"compiling","compile and build BanyanDB projects","Compile and build the SkyWalking BanyanDB project. Use when the user asks to compile, build, or generate code for this project.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1272,1275],{"name":1273,"slug":1274,"type":15},"Build","build",{"name":1276,"slug":1277,"type":15},"Engineering","engineering","2026-07-12T08:31:06.373309",{"slug":1280,"name":1280,"fn":1281,"description":1282,"org":1283,"tags":1284,"stars":1263,"repoUrl":1264,"updatedAt":1291},"gh-pull-request","create GitHub pull requests for BanyanDB","Create a GitHub pull request for SkyWalking BanyanDB. Use when the user asks to create a PR, submit changes, or open a pull request.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1285,1288],{"name":1286,"slug":1287,"type":15},"GitHub","github",{"name":1289,"slug":1290,"type":15},"Pull Requests","pull-requests","2026-07-12T08:31:03.792415",{"slug":1293,"name":1293,"fn":1294,"description":1295,"org":1296,"tags":1297,"stars":1263,"repoUrl":1264,"updatedAt":1304},"vendor-update","update Go and Node.js vendor dependencies","Upgrade Go\u002FNode.js vendor dependencies and sync tool versions. Use whenever the user says \"upgrade dependencies\", \"update vendors\", \"vendor update\", \"run vendor-upgrade\", \"bump dependencies\", \"update packages\", or asks to run the `vendor-update` Make target. This skill also checks `scripts\u002Fbuild\u002Fversion.mk` after upgrading to see if any tracked tool versions need updating too, and removes stale binaries from `bin\u002F` when versions change.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1298,1301],{"name":1299,"slug":1300,"type":15},"Go","go",{"name":1302,"slug":1303,"type":15},"Node.js","node-js","2026-07-12T08:31:02.555555",{"slug":1306,"name":1306,"fn":1307,"description":1308,"org":1309,"tags":1310,"stars":1319,"repoUrl":1320,"updatedAt":1321},"cayenne-cgen","generate Cayenne entity Java classes","Use this skill whenever the user wants to (re)generate Cayenne entity Java classes from a DataMap. Trigger on phrases like 'generate Java classes', 'regenerate entities', 'run cgen', 'create the entity classes', 'why is the Artist class missing fields', 'where did the `_Abstract*` classes come from', 'sync the entity classes with the model', or any request to materialize Java from the DataMap. Also trigger as a follow-up after modeling changes (someone added an entity, attribute, or relationship and now the Java side is stale). This skill exclusively uses the `mcp__cayenne__cgen_run` MCP tool — it does NOT use `mvn cayenne:cgen` or the Gradle cgen task.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1311,1314,1316],{"name":1312,"slug":1313,"type":15},"Data Modeling","data-modeling",{"name":1315,"slug":32,"type":15},"Java",{"name":1317,"slug":1318,"type":15},"ORM","orm",343,"https:\u002F\u002Fgithub.com\u002Fapache\u002Fcayenne","2026-08-10T04:19:27.571948",{"slug":1323,"name":1323,"fn":1324,"description":1325,"org":1326,"tags":1327,"stars":1319,"repoUrl":1320,"updatedAt":1332},"cayenne-db-import","import database schema into Cayenne DataMaps","Use this skill when the user wants to import database schema metadata into a Cayenne DataMap — the *model\u002Fmapping only*, not names or Java classes. Trigger on phrases like 'reverse engineer the database', 'import the schema', 'generate a DataMap from my DB', 'add the new tables from the DB into the model', 'import the customer table', 'create entities from these tables', or any request to read database metadata to populate or update a DataMap's XML. This is for *full schema* or *bulk table* import; one-off a-la-carte entity additions belong in the cayenne-modeling skill. IMPORTANT — scope: this imports the mapping ONLY; it does not clean up the Object-layer names or (re)generate Java classes. When the user wants their whole project brought in line with the DB ('sync my project with the database', 'my schema changed, update everything', 'update my entities\u002Fclasses from the DB'), that is the end-to-end `cayenne-full-db-sync` skill, which runs this import and then name cleanup and class generation. To regenerate classes alone use `cayenne-cgen`. The skill runs reverse engineering directly via the `mcp__cayenne__dbimport_run` MCP tool when a DBConnector is already configured; otherwise it opens the CayenneModeler GUI via `mcp__cayenne__open_project` to configure the connection first.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1328,1329,1330,1331],{"name":1260,"slug":1261,"type":15},{"name":1315,"slug":32,"type":15},{"name":1317,"slug":1318,"type":15},{"name":1231,"slug":1232,"type":15},"2026-07-19T05:40:33.655062",{"slug":1334,"name":1334,"fn":1335,"description":1336,"org":1337,"tags":1338,"stars":1319,"repoUrl":1320,"updatedAt":1342},"cayenne-full-db-sync","synchronize Cayenne projects with database","Use this skill when the user wants to bring their WHOLE Cayenne project in line with the database in one shot — the mapping, the Object-layer names, and the generated Java classes together. This is the end-to-end 'sync with the DB' workflow, and it orchestrates three skills in order: `cayenne-db-import` (import schema metadata into the DataMap) → `cayenne-model-naming` (polish the just-imported names) → `cayenne-cgen` (regenerate Java classes). Trigger on holistic phrases like 'sync my project with the database', 'sync with the DB', 'my schema changed, update everything', 'update my entities\u002Fclasses from the database', 'reverse engineer and regenerate the classes', 'import the new tables and rebuild the entities', 'full DB sync', 'bring the model and classes up to date with the DB'. The distinguishing signal is scope: the user wants the whole project (mapping + names + Java code), not just one stage. For the *model\u002Fmapping only* (no name cleanup, no class generation) use `cayenne-db-import`; to (re)generate classes alone use `cayenne-cgen`; to clean names alone use `cayenne-model-naming`. Uses the `mcp__cayenne__dbimport_run` and `mcp__cayenne__cgen_run` MCP tools via the sub-skills; does NOT use Maven or Gradle goals.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1339,1340,1341],{"name":1260,"slug":1261,"type":15},{"name":1315,"slug":32,"type":15},{"name":1317,"slug":1318,"type":15},"2026-07-19T06:03:49.112969",{"slug":1344,"name":1344,"fn":1345,"description":1346,"org":1347,"tags":1348,"stars":1319,"repoUrl":1320,"updatedAt":1353},"cayenne-model-naming","clean up Cayenne object-layer names","Use this skill to clean up Object-layer names in a Cayenne DataMap — ObjEntity, ObjAttribute, and ObjRelationship names, plus DbRelationship names (the first-class unit of relationship cleanup — every FK has one whether or not an ObjRelationship was generated; the ObjRelationship name is synced to it when one exists) — so they read as descriptive, consistent Java. Trigger on phrases like 'clean up the model names', 'fix the entity names', 'these names look ugly', 'make the names descriptive', 'normalize the ObjEntity\u002Fattribute\u002Frelationship names', 'why is this relationship called team1', 'rename entities to be consistent', 'the import produced Gametype instead of GameType'. Invoke it on an explicit user request, or as a manual follow-up after a `cayenne-db-import` to polish the just-imported additions — it is never triggered automatically. IMPORTANT: this is a LIGHT polish pass — CayenneModeler's reverse-engineering already produces good names for the common case; only improve the specific things its deterministic algorithm cannot (run-together names with no separators like `gametype`, meaningless numbered names like `team1` from multiple relationships between two tables, and a common entity prefix that leaks into relationship names like `aaOrders`). Do NOT rewrite names that are already correct. This is Obj-layer naming polish; for structural model edits use `cayenne-modeling`, and for regenerating classes afterward use `cayenne-cgen`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1349,1350,1351,1352],{"name":1312,"slug":1313,"type":15},{"name":1260,"slug":1261,"type":15},{"name":1315,"slug":32,"type":15},{"name":1317,"slug":1318,"type":15},"2026-07-22T05:35:32.342548",{"slug":1355,"name":1355,"fn":1356,"description":1357,"org":1358,"tags":1359,"stars":1319,"repoUrl":1320,"updatedAt":1363},"cayenne-modeler","manage Cayenne projects with CayenneModeler","Use this skill when the user explicitly wants to open CayenneModeler (the GUI) on a Cayenne project, or when the modeling task is inherently visual — reverse engineering (delegated to cayenne-db-import), bulk relationship layout, multi-entity visual refactoring. Trigger on phrases like 'open the Modeler', 'open in CayenneModeler', 'launch the GUI', 'edit visually', 'show me the project in the Modeler'. Do NOT trigger as a fallback for ordinary a-la-carte XML edits — those belong in the cayenne-modeling skill, which is faster and doesn't require the user to context-switch.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1360,1361,1362],{"name":1312,"slug":1313,"type":15},{"name":1315,"slug":32,"type":15},{"name":1317,"slug":1318,"type":15},"2026-07-12T08:32:37.199428",115,{"items":1366,"total":597},[1367,1377],{"slug":35,"name":35,"fn":1368,"description":1369,"org":1370,"tags":1371,"stars":22,"repoUrl":23,"updatedAt":1376},"work with Apache TsFile data formats","Work with Apache TsFile programmatic SDKs and file-format concepts in Java, Python, C++, or C. Use for reading, writing, querying, schema or data-model design, encoding\u002Fcompression decisions, performance analysis, API compatibility, and cross-language TsFile integration. Route shell inspection, preview, export, sampling, and CSV\u002FTSV conversion to the sibling tsfile-cli skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1372,1373,1374,1375],{"name":13,"slug":14,"type":15},{"name":1276,"slug":1277,"type":15},{"name":1315,"slug":32,"type":15},{"name":1229,"slug":33,"type":15},"2026-08-23T04:00:13.611935",{"slug":4,"name":4,"fn":5,"description":6,"org":1378,"tags":1379,"stars":22,"repoUrl":23,"updatedAt":24},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1380,1381,1382],{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15}]