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Claude Skills by Manoj-11-Dahal
github.com/Manoj-11-Dahal15,860 skills0 installs0 views
- Patternlab Classification Evaluation 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: classification evaluation 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, ...Votes: 0GitHub stars: 2
- Patternlab Classification Evaluation 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: classification evaluation 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 c...Votes: 0GitHub stars: 2
- Patternlab Classification Evaluation Source Disagreement Option Comparison MatrixUse when several tools, designs, methods, or workflows could satisfy the same need for Pattern recognition and applied machine learning: classification evaluation 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 u...Votes: 0GitHub stars: 2
- Patternlab Classification Evaluation 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: classification evaluation 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, an...Votes: 0GitHub stars: 2
- Patternlab Classification Evaluation 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: classification evaluation 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. U...Votes: 0GitHub stars: 2
- Patternlab Classification Evaluation 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: classification evaluation 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 hazard...Votes: 0GitHub stars: 2
- Patternlab Classification Evaluation Source Disagreement Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: classification evaluation 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 ...Votes: 0GitHub stars: 2
- Patternlab Classification Evaluation 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: classification evaluation 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...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Dataset Shift 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 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 wi...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Dataset Shift Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 b...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 tes...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 compared...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Dataset Shift 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 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 uncertai...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 measu...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 perm...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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, perm...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Dataset Shift Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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 permiss...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 reprod...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition External Validation 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 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, a...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition External Validation Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 bef...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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, on...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 com...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition External Validation 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 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 unc...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 Pattern Recognition 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: pattern recognition 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. Use...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 Pattern Recognition External Validation Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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 pe...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 r...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Measurement Uncertainty 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 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, revie...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Measurement Uncertainty Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 test...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 observat...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 chang...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Measurement Uncertainty 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 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 Pattern Recognition 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: pattern recognition 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, owne...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 expli...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 Pattern Recognition Measurement Uncertainty Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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 limitations...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 map...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Missing Observations 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 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, reviewa...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Missing Observations Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 testab...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 observatio...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 Pattern Recognition Missing Observations 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 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 wi...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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, owners...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 explici...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition 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: pattern recognition 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 ha...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Missing Observations Source Research And Provenance LedgerUse when a decision depends on current, source-grounded information for Pattern recognition and applied machine learning: pattern recognition 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 Pattern Recognition 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: pattern recognition 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 Pattern Recognition Multiple Comparisons 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 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 wit...Votes: 0GitHub stars: 2
- Patternlab Pattern Recognition Multiple Comparisons Design BlueprintUse when a solution needs a coherent structure before implementation or production for Pattern recognition and applied machine learning: pattern recognition 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 bu...Votes: 0GitHub stars: 2