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Claude Skills by Manoj-11-Dahal
github.com/Manoj-11-Dahal15,860 skills0 installs0 views
- Patternlab Statistical Evidence Assessment Privacy Constraints Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: statistical evidence assessment for privacy constraints. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Minimize personal data, document lawful/approved access, and report subgroup results only where disclosure is safe. Success means material claims are linked to current primary sources with dates and limitation...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Privacy Constraints Verification And Acceptance Test PlanUse when a result must be checked against explicit behavior, safety, or quality conditions for Pattern recognition and applied machine learning: statistical evidence assessment for privacy constraints. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Minimize personal data, document lawful/approved access, and report subgroup results only where disclosure is safe. Success means each critical requirement ma...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a bounded build or configuration runbook with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means the prepared result is reproducible, reviewab...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a staged design blueprint with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means interfaces, dependencies, constraints, and review points are testabl...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means the failure is bounded by observation...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Measured Improvement And HandoffUse when a measured result or recurring failure suggests a change worth testing and handing to an owner for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a versioned improvement proposal and handoff packet with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means the proposed change i...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means options are compared on user-approved criteria wit...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Requirements And Decision BriefUse when a request must be converted into testable constraints and an owned decision for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means requirements have priorities, evidence, owners,...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means the owner, constraints, baseline, and acceptance signal are explicit...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Security Rights And Safety ReviewUse when the workflow could affect people, systems, confidential data, intellectual property, or physical outcomes for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means the review names relevant haz...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means material claims are linked to current primary sources with dates and limitations. U...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Reproducibility Verification And Acceptance Test PlanUse when a result must be checked against explicit behavior, safety, or quality conditions for Pattern recognition and applied machine learning: statistical evidence assessment for reproducibility. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Record data version, feature steps, parameters, random state, software version, and reproducible evaluation method. Success means each critical requirement maps t...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a bounded build or configuration runbook with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means the prepared result is reproducible, reviewable, and ...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a staged design blueprint with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means interfaces, dependencies, constraints, and review points are testable before...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means the failure is bounded by observations, one t...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Measured Improvement And HandoffUse when a measured result or recurring failure suggests a change worth testing and handing to an owner for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a versioned improvement proposal and handoff packet with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means the proposed change is compar...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means options are compared on user-approved criteria with uncert...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Requirements And Decision BriefUse when a request must be converted into testable constraints and an owned decision for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means requirements have priorities, evidence, owners, and mea...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means the owner, constraints, baseline, and acceptance signal are explicit. Use pe...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Security Rights And Safety ReviewUse when the workflow could affect people, systems, confidential data, intellectual property, or physical outcomes for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means the review names relevant hazards, pe...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means material claims are linked to current primary sources with dates and limitations. Use permi...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Small Samples Verification And Acceptance Test PlanUse when a result must be checked against explicit behavior, safety, or quality conditions for Pattern recognition and applied machine learning: statistical evidence assessment for small samples. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Report sample count, unit of analysis, uncertainty range, and the limits of generalizing from a small sample. Success means each critical requirement maps to a repr...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a bounded build or configuration runbook with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means the prepared result is reproducible, revie...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a staged design blueprint with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means interfaces, dependencies, constraints, and review points are test...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means the failure is bounded by observat...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means options are compared on user-approved criteria ...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Requirements And Decision BriefUse when a request must be converted into testable constraints and an owned decision for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means requirements have priorities, evidence, owne...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means the owner, constraints, baseline, and acceptance signal are expli...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Security Rights And Safety ReviewUse when the workflow could affect people, systems, confidential data, intellectual property, or physical outcomes for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means the review names relevant ...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means material claims are linked to current primary sources with dates and limitations...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Source Disagreement Verification And Acceptance Test PlanUse when a result must be checked against explicit behavior, safety, or quality conditions for Pattern recognition and applied machine learning: statistical evidence assessment for source disagreement. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Compare labels, collection procedures, and subgroup composition before interpreting disagreement as a real effect. Success means each critical requirement map...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a bounded build or configuration runbook with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means the prepared result is reproducible, reviewable, and w...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a staged design blueprint with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means interfaces, dependencies, constraints, and review points are testable before ...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means the failure is bounded by observations, one te...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Measured Improvement And HandoffUse when a measured result or recurring failure suggests a change worth testing and handing to an owner for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a versioned improvement proposal and handoff packet with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means the proposed change is compare...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means options are compared on user-approved criteria with uncerta...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Requirements And Decision BriefUse when a request must be converted into testable constraints and an owned decision for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means requirements have priorities, evidence, owners, and meas...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means the owner, constraints, baseline, and acceptance signal are explicit. Use per...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Security Rights And Safety ReviewUse when the workflow could affect people, systems, confidential data, intellectual property, or physical outcomes for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means the review names relevant hazards, per...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means material claims are linked to current primary sources with dates and limitations. Use permis...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Dataset Shift Verification And Acceptance Test PlanUse when a result must be checked against explicit behavior, safety, or quality conditions for Pattern recognition and applied machine learning: time-series analysis for dataset shift. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Separate training and evaluation by time/source where appropriate and test for drift against the baseline distribution. Success means each critical requirement maps to a repro...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a bounded build or configuration runbook with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means the prepared result is reproducible, reviewable, ...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a staged design blueprint with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means interfaces, dependencies, constraints, and review points are testable be...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means the failure is bounded by observations, o...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Measured Improvement And HandoffUse when a measured result or recurring failure suggests a change worth testing and handing to an owner for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a versioned improvement proposal and handoff packet with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means the proposed change is co...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means options are compared on user-approved criteria with un...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Requirements And Decision BriefUse when a request must be converted into testable constraints and an owned decision for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means requirements have priorities, evidence, owners, and...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means the owner, constraints, baseline, and acceptance signal are explicit. Us...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Security Rights And Safety ReviewUse when the workflow could affect people, systems, confidential data, intellectual property, or physical outcomes for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means the review names relevant hazards...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis External Validation Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: time-series analysis for external validation. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Hold out an independent source or sample before evaluation and report performance variability, not just a point score. Success means material claims are linked to current primary sources with dates and limitations. Use p...Votes: 0GitHub stars: 2