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Claude Skills by Manoj-11-Dahal
github.com/Manoj-11-Dahal15,860 skills0 installs0 views
- Patternlab Time Series Analysis External Validation 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 external validation. Produce a risk-weighted verification plan with saved evidence 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 each critical requirement maps to a ...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a bounded build or configuration runbook with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means the prepared result is reproducible, revi...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: time-series analysis for measurement uncertainty. Produce a staged design blueprint with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means interfaces, dependencies, constraints, and review points are tes...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means the failure is bounded by observa...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a versioned improvement proposal and handoff packet with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means the proposed chan...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means options are compared on user-approved criteria...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means requirements have priorities, evidence, own...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means the owner, constraints, baseline, and acceptance signal are expl...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means the review names relevant...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means material claims are linked to current primary sources with dates and limitation...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Measurement Uncertainty 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 measurement uncertainty. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Carry sensor, annotation, sampling, and preprocessing error into the interpretation rather than reporting false precision. Success means each critical requirement ma...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a bounded build or configuration runbook with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means the prepared result is reproducible, review...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: time-series analysis for missing observations. Produce a staged design blueprint with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means interfaces, dependencies, constraints, and review points are testa...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a failure-triage record and reversible recovery plan with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means the failure is bounded by observati...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a versioned improvement proposal and handoff packet with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means the proposed change...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce an evidence-backed option-comparison matrix with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means options are compared on user-approved criteria w...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a reviewable requirements and decision brief with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means requirements have priorities, evidence, owner...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a scope-and-baseline record with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means the owner, constraints, baseline, and acceptance signal are explic...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a scoped risk-and-control review with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means the review names relevant h...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a source-and-claim ledger with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means material claims are linked to current primary sources with dates and limitations....Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Missing Observations 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 missing observations. Produce a risk-weighted verification plan with saved evidence with scope, versions, decisions, and evidence for this task-specific gate: Describe missingness by field/group and show sensitivity to treatment; do not impute silently or label absence as a signal. Success means each critical requirement maps...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Multiple Comparisons 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 multiple comparisons. Produce a bounded build or configuration runbook 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 prepared result is reproducible, reviewable, and wi...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Multiple Comparisons Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: time-series analysis for multiple comparisons. Produce a staged design blueprint 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 interfaces, dependencies, constraints, and review points are testable before b...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 tes...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 Time Series Analysis Multiple Comparisons 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 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 uncertai...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 measu...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 perm...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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, perm...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Multiple Comparisons 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 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 permiss...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 reprod...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Privacy Constraints 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 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 Time Series Analysis Privacy Constraints Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: time-series analysis 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 befor...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 ...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 compa...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Privacy Constraints 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 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 uncer...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 me...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 p...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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, p...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Privacy Constraints 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 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 perm...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 rep...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Reproducibility 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 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 wit...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Reproducibility Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: time-series analysis 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 bu...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Reproducibility 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 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 test...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 ...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Reproducibility 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 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 uncertain...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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 measur...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Reproducibility 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 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 permi...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis 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: time-series analysis 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, permi...Votes: 0GitHub stars: 2
- Patternlab Time Series Analysis Reproducibility 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 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 permissi...Votes: 0GitHub stars: 2