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Claude Skills by Manoj-11-Dahal
github.com/Manoj-11-Dahal15,860 skills0 installs0 views
- Ml Data Ops Feature Parity Recovery Readiness DrillUse when the feature transformation parity workflow needs a safe recovery, rollback, replay, or continuity check to produce a recovery-drill record for the feature-pipeline parity report with starting state, test, and observed outcome. Success means the dry-run or approved non-production drill meets the predeclared recovery target and leaves the baseline intact; the same approved fixture produces equivalent features across intended paths. Use configured search, fetch, read, browser, test, and...Votes: 0GitHub stars: 2
- Ml Data Ops Feature Parity Scenario Sensitivity MatrixUse when the feature transformation parity team needs to compare options under changing assumptions to produce a baseline-plus-scenarios matrix for the feature-pipeline parity report with assumptions and ranges. Success means the baseline is reproducible, scenario inputs are explicit, comparable units are used, and conclusions state uncertainty; the same approved fixture produces equivalent features across intended paths. Use configured search, fetch, read, browser, test, and write capabiliti...Votes: 0GitHub stars: 2
- Ml Data Ops Feature Parity Scope Intake GateUse when a new feature transformation parity request needs a bounded work scope to produce a scoped intake card for the feature-pipeline parity report. Success means owner, objective, permitted sources, acceptance condition, exclusions, and deadline are explicit; the same approved fixture produces equivalent features across intended paths. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, limit refinement to three foc...Votes: 0GitHub stars: 2
- Ml Data Ops Feature Parity Source Provenance LedgerUse when a decision about feature transformation parity depends on facts from several records or public sources to produce a source-to-claim provenance ledger for the feature-pipeline parity report. Success means each material claim has a source, version/date, location, and confidence note; the same approved fixture produces equivalent features across intended paths. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, l...Votes: 0GitHub stars: 2
- Ml Data Ops Feature Parity Threshold Rule CheckUse when a feature transformation parity decision depends on a limit, eligibility rule, policy, or target to produce a rule-check record for the feature-pipeline parity report showing source, units, boundary case, and outcome. Success means the rule source and effective date are verified, units and scope match, and borderline cases are flagged rather than auto-approved; the same approved fixture produces equivalent features across intended paths. Use configured search, fetch, read, browser, t...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Approval Evidence PacketUse when a tabular dataset snapshot lineage result is ready for a human owner to approve, reject, or redirect to produce a decision packet for the dataset-to-run lineage card containing options, evidence, risks, and open questions. Success means the decision owner, requested decision, source evidence, alternatives, uncertainty, and consequence of no action are all visible; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, br...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Change Impact TraceUse when a version, rule, source, or stakeholder change may affect tabular dataset snapshot lineage to produce a before/after change record and impact map for the dataset-to-run lineage card. Success means each material difference is tied to affected dependencies, consumers, owners, and a test or explicitly unknown impact; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, test, and write capabilities only when relev...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Closeout Handoff LedgerUse when a tabular dataset snapshot lineage work item is nearing completion, pause, or transfer to another owner to produce a closeout ledger for the dataset-to-run lineage card with status, evidence, owner, and retention state. Success means all deliverables, unresolved items, approvals, and next owners are recorded, and the stop reason is explicit; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, test, and write ...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Completeness ReconciliationUse when the tabular dataset snapshot lineage workflow receives records that must agree across sources, periods, or statuses to produce a reconciliation worksheet for the dataset-to-run lineage card with matched, unmatched, and unresolved rows. Success means counts and key fields reconcile or every variance is quantified, sourced, and left unresolved for an owner; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, te...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Exception Triage QueueUse when the tabular dataset snapshot lineage workflow has exceptions, missing evidence, or competing priorities to produce a prioritized exception queue for the dataset-to-run lineage card with evidence, owner, and next action. Success means every exception has a severity rationale, source, owner or explicit unassigned state, and a bounded next step; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, test, and write...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Recovery Readiness DrillUse when the tabular dataset snapshot lineage workflow needs a safe recovery, rollback, replay, or continuity check to produce a recovery-drill record for the dataset-to-run lineage card with starting state, test, and observed outcome. Success means the dry-run or approved non-production drill meets the predeclared recovery target and leaves the baseline intact; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, test...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Scenario Sensitivity MatrixUse when the tabular dataset snapshot lineage team needs to compare options under changing assumptions to produce a baseline-plus-scenarios matrix for the dataset-to-run lineage card with assumptions and ranges. Success means the baseline is reproducible, scenario inputs are explicit, comparable units are used, and conclusions state uncertainty; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, test, and write capab...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Scope Intake GateUse when a new tabular dataset snapshot lineage request needs a bounded work scope to produce a scoped intake card for the dataset-to-run lineage card. Success means owner, objective, permitted sources, acceptance condition, exclusions, and deadline are explicit; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, limit refinement to thre...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Source Provenance LedgerUse when a decision about tabular dataset snapshot lineage depends on facts from several records or public sources to produce a source-to-claim provenance ledger for the dataset-to-run lineage card. Success means each material claim has a source, version/date, location, and confidence note; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record eviden...Votes: 0GitHub stars: 2
- Ml Data Ops Snapshot Lineage Threshold Rule CheckUse when a tabular dataset snapshot lineage decision depends on a limit, eligibility rule, policy, or target to produce a rule-check record for the dataset-to-run lineage card showing source, units, boundary case, and outcome. Success means the rule source and effective date are verified, units and scope match, and borderline cases are flagged rather than auto-approved; the analysis points to a reproducible snapshot and unapproved fields are excluded. Use configured search, fetch, read, brows...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Approval Evidence PacketUse when a train-validation-test split integrity result is ready for a human owner to approve, reject, or redirect to produce a decision packet for the split-integrity audit containing options, evidence, risks, and open questions. Success means the decision owner, requested decision, source evidence, alternatives, uncertainty, and consequence of no action are all visible; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, b...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Change Impact TraceUse when a version, rule, source, or stakeholder change may affect train-validation-test split integrity to produce a before/after change record and impact map for the split-integrity audit. Success means each material difference is tied to affected dependencies, consumers, owners, and a test or explicitly unknown impact; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, test, and write capabilities only when rele...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Closeout Handoff LedgerUse when a train-validation-test split integrity work item is nearing completion, pause, or transfer to another owner to produce a closeout ledger for the split-integrity audit with status, evidence, owner, and retention state. Success means all deliverables, unresolved items, approvals, and next owners are recorded, and the stop reason is explicit; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, test, and write...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Completeness ReconciliationUse when the train-validation-test split integrity workflow receives records that must agree across sources, periods, or statuses to produce a reconciliation worksheet for the split-integrity audit with matched, unmatched, and unresolved rows. Success means counts and key fields reconcile or every variance is quantified, sourced, and left unresolved for an owner; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, t...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Exception Triage QueueUse when the train-validation-test split integrity workflow has exceptions, missing evidence, or competing priorities to produce a prioritized exception queue for the split-integrity audit with evidence, owner, and next action. Success means every exception has a severity rationale, source, owner or explicit unassigned state, and a bounded next step; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, test, and writ...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Recovery Readiness DrillUse when the train-validation-test split integrity workflow needs a safe recovery, rollback, replay, or continuity check to produce a recovery-drill record for the split-integrity audit with starting state, test, and observed outcome. Success means the dry-run or approved non-production drill meets the predeclared recovery target and leaves the baseline intact; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, tes...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Scenario Sensitivity MatrixUse when the train-validation-test split integrity team needs to compare options under changing assumptions to produce a baseline-plus-scenarios matrix for the split-integrity audit with assumptions and ranges. Success means the baseline is reproducible, scenario inputs are explicit, comparable units are used, and conclusions state uncertainty; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, test, and write capa...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Scope Intake GateUse when a new train-validation-test split integrity request needs a bounded work scope to produce a scoped intake card for the split-integrity audit. Success means owner, objective, permitted sources, acceptance condition, exclusions, and deadline are explicit; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, limit refinement to thr...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Source Provenance LedgerUse when a decision about train-validation-test split integrity depends on facts from several records or public sources to produce a source-to-claim provenance ledger for the split-integrity audit. Success means each material claim has a source, version/date, location, and confidence note; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evide...Votes: 0GitHub stars: 2
- Ml Data Ops Split Leakage Threshold Rule CheckUse when a train-validation-test split integrity decision depends on a limit, eligibility rule, policy, or target to produce a rule-check record for the split-integrity audit showing source, units, boundary case, and outcome. Success means the rule source and effective date are verified, units and scope match, and borderline cases are flagged rather than auto-approved; no prohibited entity or future information crosses the declared evaluation boundary. Use configured search, fetch, read, brow...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Approval Evidence PacketUse when a target-label definition quality result is ready for a human owner to approve, reject, or redirect to produce a decision packet for the target-label specification containing options, evidence, risks, and open questions. Success means the decision owner, requested decision, source evidence, alternatives, uncertainty, and consequence of no action are all visible; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser,...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Change Impact TraceUse when a version, rule, source, or stakeholder change may affect target-label definition quality to produce a before/after change record and impact map for the target-label specification. Success means each material difference is tied to affected dependencies, consumers, owners, and a test or explicitly unknown impact; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, and write capabilities only when relevant an...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Closeout Handoff LedgerUse when a target-label definition quality work item is nearing completion, pause, or transfer to another owner to produce a closeout ledger for the target-label specification with status, evidence, owner, and retention state. Success means all deliverables, unresolved items, approvals, and next owners are recorded, and the stop reason is explicit; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, and write capabi...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Completeness ReconciliationUse when the target-label definition quality workflow receives records that must agree across sources, periods, or statuses to produce a reconciliation worksheet for the target-label specification with matched, unmatched, and unresolved rows. Success means counts and key fields reconcile or every variance is quantified, sourced, and left unresolved for an owner; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, an...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Exception Triage QueueUse when the target-label definition quality workflow has exceptions, missing evidence, or competing priorities to produce a prioritized exception queue for the target-label specification with evidence, owner, and next action. Success means every exception has a severity rationale, source, owner or explicit unassigned state, and a bounded next step; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, and write capab...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Recovery Readiness DrillUse when the target-label definition quality workflow needs a safe recovery, rollback, replay, or continuity check to produce a recovery-drill record for the target-label specification with starting state, test, and observed outcome. Success means the dry-run or approved non-production drill meets the predeclared recovery target and leaves the baseline intact; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, and ...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Scenario Sensitivity MatrixUse when the target-label definition quality team needs to compare options under changing assumptions to produce a baseline-plus-scenarios matrix for the target-label specification with assumptions and ranges. Success means the baseline is reproducible, scenario inputs are explicit, comparable units are used, and conclusions state uncertainty; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, and write capabilitie...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Scope Intake GateUse when a new target-label definition quality request needs a bounded work scope to produce a scoped intake card for the target-label specification. Success means owner, objective, permitted sources, acceptance condition, exclusions, and deadline are explicit; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, limit refinement to three focu...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Source Provenance LedgerUse when a decision about target-label definition quality depends on facts from several records or public sources to produce a source-to-claim provenance ledger for the target-label specification. Success means each material claim has a source, version/date, location, and confidence note; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, li...Votes: 0GitHub stars: 2
- Ml Data Ops Target Quality Threshold Rule CheckUse when a target-label definition quality decision depends on a limit, eligibility rule, policy, or target to produce a rule-check record for the target-label specification showing source, units, boundary case, and outcome. Success means the rule source and effective date are verified, units and scope match, and borderline cases are flagged rather than auto-approved; the target can be assigned consistently and ambiguous cases remain unresolved. Use configured search, fetch, read, browser, te...Votes: 0GitHub stars: 2
- Schema Change Consumer Impact WalkthroughUse when a schema or API field is added, removed, renamed, or constrained to create or update a consumer map with compatibility test cases. Use the configured search, fetch, read, browser, and test capabilities only when available and authorized. Success criterion: all known consumers and wire-format boundaries have an explicit pass or migration action. Preserve evidence and a run record, limit rework to three meaningful passes, and obtain approval before externally visible or irreversible wr...Votes: 0GitHub stars: 2
- Timestamp Timezone Normalization Edge AuditUse when an event pipeline or report converts timestamps between representations to create or update a timestamp test matrix with normalized instants and displayed dates. Use the configured search, fetch, read, browser, and test capabilities only when available and authorized. Success criterion: serialized instants remain stable and displayed local dates follow the stated zone. Preserve evidence and a run record, limit rework to three meaningful passes, and obtain approval before externally v...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Approval Evidence PacketUse when a SQL query-plan regression result is ready for a human owner to approve, reject, or redirect to produce a decision packet for the query-plan baseline comparison containing options, evidence, risks, and open questions. Success means the decision owner, requested decision, source evidence, alternatives, uncertainty, and consequence of no action are all visible; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Change Impact TraceUse when a version, rule, source, or stakeholder change may affect SQL query-plan regression to produce a before/after change record and impact map for the query-plan baseline comparison. Success means each material difference is tied to affected dependencies, consumers, owners, and a test or explicitly unknown impact; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, and write capabilities only when relevant a...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Closeout Handoff LedgerUse when a SQL query-plan regression work item is nearing completion, pause, or transfer to another owner to produce a closeout ledger for the query-plan baseline comparison with status, evidence, owner, and retention state. Success means all deliverables, unresolved items, approvals, and next owners are recorded, and the stop reason is explicit; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, and write capab...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Completeness ReconciliationUse when the SQL query-plan regression workflow receives records that must agree across sources, periods, or statuses to produce a reconciliation worksheet for the query-plan baseline comparison with matched, unmatched, and unresolved rows. Success means counts and key fields reconcile or every variance is quantified, sourced, and left unresolved for an owner; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, a...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Exception Triage QueueUse when the SQL query-plan regression workflow has exceptions, missing evidence, or competing priorities to produce a prioritized exception queue for the query-plan baseline comparison with evidence, owner, and next action. Success means every exception has a severity rationale, source, owner or explicit unassigned state, and a bounded next step; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, and write capa...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Recovery Readiness DrillUse when the SQL query-plan regression workflow needs a safe recovery, rollback, replay, or continuity check to produce a recovery-drill record for the query-plan baseline comparison with starting state, test, and observed outcome. Success means the dry-run or approved non-production drill meets the predeclared recovery target and leaves the baseline intact; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, and...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Scenario Sensitivity MatrixUse when the SQL query-plan regression team needs to compare options under changing assumptions to produce a baseline-plus-scenarios matrix for the query-plan baseline comparison with assumptions and ranges. Success means the baseline is reproducible, scenario inputs are explicit, comparable units are used, and conclusions state uncertainty; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, and write capabiliti...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Scope Intake GateUse when a new SQL query-plan regression request needs a bounded work scope to produce a scoped intake card for the query-plan baseline comparison. Success means owner, objective, permitted sources, acceptance condition, exclusions, and deadline are explicit; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, limit refinement to three foc...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Source Provenance LedgerUse when a decision about SQL query-plan regression depends on facts from several records or public sources to produce a source-to-claim provenance ledger for the query-plan baseline comparison. Success means each material claim has a source, version/date, location, and confidence note; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, test, and write capabilities only when relevant and authorized. Record evidence, l...Votes: 0GitHub stars: 2
- Aas Data Query Plan Regression Threshold Rule CheckUse when a SQL query-plan regression decision depends on a limit, eligibility rule, policy, or target to produce a rule-check record for the query-plan baseline comparison showing source, units, boundary case, and outcome. Success means the rule source and effective date are verified, units and scope match, and borderline cases are flagged rather than auto-approved; plan changes are attributed to the tested version and no production query is run. Use configured search, fetch, read, browser, t...Votes: 0GitHub stars: 2
- Aas Data Vector Index Identity Approval Evidence PacketUse when a vector index rebuild identity result is ready for a human owner to approve, reject, or redirect to produce a decision packet for the vector index build manifest containing options, evidence, risks, and open questions. Success means the decision owner, requested decision, source evidence, alternatives, uncertainty, and consequence of no action are all visible; the rebuilt index is attributable and retrieval differences can be tied to a changed input. Use configured search, fetch, re...Votes: 0GitHub stars: 2
- Aas Data Vector Index Identity Change Impact TraceUse when a version, rule, source, or stakeholder change may affect vector index rebuild identity to produce a before/after change record and impact map for the vector index build manifest. Success means each material difference is tied to affected dependencies, consumers, owners, and a test or explicitly unknown impact; the rebuilt index is attributable and retrieval differences can be tied to a changed input. Use configured search, fetch, read, browser, test, and write capabilities only when...Votes: 0GitHub stars: 2
- Aas Data Vector Index Identity Closeout Handoff LedgerUse when a vector index rebuild identity work item is nearing completion, pause, or transfer to another owner to produce a closeout ledger for the vector index build manifest with status, evidence, owner, and retention state. Success means all deliverables, unresolved items, approvals, and next owners are recorded, and the stop reason is explicit; the rebuilt index is attributable and retrieval differences can be tied to a changed input. Use configured search, fetch, read, browser, test, and ...Votes: 0GitHub stars: 2