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Claude Skills by Manoj-11-Dahal
github.com/Manoj-11-Dahal15,860 skills0 installs0 views
- Patternlab Pattern Recognition Multiple Comparisons Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: pattern recognition for multiple comparisons. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means the failure is bounded by observations, one test...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons 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: pattern recognition for multiple comparisons. Produce a versioned improvement proposal and handoff packet with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means the proposed change is compared ...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: pattern recognition for multiple comparisons. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means options are compared on user-approved criteria with uncertain...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons Requirements And Decision BriefUse when a request must be converted into testable constraints and an owned decision for Pattern recognition and applied machine learning: pattern recognition for multiple comparisons. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means requirements have priorities, evidence, owners, and measur...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: pattern recognition for multiple comparisons. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means the owner, constraints, baseline, and acceptance signal are explicit. Use permi...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons 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: pattern recognition for multiple comparisons. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means the review names relevant hazards, permi...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition for multiple comparisons. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means material claims are linked to current primary sources with dates and limitations. Use permissi...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons 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: pattern recognition for multiple comparisons. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Predeclare comparisons or adjust for multiplicity; distinguish exploratory patterns from confirmatory evidence. Success means each critical requirement maps to a reprodu...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: pattern recognition for privacy constraints. Produce a bounded build or configuration runbook 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 the prepared result is reproducible, reviewable, and ...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition for privacy constraints. Produce a staged design blueprint 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 interfaces, dependencies, constraints, and review points are testable before...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: pattern recognition for privacy constraints. Produce a failure-triage record and reversible recovery plan 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 the failure is bounded by observations, one t...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints 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: pattern recognition for privacy constraints. Produce a versioned improvement proposal and handoff packet 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 the proposed change is compar...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: pattern recognition for privacy constraints. Produce an evidence-backed option-comparison matrix 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 options are compared on user-approved criteria with uncert...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints Requirements And Decision BriefUse when a request must be converted into testable constraints and an owned decision for Pattern recognition and applied machine learning: pattern recognition for privacy constraints. Produce a reviewable requirements and decision brief 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 requirements have priorities, evidence, owners, and mea...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: pattern recognition for privacy constraints. Produce a scope-and-baseline record 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 the owner, constraints, baseline, and acceptance signal are explicit. Use pe...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints 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: pattern recognition for privacy constraints. Produce a scoped risk-and-control review 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 the review names relevant hazards, pe...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Privacy Constraints Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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 limitations. Use permi...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 maps to a repr...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Reproducibility Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: pattern recognition 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, reviewable, and with...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Reproducibility Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 testable before bui...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Reproducibility Failure Triage And RecoveryUse when an unexpected result needs diagnosis without widening risk or losing evidence for Pattern recognition and applied machine learning: pattern recognition 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 observations, one testa...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 is compared w...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Reproducibility Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: pattern recognition 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 with uncertaint...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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, and measura...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Reproducibility Scope And Baseline RecordUse when the work needs a verified goal, authorized boundary, and starting state for Pattern recognition and applied machine learning: pattern recognition 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. Use permis...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 hazards, permis...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Reproducibility Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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. Use permissio...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 to a reproduc...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Small Samples Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: pattern recognition 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 within the a...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Small Samples Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 build. Use ...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 testable hypo...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 compared with a ba...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Small Samples Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: pattern recognition 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 uncertainty and tr...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 measurable acce...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 permissioned i...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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, permissions, c...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Small Samples Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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 permissioned inpu...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 reproducible che...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Source Disagreement Build Configuration RunbookUse when an authorized implementation needs repeatable steps and a visible change boundary for Pattern recognition and applied machine learning: pattern recognition 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, reviewable, and w...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Source Disagreement Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 testable before ...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 observations, one te...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Source Disagreement 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: pattern recognition for source disagreement. Produce a versioned improvement proposal and handoff packet 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 proposed change is compare...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Source Disagreement Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: pattern recognition 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 with uncerta...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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, owners, and meas...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 explicit. Use per...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 hazards, per...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Source Disagreement Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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. Use permis...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 maps to a repro...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Dataset Shift 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 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, review...Votes: 0GitHub stars: 2
- Patternlab Statistical Evidence Assessment Dataset Shift Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: statistical evidence assessment 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 testa...Votes: 0GitHub stars: 2