Plugin Claude Code
Development marketplace for datapowers data mining skills library.
1 5mo ago A
tokens not measured
original MIT
datapowers
02Plugin Claude Code
Data mining skills library: EDA, validation, feature engineering, modeling, and proven analytical workflows for data analysts.
1 5mo ago A
tokens not measured
original MIT
Instructions file Gemini CLI
Gemini CLI instructions for zpower426/datapowers, a project described as: Professional Data Mining & ML Protocol: A hypothesis-driven workflow featuring strict leakage-guards, three-layer validation, and statistical rigor for robust AI agent deployment.
1 5mo ago A 28 tokens
original MIT
analyst
04Agent
Dispatch as a subagent to execute a specific analysis task. Receives full task specification from the orchestrating agent. Does NOT inherit session context. Examples: Context: An orchestrating agent is running subagent-driven-analysis. user: "Execute Task 3: numeric feature preprocessing" assistant: "Dispatching…
1 5mo ago A 100 tokens
original MIT
Agent
Use after statistical review has passed to check code quality of analysis code. Reviews for vectorization, reproducibility, clarity, and artifact correctness. Examples: Context: Statistical review has passed for a feature engineering task. user: "Statistical review approved the feature engineering code" assistant…
1 5mo ago A 99 tokens
original MIT
Agent
Use after an analyst subagent completes a task to verify statistical correctness. Reviews for data leakage, correct metric selection, proper cross-validation, and sound statistical methodology. Examples: Context: A feature engineering task has been completed. user: "Feature engineering for numeric columns is done"…
1 5mo ago A 110 tokens
original MIT
brainstorm
07Command
Start a new analysis project with structured hypothesis-first brainstorming.
1 5mo ago A 10 tokens
original MIT
execute-plan
08Command
Execute an analysis plan using subagent-driven analysis with two-stage review.
1 5mo ago A 13 tokens
original MIT
write-plan
09Command
Break an approved analysis design into discrete, executable tasks.
1 5mo ago A 10 tokens
original MIT
SessionStart
10Hook
Runs when a session starts on startup, clear and compact, executing run-hook.cmd. From zpower426/datapowers.
1 5mo ago A
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copy · 86% MIT
Skill Claude CodeCodex
Use at the START of every analysis session and at the END of every skill stage. Maintains artifacts/analysismanifest.json as the single source of truth for analysis state, preventing context drift across long sessions.
1 5mo ago A 45 tokens
original MIT
Skill Claude CodeCodex
Use BEFORE any analysis project, ML task, or significant data work. Explores business context, data characteristics, and analytical approach before any code or modeling.
1 5mo ago B 35 tokens
original MIT
Skill Claude CodeCodex
Use when exploring any dataset for the first time, or when asked to perform EDA. Enforces systematic exploration before any modeling or transformation.
1 5mo ago A 33 tokens
original MIT
Skill Claude CodeCodex
Use BEFORE dispatching any subagent that needs to understand the dataset. Generates a high-density, PII-free data profile in Markdown so subagents receive structured context instead of raw data.
1 5mo ago A 42 tokens
original MIT
Skill Claude CodeCodex
Use before any model training, feature engineering, or data transformation. Validates data schema, quality constraints, and statistical expectations.
1 5mo ago A 28 tokens
original MIT
Skill Claude CodeCodex
Use when a data pipeline, model, or analysis produces unexpected results, errors, or performance degradation. Enforces root cause investigation before any fix.
1 5mo ago A 34 tokens
original MIT
Skill Claude CodeCodex
Use when executing a written analysis plan task by task. Manages task state, enforces two-stage review (statistical first, then code quality), and gates manifest updates behind completed reviews.
1 5mo ago A 43 tokens
original MIT
Skill Claude CodeCodex
Use when creating, transforming, or selecting features. Enforces leakage-free, reproducible feature pipelines.
1 5mo ago A 24 tokens
original MIT
Skill Claude CodeCodex
Use when analysis is complete, all validations pass, and you need to decide how to integrate the work — guides delivery of analysis artifacts via commit, PR, or archive.
1 5mo ago A 41 tokens
original MIT
Skill Claude CodeCodex
Use whenever building features for time-series or any temporal dataset. Enforces strict temporal integrity: no future data in features, no post-event information, correct CV strategy.
1 5mo ago A 39 tokens
original MIT
Skill Claude CodeCodex
Use when evaluating a trained model. Enforces one-time test set evaluation, statistical significance testing, and calibration checks.
1 5mo ago A 27 tokens
original MIT
Skill Claude CodeCodex
Use when choosing which model(s) to train. Enforces baseline comparison before hyperparameter tuning, and correct metric selection for the task type.
1 5mo ago A 31 tokens
original MIT
Skill Claude CodeCodex
Use when writing analysis reports, stakeholder summaries, or presenting model results. Enforces reproducibility, honest uncertainty communication, and actionable conclusions.
1 5mo ago A 30 tokens
original MIT
Skill Claude CodeCodex
Use after completing any major analytical task (EDA, features, modeling). Enforces rigorous auditing for target leakage, metric choice, and statistical significance.
1 5mo ago A 35 tokens
original MIT