Business & Operations

Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.

Use when the user wants a quality review, interaction audit, or to test the workflow against realistic scenarios.

Use when the user wants to find problems, audit workflow quality, or get a comprehensive health check on their AI workflow.

Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.

Use the project wiki as RAG knowledge source — search wiki pages to answer codebase questions before exploring raw files

Apache Spark 4.0.2 best practices for PySpark and Scala distributed data processing

Read-only report of improvement suggestions from eval-core analysis engine

Search and recall memories from claude-mem

Memory persistence operations using claude-mem

Structured SE task evaluation using 15 benchmark definitions from claude-code-harness research

Routes data engineering tasks to the correct DE expert agent. Use when user requests data pipeline design, DAG authoring, SQL modeling, stream processing, or warehouse optimization.

Semantic / ANN vector search over a sparq RDF graph: build a memory-mapped per-term-id embedding store (.spqv), then run cosine top-k with an in-RAM HNSW, a persistent on-disk DiskANN/Vamana graph (.spqg), or an exact brute-force baseline; verbalize entities (label+type+description) for embedding, scalar/product quantize (SQ/PQ) for large stores, fuse with another ranked signal (RRF / score blend) for hybrid retrieval, run predicate-constrained (filtered) ANN over a BGP-selected dict-id mask ...

Evaluate W3C ODRL 2.2 usage-control policies over RDF with the opt-in sparq-policy crate — parse an ODRL Set/Offer/Agreement into a typed Policy of Permission/Prohibition rules (action, target, assignee, Constraint, Duty), then evaluate an access Request to a fail-closed ALLOW/DENY Decision. Use when gating a query/asset by purpose, recipient, time window, count, or a duty obligation; when mapping ODRL to the sparq-solid WAC/ACP allow-deny model; or when wiring usage control above access cont...

Use when running continuous/standing SPARQL over a live RDF triple stream with the sparq engine — sliding/tumbling time windows (RANGE/STEP), count (ROWS) windows, opt-in textual T0/MAXDELAY clauses, opt-in gap-triggered session windows, opt-in closed-window scalar aggregates, RSTREAM/ISTREAM/DSTREAM output, RSP-QL surface syntax (REGISTER STREAM, FROM NAMED WINDOW ... ON ... RANGE/STEP), and multi-window joins (WINDOW <w1>{} JOIN WINDOW <w2>{}). Covers the sparq-rsp crate's ContinuousQuery /...

Run SPARQL 1.1/1.2 queries (SELECT/ASK/CONSTRUCT/DESCRIBE) and UPDATE against the sparq RDF engine in Rust — load RDF into a sparq_core::Graph, then use sparq_engine::{query, ask, query_json, count, construct, describe, update}; covers property paths, RDF 1.2 triple terms, aggregates/subqueries, custom extension functions (query_with_functions / FunctionRegistry), prepared queries, query budgets/timeouts, named-graph dataset views, and EXPLAIN. Use when an agent or developer needs to embed/ex...

Use when adding GeoSPARQL spatial support to the sparq RDF/SPARQL engine — parsing geo:wktLiteral and geo:gmlLiteral (GML Simple-Features) geometries, calling geof: functions (distance, metricArea/metricLength/metricPerimeter/centroid, bounding coordinates, isEmpty, simplify, sf*/eh*/rcc8* DE-9IM relations, geometry/set operations, getSRID) inside SPARQL FILTER/BIND/SELECT via the sparq-engine extension-function registry, or building an R-tree GeoIndex over a Graph for within_distance / neare...

Cost-based federated SPARQL source selection + bind-vs-hash join planning over already-fetched source descriptors, plus an ANAPSID-style non-blocking streaming join with operator spill, via the opt-in sparq-fedplan crate. Use when planning a federated BGP across multiple SPARQL endpoints from their served statistics (VoID property/class partitions + mined scs: characteristic sets): deciding which sources can contribute to each triple pattern (HiBISCuS recall-safe pruning + CostFed skew-aware ...

Parse and load RDF into a sparq Graph (Turtle/N-Triples/N-Quads/TriG via sparq-core, and HDT incl. compressed .hdt.gz/.hdt.zst/.hdt.bz2 via sparq-hdt), do streaming/parallel/external-memory ingest of compressed dumps, and take cheap immutable copy-on-write Graph snapshots. Use when ingesting RDF files, choosing a loader, wiring HDT, or snapshotting a graph for serving.

Use when you need to drive the sparq RDF/SPARQL engine from the command line — load a Turtle/N-Triples/N-Quads/TriG (or HDT) file and run a SPARQL query, compare RDF triple sets, build/query memory-mapped on-disk indexes for datasets larger than RAM, materialize RDFS/OWL-RL/N3 reasoning closures, classify an OWL 2 EL ontology into its subsumption lattice, stream-ingest huge gzip/bzip2/zstd dumps, import CSV as RDF (direct mapping or R2RML), or benchmark query suites. Covers the actual `sparq-...

Use when adapting ShapeShift Labs Evidence Kit to a specific JS/TS project by deriving target-owned source lists, correctness contracts, corpus cases, fuzz generators, benchmark fixtures, source-pass plans, or evidence acceptance criteria from that project's own code, docs, tests, issues, or fetched sources.

Use when changing JS/TS package exports, startup/import cost, package size, public subpaths, dependency direction, optional peers, tree-shaking, or package-boundary tests.

Master Rust 1.75+ with modern async patterns, advanced type system