{ "name": "vector-agentic-skills", "repository": "https://github.com/MuhammadHusnainAli/vector-agentic-skills", "site": "https://agenticskills.vector-ai-lab.com", "skill_count": 21, "categories": [ { "name": "programming", "title": "Programming", "description": "Skills for writing, reviewing, debugging and optimising code and queries, grouped by language and tool.", "skill_count": 18, "subcategories": [ { "name": "sql", "title": "SQL", "description": "Write, check, explain, optimise, debug and translate SQL across PostgreSQL, MySQL, SQL Server, Oracle and SQLite, plus analytics, reporting and data-quality work.", "plugin": "sql-skills", "skill_count": 11, "skills": [ "sql-analytics", "sql-data-quality", "sql-debugger", "sql-dialect-translator", "sql-optimizer", "sql-performance-tuning", "sql-query-explainer", "sql-query-writer", "sql-reporting", "sql-syntax-checker", "sql-window-functions" ] }, { "name": "python", "title": "Python", "description": "Write, review and teach idiomatic modern Python for AI engineers: idioms, comprehensions, type hints, dataclasses, exception design, context managers and beginner tutoring.", "plugin": "python-skills", "skill_count": 7, "skills": [ "python-beginner-concept-tutor", "python-comprehension-refactorer", "python-context-manager-writer", "python-dataclass-converter", "python-exception-handling-designer", "python-idiomatic-code-reviewer", "python-type-hints-annotator" ] } ] }, { "name": "productivity", "title": "Productivity", "description": "Skills for office and business tools: spreadsheets, documents and everyday data work.", "skill_count": 3, "subcategories": [ { "name": "excel", "title": "Excel", "description": "Write error-free Excel formulas, use modern LAMBDA and dynamic-array functions, and organise, format and inspect workbooks.", "plugin": "excel-skills", "skill_count": 3, "skills": [ "excel-advanced-formulas", "excel-formulas", "excel-fundamentals" ] } ] } ], "skills": [ { "name": "excel-advanced-formulas", "title": "Advanced XLSX Formulas", "description": "Modern Excel 365/2021+ formulas — LAMBDA and LAMBDA helpers (MAP, REDUCE, SCAN, BYROW, BYCOL), LET, dynamic arrays (FILTER, SORT, UNIQUE, HSTACK, VSTACK, TAKE, DROP), TEXTSPLIT, REGEX functions, GROUPBY and PIVOTBY. Use when the user needs custom reusable functions, array reshaping, regex text parsing, or formulas beyond classic Excel.", "category": "productivity", "subcategory": "excel", "version": "1.0.0", "path": "skills/productivity/excel/excel-advanced-formulas", "files": [ "SKILL.md", "references/advanced-patterns.md", "references/array-manipulation.md", "references/lambda-functions.md", "references/text-parsing.md", "scripts/check_compat.py" ], "references": [ "references/advanced-patterns.md", "references/array-manipulation.md", "references/lambda-functions.md", "references/text-parsing.md" ], "scripts": [ "scripts/check_compat.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/excel-advanced-formulas/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/productivity/excel/excel-advanced-formulas/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/excel-advanced-formulas.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/productivity/excel/excel-advanced-formulas", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill excel-advanced-formulas" }, { "name": "excel-formulas", "title": "XLSX Formulas", "description": "Write error-free Excel formulas — syntax rules, cell references, math, logical, lookup (VLOOKUP, INDEX/MATCH, XLOOKUP), text, date/time and conditional aggregation (SUMIFS, COUNTIFS) with error handling. Use when the user asks for an Excel or spreadsheet formula, a calculation in a workbook, or help fixing #REF!, #VALUE!, #N/A or #NAME? errors.", "category": "productivity", "subcategory": "excel", "version": "1.0.0", "path": "skills/productivity/excel/excel-formulas", "files": [ "SKILL.md", "references/examples.md", "references/formulas.md", "references/functions-reference.md", "scripts/check_formula.py" ], "references": [ "references/examples.md", "references/formulas.md", "references/functions-reference.md" ], "scripts": [ "scripts/check_formula.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/excel-formulas/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/productivity/excel/excel-formulas/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/excel-formulas.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/productivity/excel/excel-formulas", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill excel-formulas" }, { "name": "excel-fundamentals", "title": "XLSX Fundamentals", "description": "Excel workbook fundamentals — cells, ranges, absolute/relative references, named ranges, number formats, conditional formatting, sheets and views, sorting, filtering, tables and keyboard shortcuts. Use when the user asks how to organise, format, sort, filter or navigate spreadsheet data rather than write a formula.", "category": "productivity", "subcategory": "excel", "version": "1.0.0", "path": "skills/productivity/excel/excel-fundamentals", "files": [ "SKILL.md", "references/cells-and-ranges.md", "references/formatting-and-styles.md", "references/sheets-and-views.md", "references/sorting-filtering-tables.md", "scripts/inspect_workbook.py" ], "references": [ "references/cells-and-ranges.md", "references/formatting-and-styles.md", "references/sheets-and-views.md", "references/sorting-filtering-tables.md" ], "scripts": [ "scripts/inspect_workbook.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/excel-fundamentals/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/productivity/excel/excel-fundamentals/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/excel-fundamentals.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/productivity/excel/excel-fundamentals", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill excel-fundamentals" }, { "name": "python-beginner-concept-tutor", "title": "Python Beginner Concept Tutor", "description": "Teach Python concepts to beginners heading into AI engineering (data scientists, analysts, students, career switchers): plain-language definitions, analogies, minimal examples, line-by-line walkthroughs, common mistakes, check-your-understanding questions and mini exercises; Socratic hints before solutions; explaining tracebacks; mutable vs immutable, references and aliasing, is vs ==, integer division, floating point, slicing and off-by-one, indentation errors; a staged learning path from variables to calling an LLM API, embeddings and a tiny RAG. Ships a script that lists the concepts a snippet uses in learning order and traces execution step by step like Python Tutor. Use when someone says they are new to Python, asks what a piece of code does line by line, asks to explain a concept or an error message simply, wants exercises or a study plan, or is learning Python to build LLM apps.", "category": "programming", "subcategory": "python", "version": "1.0.0", "path": "skills/programming/python/python-beginner-concept-tutor", "files": [ "SKILL.md", "faq.json", "prompts.txt", "references/common-beginner-errors.md", "references/concept-explanations.md", "references/curriculum-to-ai-engineer.md", "references/exercises-with-solutions.md", "references/faq.json", "references/prompts.txt", "references/teaching-playbook.md", "scripts/explain_concepts.py" ], "references": [ "references/common-beginner-errors.md", "references/concept-explanations.md", "references/curriculum-to-ai-engineer.md", "references/exercises-with-solutions.md", "references/faq.json", "references/prompts.txt", "references/teaching-playbook.md" ], "scripts": [ "scripts/explain_concepts.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/python-beginner-concept-tutor/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/python/python-beginner-concept-tutor/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/python-beginner-concept-tutor.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/python/python-beginner-concept-tutor", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill python-beginner-concept-tutor" }, { "name": "python-comprehension-refactorer", "title": "Python Comprehension Refactorer", "description": "Refactor Python loops into list, dict and set comprehensions and generator expressions, and unroll comprehensions that are too clever: filtering, mapping, nested-loop flattening, conditional expressions, walrus in comprehensions, dict inversion, grouping with defaultdict/Counter, lazy generators for sum/any/all/max, streaming large files, itertools (chain, islice, groupby, batched, pairwise, accumulate, product), scoping rules, side-effect anti-patterns and performance (when map/filter or numpy/pandas vectorization win). AI-engineering focus: building prompt lists, batching texts for embeddings, filtering retrieved chunks by score, id->embedding dicts, flattening tool-call results, lazy dataset streaming and token counting. Use when the user asks to make a loop more Pythonic, convert a for loop to a comprehension, simplify or explain a nested comprehension, reduce memory with generators, batch or chunk an iterable, or review .py code for comprehension anti-patterns.", "category": "programming", "subcategory": "python", "version": "1.0.0", "path": "skills/programming/python/python-comprehension-refactorer", "files": [ "SKILL.md", "references/ai-data-pipeline-patterns.md", "references/comprehension-patterns.md", "references/generators-and-itertools.md", "references/performance-notes.md", "references/when-not-to-use.md", "scripts/find_comprehension_candidates.py" ], "references": [ "references/ai-data-pipeline-patterns.md", "references/comprehension-patterns.md", "references/generators-and-itertools.md", "references/performance-notes.md", "references/when-not-to-use.md" ], "scripts": [ "scripts/find_comprehension_candidates.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/python-comprehension-refactorer/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/python/python-comprehension-refactorer/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/python-comprehension-refactorer.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/python/python-comprehension-refactorer", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill python-comprehension-refactorer" }, { "name": "python-context-manager-writer", "title": "Python Context Manager Writer", "description": "Write correct Python context managers and find resource-handling bugs — __enter__/__exit__ semantics and exception suppression, contextlib (contextmanager, asynccontextmanager, ExitStack, AsyncExitStack, closing, aclosing, suppress, redirect_stdout, nullcontext, chdir), async with, re-entrancy, leaked files/connections/clients/pools/locks, and AI-engineering recipes: torch.no_grad/inference_mode/autocast, eval()/train() switches, GPU cache cleanup, token and latency meters, tracing spans, temp env vars, rate-limit semaphores, httpx/aiohttp client lifecycle, FastAPI lifespan, DB/vector-store transactions, atomic checkpoint writes, seeds and agent sandboxes. Use when writing or reviewing a with statement or context manager, when files/sockets/clients/sessions/locks are opened without with, when an error is silently swallowed by __exit__ or a @contextmanager, on ResourceWarning, Too many open files, deadlocks, or generator didn't stop errors, or when wiring setup/teardown for models, clients and transactions.", "category": "programming", "subcategory": "python", "version": "1.0.0", "path": "skills/programming/python/python-context-manager-writer", "files": [ "SKILL.md", "references/ai-engineering-recipes.md", "references/async-context-managers.md", "references/contextlib-reference.md", "references/pitfalls-and-testing.md", "references/protocol-reference.md", "references/recipes.md", "scripts/ctx_tool.py" ], "references": [ "references/ai-engineering-recipes.md", "references/async-context-managers.md", "references/contextlib-reference.md", "references/pitfalls-and-testing.md", "references/protocol-reference.md", "references/recipes.md" ], "scripts": [ "scripts/ctx_tool.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/python-context-manager-writer/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/python/python-context-manager-writer/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/python-context-manager-writer.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/python/python-context-manager-writer", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill python-context-manager-writer" }, { "name": "python-dataclass-converter", "title": "Python Dataclass Converter", "description": "Convert boilerplate Python classes, dicts, tuples and JSON payloads into dataclasses, or into pydantic v2 BaseModel, TypedDict, NamedTuple, attrs or msgspec when that fits better. Covers every @dataclass option (frozen, slots, kw_only, order, unsafe_hash, match_args, weakref_slot), field() (default_factory, init=False, repr, compare, hash, metadata), __post_init__, InitVar, KW_ONLY, inheritance and default ordering, replace(), asdict deep-copy pitfalls, hashing/equality, serialization and validation. AI focus: LLM request/response and chat Message types, RAG chunks with embeddings (numpy eq gotcha), eval records, configs, typed OpenAI/Anthropic JSON. Use when the user asks to convert a class or dict to a dataclass, remove __init__/__repr__/__eq__ boilerplate, model a JSON/API response with types, pick dataclass vs pydantic vs TypedDict, or fix dataclass errors (mutable default, non-default argument follows default argument, FrozenInstanceError, unhashable type).", "category": "programming", "subcategory": "python", "version": "1.0.0", "path": "skills/programming/python/python-dataclass-converter", "files": [ "SKILL.md", "references/ai-engineering-models.md", "references/choosing-a-data-container.md", "references/conversion-examples.md", "references/dataclass-reference.md", "references/serialization-and-validation.md", "scripts/to_dataclass.py" ], "references": [ "references/ai-engineering-models.md", "references/choosing-a-data-container.md", "references/conversion-examples.md", "references/dataclass-reference.md", "references/serialization-and-validation.md" ], "scripts": [ "scripts/to_dataclass.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/python-dataclass-converter/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/python/python-dataclass-converter/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/python-dataclass-converter.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/python/python-dataclass-converter", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill python-dataclass-converter" }, { "name": "python-exception-handling-designer", "title": "Python Exception Handling Designer", "description": "Design and review Python exception handling: custom exception hierarchies with retryable flags, what to catch where, EAFP vs LBYL, chaining with raise ... from, else/finally, logger.exception, add_note, ExceptionGroup and except* with asyncio.TaskGroup, warnings, asserts vs validation, FastAPI error translation, retries with backoff and jitter, timeouts, cancellation, pytest.raises, plus LLM-app failures: 429 rate limits with retry-after, 5xx overloaded, context-length exceeded, content filters, broken streams, malformed JSON repair loops, tool-call errors fed back to the model, partial embedding batch failures, CUDA OOM batch halving, vector DB outages, circuit breakers and model fallbacks. Use when the user writes or reviews try/except code, designs an errors.py, asks how to retry or handle LLM/API errors, sees swallowed or lost tracebacks, maps exceptions to HTTP status codes, or tests exceptions in .py files.", "category": "programming", "subcategory": "python", "version": "1.0.0", "path": "skills/programming/python/python-exception-handling-designer", "files": [ "SKILL.md", "references/ai-error-handling.md", "references/anti-patterns.md", "references/async-and-groups.md", "references/exception-hierarchy.md", "references/patterns.md", "references/testing-exceptions.md", "scripts/audit_exceptions.py", "scripts/scaffold_exceptions.py" ], "references": [ "references/ai-error-handling.md", "references/anti-patterns.md", "references/async-and-groups.md", "references/exception-hierarchy.md", "references/patterns.md", "references/testing-exceptions.md" ], "scripts": [ "scripts/audit_exceptions.py", "scripts/scaffold_exceptions.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/python-exception-handling-designer/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/python/python-exception-handling-designer/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/python-exception-handling-designer.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/python/python-exception-handling-designer", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill python-exception-handling-designer" }, { "name": "python-idiomatic-code-reviewer", "title": "Python Idiomatic Code Reviewer", "description": "Review Python code for non-idiomatic, unpythonic or risky patterns and rewrite it into clean modern Python: PEP 8 / PEP 20, EAFP vs LBYL, iteration idioms (enumerate, zip, comprehensions, any/all), unpacking, f-strings, pathlib, truthiness, `is None`, mutable defaults, walrus, match statements, collections / itertools / functools, logging instead of print, with-blocks and resource handling. Includes AI-engineering checks: hardcoded API keys, time.sleep or requests inside async def, missing HTTP timeouts, unbounded retry loops, model clients built at import time, prompt string concatenation, sequential awaits, eval() on LLM output. Ships a 46-rule AST reviewer with severities and suggested rewrites. Use when the user asks to review, clean up, modernise, make pythonic or idiomatic, refactor or code-review a .py file, LLM / RAG / agent / FastAPI / training code, a pull request diff, or asks 'is this good Python?' or 'how would a senior Python dev write this?'.", "category": "programming", "subcategory": "python", "version": "1.0.0", "path": "skills/programming/python/python-idiomatic-code-reviewer", "files": [ "SKILL.md", "references/ai-engineering-idioms.md", "references/idioms-catalog.md", "references/modern-python-by-version.md", "references/review-checklist.md", "references/stdlib-power-tools.md", "scripts/review_idioms.py" ], "references": [ "references/ai-engineering-idioms.md", "references/idioms-catalog.md", "references/modern-python-by-version.md", "references/review-checklist.md", "references/stdlib-power-tools.md" ], "scripts": [ "scripts/review_idioms.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/python-idiomatic-code-reviewer/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/python/python-idiomatic-code-reviewer/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/python-idiomatic-code-reviewer.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/python/python-idiomatic-code-reviewer", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill python-idiomatic-code-reviewer" }, { "name": "python-type-hints-annotator", "title": "Python Type Hints Annotator", "description": "Add accurate, modern type hints to Python and fix mypy / pyright (pyrefly, ty) errors: builtin generics, X | None, TypeAlias and the 3.12 type statement, TypeVar and PEP 695 generics, Protocol, Callable / ParamSpec / Concatenate, TypedDict (Required, NotRequired, ReadOnly), Literal, Final, ClassVar, overload, Annotated, TypeGuard / TypeIs, Self, Never, TypeVarTuple, async types, Iterable vs Sequence vs Mapping, TYPE_CHECKING, stubs, py.typed, gradual strictness. AI-engineering focus: typed LLM message dicts and tool schemas, pydantic vs TypedDict, numpy NDArray, torch / jaxtyping shapes, streaming generators, async clients, callbacks, generic VectorStore protocols, typed config. Ships an AST audit: coverage gate, legacy-typing rewrites, inferred types. Use when the user asks to add type hints, annotate or type a module, fix a mypy or pyright error, modernise typing imports (List, Optional, Union), set up strict type checking or a coverage gate in CI, or type LLM, RAG, agent, FastAPI or ML code.", "category": "programming", "subcategory": "python", "version": "1.0.0", "path": "skills/programming/python/python-type-hints-annotator", "files": [ "SKILL.md", "references/advanced-typing.md", "references/ai-ml-typing.md", "references/migration-strategy.md", "references/type-checker-setup.md", "references/typing-cheatsheet.md", "scripts/annotation_audit.py" ], "references": [ "references/advanced-typing.md", "references/ai-ml-typing.md", "references/migration-strategy.md", "references/type-checker-setup.md", "references/typing-cheatsheet.md" ], "scripts": [ "scripts/annotation_audit.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/python-type-hints-annotator/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/python/python-type-hints-annotator/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/python-type-hints-annotator.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/python/python-type-hints-annotator", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill python-type-hints-annotator" }, { "name": "sql-analytics", "title": "Analytics SQL", "description": "Analytical and aggregation SQL — GROUP BY, ROLLUP, CUBE, GROUPING SETS, pivots, cohorts, funnels, retention, percentiles and statistical functions. Use when the user needs metrics, business analysis, OLAP-style summaries, or customer/revenue/product analytics in SQL.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-analytics", "files": [ "SKILL.md", "references/examples.md", "scripts/analytics_sql.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/analytics_sql.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-analytics/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-analytics/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-analytics.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-analytics", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-analytics" }, { "name": "sql-data-quality", "title": "SQL Data Quality", "description": "Profile and validate data with SQL — NULL analysis, duplicate detection, referential integrity, range and format checks, outliers, constraints and cleansing queries. Use when the user wants to audit data quality, find duplicates or bad records, or add validation rules to a database.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-data-quality", "files": [ "SKILL.md", "references/examples.md", "references/monitoring-queries.md", "references/quality-reports.md", "scripts/profile_data.py" ], "references": [ "references/examples.md", "references/monitoring-queries.md", "references/quality-reports.md" ], "scripts": [ "scripts/profile_data.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-data-quality/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-data-quality/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-data-quality.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-data-quality", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-data-quality" }, { "name": "sql-debugger", "title": "SQL Debugger", "description": "Debug failing SQL or queries returning wrong results — interpret error messages, find causes of duplicates, missing rows, NULL surprises, fan-out joins and type mismatches, and produce a fixed query. Use when SQL throws an error, returns unexpected results, or the user asks why a query is failing.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-debugger", "files": [ "SKILL.md", "references/examples.md", "scripts/diagnose_error.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/diagnose_error.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-debugger/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-debugger/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-debugger.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-debugger", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-debugger" }, { "name": "sql-dialect-translator", "title": "SQL Dialect Translator", "description": "Translate SQL between dialects — PostgreSQL, MySQL, SQL Server (T-SQL), Oracle, SQLite — covering data types, functions, pagination, date handling, upserts and identity columns. Use when migrating queries between databases or the user asks to convert SQL to another dialect. Includes a sqlglot-based translation script.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-dialect-translator", "files": [ "SKILL.md", "references/examples.md", "scripts/translate_sql.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/translate_sql.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-dialect-translator/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-dialect-translator/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-dialect-translator.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-dialect-translator", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-dialect-translator" }, { "name": "sql-optimizer", "title": "SQL Query Optimizer", "description": "Rewrite slow SQL queries for performance — read execution plans (EXPLAIN / EXPLAIN ANALYZE), remove anti-patterns, make predicates sargable, choose JOIN/EXISTS strategies and suggest indexes. Use when the user says a query is slow, times out, or asks to optimise or speed up specific SQL.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-optimizer", "files": [ "SKILL.md", "references/examples.md", "scripts/find_antipatterns.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/find_antipatterns.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-optimizer/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-optimizer/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-optimizer.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-optimizer", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-optimizer" }, { "name": "sql-performance-tuning", "title": "SQL Performance Tuning", "description": "Database-level SQL performance tuning — index design and maintenance, query profiling, statistics, partitioning, schema design, locking and configuration bottlenecks. Use when the problem is the database or workload as a whole rather than one query, or when the user asks about indexing strategy or profiling.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-performance-tuning", "files": [ "SKILL.md", "references/examples.md", "scripts/analyze_plan.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/analyze_plan.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-performance-tuning/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-performance-tuning/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-performance-tuning.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-performance-tuning", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-performance-tuning" }, { "name": "sql-query-explainer", "title": "SQL Query Explainer", "description": "Explain what an existing SQL query does in plain language — logical execution order, step-by-step breakdown of joins, filters, grouping and window logic, and the shape of the result. Use when the user asks what a query does, how it works, or wants complex/legacy SQL documented.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-query-explainer", "files": [ "SKILL.md", "references/examples.md", "scripts/outline_query.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/outline_query.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-query-explainer/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-query-explainer/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-query-explainer.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-query-explainer", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-query-explainer" }, { "name": "sql-query-writer", "title": "SQL Query Writer", "description": "Write correct, readable SQL from natural-language requirements — SELECT, INSERT, UPDATE, DELETE, JOINs, subqueries, CTEs and DDL (CREATE/ALTER/DROP). Use when the user asks to write, create or generate a query, describes data they want to retrieve, or provides a schema and wants queries against it.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-query-writer", "files": [ "SKILL.md", "references/examples.md", "references/sql-quick-reference.md", "scripts/plan_joins.py" ], "references": [ "references/examples.md", "references/sql-quick-reference.md" ], "scripts": [ "scripts/plan_joins.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-query-writer/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-query-writer/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-query-writer.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-query-writer", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-query-writer" }, { "name": "sql-reporting", "title": "SQL Reporting", "description": "Build business reporting SQL — KPIs, dashboard datasets, period comparisons (MoM/YoY), executive, sales and financial reports and scheduled-report queries. Use when the user asks for a report, KPI query, dashboard feed or recurring business summary in SQL.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-reporting", "files": [ "SKILL.md", "references/examples.md", "references/formatting.md", "references/operational-reports.md", "scripts/date_ranges.py" ], "references": [ "references/examples.md", "references/formatting.md", "references/operational-reports.md" ], "scripts": [ "scripts/date_ranges.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-reporting/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-reporting/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-reporting.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-reporting", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-reporting" }, { "name": "sql-syntax-checker", "title": "SQL Syntax Checker", "description": "Validate SQL syntax and structure before execution and point out errors with corrected versions, dialect-aware (PostgreSQL, MySQL, SQL Server, Oracle, SQLite). Use when the user asks to check, lint, validate or review a SQL statement, or pastes SQL that may not parse. Includes a script that parses SQL with sqlglot.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-syntax-checker", "files": [ "SKILL.md", "references/examples.md", "scripts/check_sql.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/check_sql.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-syntax-checker/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-syntax-checker/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-syntax-checker.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-syntax-checker", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-syntax-checker" }, { "name": "sql-window-functions", "title": "SQL Window Functions", "description": "Write window/analytic SQL — ROW_NUMBER, RANK, DENSE_RANK, NTILE, LAG/LEAD, FIRST_VALUE/LAST_VALUE, running totals, moving averages and frame clauses (ROWS/RANGE). Use for rankings, top-N per group, period-over-period comparisons, cumulative sums or deduplication with window functions.", "category": "programming", "subcategory": "sql", "version": "1.0.0", "path": "skills/programming/sql/sql-window-functions", "files": [ "SKILL.md", "references/examples.md", "scripts/sql_sandbox.py" ], "references": [ "references/examples.md" ], "scripts": [ "scripts/sql_sandbox.py" ], "url": "https://agenticskills.vector-ai-lab.com/skills/sql-window-functions/", "raw_url": "https://agenticskills.vector-ai-lab.com/raw/skills/programming/sql/sql-window-functions/SKILL.md", "download_url": "https://agenticskills.vector-ai-lab.com/dl/sql-window-functions.tar.gz", "source_url": "https://github.com/MuhammadHusnainAli/vector-agentic-skills/tree/main/skills/programming/sql/sql-window-functions", "install": "npx skills add https://agenticskills.vector-ai-lab.com --skill sql-window-functions" } ] }