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Found 301 Skills
Run a comprehensive data quality assessment and produce a scorecard across 6 dimensions: completeness, uniqueness, consistency, timeliness, accuracy, validity. Use when the user asks about data quality, mentions data issues, wants to audit a table, is onboarding a new data source, or needs to validate pipeline output.
Profile-driven performance optimization with behavior proofs. Use when: optimize, slow, bottleneck, hotspot, profile, p95, latency, throughput, or algorithmic improvements.
Evaluate the performance of Triton operators on Ascend NPU. It is used when users need to analyze operator performance bottlenecks, collect and compare operator performance using msprof/msprof op, diagnose Memory-Bound/Compute-Bound bottlenecks, measure hardware utilization metrics, and generate performance evaluation reports.
Guidance for interpreting SPAA (Stack Profile for Agentic Analysis) files. Provides information on the file format, as well as tips on how to use it to identify performance bottlenecks, memory leaks, or opportunities for optimization. Use when the user is trying to read a .spaa file to understand the performance of an application.
Render JSON artifacts into readable UI with an inspect-first, facts-first workflow. Use when Codex needs to turn JSON files, JSON-producing shell commands, CLI output artifacts, or unknown structured payloads into a declarative UI spec that can be rendered natively by the harness or through a terminal-native reference renderer, including cases with repeated child records encoded as aligned arrays.
Establish CPU/GPU baselines before resource-intensive operations.
Profile a new tabular dataset before modeling. Find target leakage, missing data patterns, high-cardinality categoricals, near-constant features, redundant pairs, and non-linear relationships that Pearson correlation misses. Use whenever the user hands you a CSV or parquet and asks "what should I do with this?" Always run this skill before training any model on data you haven't seen before.
Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
진단 대화 시작점. 학습자의 직무/경력/AI 경험/사전 지식/학습 목적을 5문항으로 파악하고 학습 경로를 제안할 때 사용.
Read any data file (CSV, JSON, Parquet, Avro, Excel, spatial, SQLite) or remote URL (S3, HTTPS). Use when user references a data file, asks "what's in this file", or wants to preview/profile a dataset. Not for source code.
Build a personalised voice profile inside a Cowork project from a short interview plus 3 to 5 sample pieces of writing. Works for any content format: LinkedIn posts, newsletters, essays, emails, blog posts, tweets, or any other published writing. Use this skill at the start of any Cowork project where the user wants Claude to learn who they are and how they write before drafting new content. Trigger whenever the user says "build my voice", "learn my voice", "set up my content system", "onboard me", "train on my writing", "train on my posts", "I want Claude to sound like me", or drops a batch of writing samples into chat at the start of a project. Also trigger for first-time Cowork users who need a voice foundation before writing anything. Always produces two files (about-me.md and voice.md) saved into the project root.
Retrieves chemical compound information from PubChem and ChEMBL with disambiguation, cross-referencing, and quality assessment. Creates comprehensive compound profiles with identifiers, properties, bioactivity, and drug information. Use when users need chemical data, drug information, or mention PubChem CID, ChEMBL ID, SMILES, InChI, or compound names.