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Polygres retrieval design

Skill Evokoa/polygres-skills/plugins/polygres/skills/polygres-retrieval-design

Design and review Polygres retrieval plans across relational, graph, text, hybrid, Polygres AI Context, and existing pgvector-backed strategies. Use when a user must choose between retrieval surfaces, model graph or embedding inputs, plan Context collections or grounded RAG, migrate or coexist with an existing vector configuration, or review retrieval architecture before configuration or implementation. Do not mutate a project, run configuration commands, or write application code.From its SKILL.md

Install
npx -y skills add Evokoa/polygres-skills --skill polygres-retrieval-design

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SKILL.md

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Polygres Retrieval Design

Produce a reviewable plan before retrieval configuration or application work. This skill is advisory: it must not mutate a project directly.

Workflow

  1. Extract the user outcome, authorization, latency, freshness, and expected result shape from the prompt and inspected application. Ask only for a missing fact that changes the recommendation; representative questions are useful evidence, not a mandatory interview.
  2. Resolve project mode, then inspect the supplied schema, verified row identifiers, sample data, and existing retrieval configuration. Label missing evidence as unresolved; never infer production facts from a table or column name.
  3. Select the smallest sufficient strategy using references/strategy-selection.md. Reject an unsupported strategy rather than inventing a capability.
  4. For graph retrieval, apply references/graph-modeling.md. For an existing vector configuration, TSVector, or fuzzy retrieval, apply references/vector-and-text-design.md.
  5. For pgContext collections, point synchronization, registered filters, or Context retrieval modes, apply references/context-design.md.
  6. For multi-stage retrieval or RAG, apply references/hybrid-and-rag-plan.md.
  7. Write the result with references/plan-template.md. When called by $polygres-data-pipeline, return the selected and omitted components plus exact public-interface handoffs in a machine-readable section so the caller can continue without another interview.
  8. In a design-only request, stop before mutation. In an active data-pipeline setup, return control to the orchestrating skill; its consolidated review and approval govern the implementation.

Design rules

  • Prefer relational retrieval for exact predicates, joins, aggregates, and transactions that do not need a retrieval index.
  • For a synced project, keep exact SQL, transactions, and source mutations in the source PostgreSQL database. Use only the supported Runtime retrieval and retrieval-configuration surfaces on Polygres.
  • Treat graph, vector, text, and Context indexes and point mappings as derived project resources whose readiness and refresh behavior must be validated.
  • Use exact schema identifiers and stable row ID values from verified data. Do not use invented row IDs or fuzzy-match schema names.
  • Bound graph direction, depth, fan-out, result count, and cycle behavior.
  • Record the embedding model, dimensions, metric, input construction, and response to a dimension mismatch or empty embedding.
  • Default new semantic retrieval plans to a Polygres AI Context collection. Decide explicitly whether distinct embeddings belong as named vectors in one collection or require separate collection-level source and policy settings. Record any existing pgvector configuration that must remain compatible or needs a migration plan. Never treat those resources as interchangeable. On a synced project, use only an existing synchronized source table and embedding column; do not plan add_column or new_table on the target.
  • State TSVector language/configuration choices and fuzzy thresholds.
  • For hybrid retrieval, define stage order, provenance, deduplication, authorization, and token budget.
  • Include rebuild or reindex triggers, readiness checks, and rollback or fallback behavior.

Boundaries

  • This skill must not mutate a project, generate secrets, or claim that a plan has been applied.
  • Do not write mutating command examples. Route approved configuration work to $polygres-cli and approved Python integration to $polygres-sdk.
  • Filters are not an authorization boundary. Apply access control before data enters retrieval and again when results are resolved.
  • If required columns, stable IDs, or a usable sample are absent, make a reversible provisional recommendation when possible. Stop only when the missing evidence makes every safe recommendation invalid.

Completion

Return the completed reviewable plan, the unresolved assumptions, the recommended public-surface handoffs, and the explicit approval needed before any mutation or implementation.

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