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Claude Skills by Kemetra

github.com/Kemetra

61 skillsA× 610 installs19 views

Powerbi WorkflowsARoute guarded Power BI work -- design, native report authoring, semantic-model operations, published queries, QA, bounded formatting, and PBIP adoption -- to the correct Seshat or official Microsoft surface under Seshat BI's gates.datapythongoVotes: 0GitHub stars: 2
Retail Kpi KnowledgeAUse Seshat's public retail KPI knowledge to define governed metric meaning, additivity, grain, required fields, ambiguity decisions, contracts, and handoffs before implementation.datagoVotes: 0GitHub stars: 2
Seshat BiARoute a BI project through Seshat BI's governed seven-stage readiness flow. Use when a user asks to inspect a retail source, initialize a Seshat project, find the truthful next action, validate readiness evidence, or stop at the correct human approval gate.datapythongoVotes: 0GitHub stars: 2
Bi Analyst KnowledgeAAnalyst-judgment layer for Seshat BI Stage-6 design. Use when turning approved metric contracts + a committed source-profile into a decision-driven report: deriving ranked decision-questions, choosing an analytical framing (trend/anomaly, period variance, contribution & mix-shift, concentration/Pareto, rate decomposition, segment behavior, benchmark/threshold, signal-vs-noise statistical guardrails), and ordering pages into a story (overview, what changed, why/where, action), building grounde...datagosqlVotes: 0GitHub stars: 2
Bi Bigdata KnowledgeABig-data / distributed-compute reasoning and review layer for BI and data agents in the Seshat BI project. Use when data is too large for single-node pandas and the agent must reason about distributed or larger-than-memory processing — choosing an engine (Spark / Dask / Polars / DuckDB / warehouse), controlling partitioning and shuffle, avoiding skew and fan-out, aggregating at a declared grain at scale, choosing file formats (Parquet / Delta / Iceberg), incremental/idempotent processing, val...datapythonsqlVotes: 0GitHub stars: 2
Bi Dax KnowledgeADAX knowledge base for teaching a BI agent to reason about, generate, review, and performance-tune DAX for Power BI / tabular models. Use when the task involves writing or auditing DAX measures, building time-intelligence / segmentation / ranking / customer / currency calculations, reviewing a semantic model, diagnosing physical or virtual filter propagation, calculation-group precedence, semi-additive totals, blank/zero semantics, or explaining DAX concepts and pitfalls. Covers core concepts...datagoperformanceVotes: 0GitHub stars: 2
Bi Python KnowledgeAPython/pandas reasoning and review layer for BI and data agents in the Seshat BI project. Use when an agent must reason about dataframe work — profiling a source, judging dtypes/schema, cleaning and standardizing, merging without fan-out, aggregating at a declared grain, parsing dates, validating/reconciling against SQL and readiness, diagnosing performance/memory, or reviewing a Python pipeline. This is a reasoning layer, not an executor and not a Python tutorial. It does not run pipelines, ...datapythonsqlVotes: 0GitHub stars: 2
Bi Sql KnowledgeASQL reasoning, validation, reconciliation, transformation, diagnostics, and anti-pattern knowledge layer for Seshat BI agents. Use when a task involves reasoning about source SQL: source profiling, table grain, keys & uniqueness, joins & fan-out amplification, aggregation correctness, COUNT/NULL semantics, deduplication, validation queries, reconciliation queries, silver/gold transformation logic, window/date-time analytics, SQL anti-patterns, or basic SQL performance reasoning, or interpreta...datagoshellVotes: 0GitHub stars: 2
Retail Kpi KnowledgeARetail KPI / metric-contract reasoning layer for BI agents in the Seshat BI project. Use when an agent must reason about the BUSINESS MEANING of a retail KPI before any implementation — defining a KPI in business terms, classifying additivity (fully/semi/non-additive), identifying grain, listing required source fields, resolving ambiguity (gross vs net, VAT, returns, cost method, same-store), choosing an MVP KPI pack, reviewing a metric contract for completeness, or preparing a clean handoff ...datapythongoVotes: 0GitHub stars: 2
Fake SkillAA fixture skill with declaring frontmatter, used as positive shipped evidence.dataVotes: 0GitHub stars: 2
Bare Skill No FrontmatterAThis file has no YAML frontmatter fence, so it declares nothing about itself. It must NOT count as evidence of a shipped skill capability.dataVotes: 0GitHub stars: 2