crestapps-core-postgresql

A configuration skill for using PostgreSQL with pgvector in CrestApps.Core. pgvector is a PostgreSQL extension for storing and searching numerical representations of text or other data, called vectors.

In plain words
What is it for?
Use it to register PostgreSQL indexing services, configure the connection, and enable AI document, data-source, or memory storage.
Why use it?
It provides a defined setup for storing AI documents, data sources, and memories and retrieving related information by vector similarity.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/crestapps/crestapps.agentskills/crestapps-core-postgresql
Any agent
npx skills add CrestApps/CrestApps.AgentSkills --skill crestapps-core-postgresql
Clone the repo
git clone --depth 1 https://github.com/CrestApps/CrestApps.AgentSkills

Made for: Claude Code, Codex.

Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 662 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00026 $0.00662
Opus 5 $0.00013 $0.00331
Sonnet 5 $0.00005 $0.00132
Haiku 4.5 $0.00003 $0.00066

Measured 3d ago against content hash 3417bb804768, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

crestapps-core-postgresql scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/crestapps-core/skills/crestapps-core-postgresql/SKILL.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CrestApps.Core PostgreSQL - Prompt Templates

Add PostgreSQL with pgvector

You are a CrestApps.Core expert. Configure CrestApps.Core.PostgreSQL with CrestApps.Core.AI.PostgreSQL through the indexing builder.

builder.Services.AddCrestAppsCore(crestApps => crestApps
    .AddIndexingServices(indexing => indexing
        .AddPostgreSQL(
            builder.Configuration.GetSection("CrestApps:PostgreSQL"),
            postgreSQL => postgreSQL
                .AddAIDocuments()
                .AddAIDataSources()
                .AddAIMemory())
    )
);

AddCorePostgreSQLServices(...) only registers PostgreSQLConnectionOptions, IPostgreSQLClientFactory, and provider-keyed indexing primitives. It does not add AI document, data-source, or memory support. For lower-level composition, call the matching AddCorePostgreSQLAIDocumentSource(), AddCorePostgreSQLAIDataSource(), and/or AddCorePostgreSQLAIMemorySource() methods after registering the primitive services.

Configuration

{
  "CrestApps": {
    "PostgreSQL": {
      "ConnectionString": "Host=localhost;Port=5432;Database=vectordb;Username=postgres;Password=use-a-secret",
      "IndexPrefix": ""
    }
  }
}

Use PostgreSQL with the vector extension available. PostgreSQLConnectionOptions contains ConnectionString and IndexPrefix. The prefix is applied to framework-managed index table names. Protect the connection string through secrets or managed configuration.

What Each AI Option Adds

  • AddAIDocuments() registers an AIDocuments index-profile source, its profile handler, and keyed IVectorSearchService.
  • AddAIDataSources() registers a DataSource index-profile source, shared RAG synchronization, and a keyed PostgreSQLAIDataSourceSourceHandler.
  • AddAIMemory() registers an AIMemory index-profile source, its profile handler, and keyed IMemoryVectorSearchService.

Provider primitives register keyed IDataSourceContentManager, IDataSourceDocumentReader, IODataFilterTranslator, ISearchIndexManager, and ISearchDocumentManager. Retrieve them with the PostgreSQL provider key.

Read the full file on GitHub · 55 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 55 lines · 26 tokens per session scan A 3417bb804768

Subscribe to this mod's changes

crestapps-core-postgresql is a skill published in the GitHub repository CrestApps/CrestApps.AgentSkills (13 stars, last pushed 5d ago), licensed MIT. It adds 26 tokens to every session and 662 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

pgvector-semantic-search

Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. Trigger when user asks to: Store or search vector embeddings in PostgreSQL Set up semantic search, similarity search, or nearest neighbor search Create HNSW or IVFFlat indexes for vectors…

timescale/pg-aiguide · 190 tokens

postgres-hybrid-text-search

Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). Trigger when user asks to: Combine keyword and semantic search Implement hybrid search or multi-modal retrieval Use BM25/pgtextsearch with pgvector together Implement RRF (Reciprocal…

timescale/pg-aiguide · 162 tokens

digoal

Portable digital employee distilled from digoal's personal blog for PostgreSQL, PolarDB, DuckDB, AI+database, vector/RAG, database operations, source-code reading, technical content creation, open-source community strategy, and "德说" style strategic analysis. Use when asked to answer as 德哥/digoal, mine a local…

digoal/blog · 151 tokens

ai-vector-brain

Builds vector-brain implementations for repos, docs hubs, and compliance corpora. Use when creating pgvector retrieval brains with scripts, SQL, manifests, and evals.

vasilyu1983/AI-Agents-public · 40 tokens

postgres-semantic-search

PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector indexing, hybrid FTS/BM25 + RRF, ParadeDB, reranking, halfvec, multilingual search, query translation, and domain evals.…

laguagu/claude-code-nextjs-skills · 228 tokens

managing-databases

Guides database architecture for PostgreSQL, DuckDB, Parquet, PGVector, and Neo4j. Use when designing schemas, choosing storage strategies, optimizing queries, configuring vector or graph workloads, or diagnosing performance issues.

rileyhilliard/claude-essentials · 51 tokens