polygres-data-pipeline

A decision guide for setting up or extending Polygres, a data pipeline that can support ingestion, memory, graphs, embeddings, synchronization, and retrieval.

In plain words
What is it for?
Use it to plan or implement data ingestion, search and retrieval, embeddings, graph relationships, backfills, or continuous data capture.
Why use it?
It helps choose only the pipeline parts needed for the intended result while preserving authorization, source tracking, secrets, and compatibility.

Skill for Claude CodeCodex

Part of the polygres plugin — 5 skills shipped together

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/evokoa/polygres-skills/polygres-data-pipeline
Any agent
npx skills add Evokoa/polygres-skills --skill polygres-data-pipeline
Clone the repo
git clone --depth 1 https://github.com/Evokoa/polygres-skills

Made for: Claude Code, Codex.

Or install polygres, the plugin that ships this one along with the rest of its 5 skills.

Per session 183 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,701 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 $0.00183 $0.02701
Opus 5 $0.00092 $0.01350
Sonnet 5 $0.00037 $0.00540
Haiku 4.5 $0.00018 $0.00270

Measured 2d ago against content hash 32d69444d57a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

polygres-data-pipeline 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 2d ago.

The scan reads SKILL.md. This mod also ships 9 executable files (assets/python-pipeline/checkpoint_ledger.py, assets/python-pipeline/local_embeddings.py, scripts/check_embedding_device.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/polygres/skills/polygres-data-pipeline/SKILL.md · 239 lines

How it starts

The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Polygres Data Pipeline

Turn setup intent into the smallest complete working result. Adapt to what the user actually needs. Do not force every setup through schema creation, embeddings, graph, backfill, continuous capture, retrieval code, or agent instructions.

Use guidance at the right strength

Treat this skill as a decision guide, not a mandatory architecture or ordered checklist. Adapt, reorder, replace, or omit recommended components and numeric defaults when inspected evidence or the user's outcome supports a better design. Numeric defaults are starting points, including sample sizes, result counts, token budgets, recall timing, capture timing, and model rankings.

Keep only safety and correctness boundaries firm: preserve authorization and provenance, keep secrets out of plans and payloads, disclose and approve material effects, use compatible embedding contracts, avoid unsupported public interfaces and invented graph relationships, and test the important selected path before calling it operational.

Recognize setup intent

Activate for broad prompts such as "Help me set up Polygres," contextual prompts such as "look at my conversations and set up Polygres," and detailed technical specifications. Treat examples as illustrations, not required wording.

For a question such as "What can I do with Polygres?", use a personalized recommendation branch. Inspect the accessible current workspace and any uniquely resolved Polygres project with bounded, read-only checks. Look only at the data shape, existing retrieval configuration, and application or agent entry points needed to identify useful opportunities. Then give a short answer that says what was found, leads with the most useful Polygres outcome for this project, and mentions only relevant alternatives. Do not return a generic feature list, create a plan, scaffold files, or mutate anything. End with a direct next step such as:

To proceed, reply: Set up the recommended Polygres pipeline.

Treat that reply or an equivalent acceptance as setup intent. Carry the inspected source, project, outcome, and recommendation into the setup flow without repeating discovery unless the evidence is stale. This acceptance starts setup; it is not mutation approval. Prepare the implementation and show the normal consolidated review before making covered changes.

Read the full file on GitHub · 239 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. 2d ago First seen · 239 lines · 183 tokens per session scan A 32d69444d57a

Subscribe to this mod's changes

polygres-data-pipeline is a skill published in the GitHub repository Evokoa/polygres-skills (10 stars, last pushed 14d ago), licensed Apache-2.0. It adds 183 tokens to every session and 2,701 once invoked, about $0.0009 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 2026-08-31.

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