timescaledb

timescaledb is a skill for Claude Code, Codex from G1Joshi/Agent-Skills. It costs 43 tokens per session (1,152 once invoked), scanned A, original, MIT.

A TimescaleDB guide for storing and querying time-series data, such as sensor readings or events, in PostgreSQL. Time-series data is recorded with timestamps and is often analyzed over time.

In plain words
What is it for?
Use it for sensor data, monitoring, historical measurements, time-based summaries, and queries that group values into intervals.
Why use it?
It helps you combine time-based measurements with ordinary relational data while continuing to use PostgreSQL and SQL.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for sensor data, monitoring, historical measurements, time-based summaries, and queries that group values into intervals.

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Install with agentmods
npx agentmods add skills/g1joshi/agent-skills/timescaledb
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.

Any agent
npx skills add G1Joshi/Agent-Skills --skill timescaledb
Clone the repo
git clone --depth 1 https://github.com/G1Joshi/Agent-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for timescaledb

README.md
[![agentmods](https://agentmods.dev/badge/skills/g1joshi/agent-skills/timescaledb/github.svg)](https://agentmods.dev/skills/g1joshi/agent-skills/timescaledb)
Your own site
<a href="https://agentmods.dev/skills/g1joshi/agent-skills/timescaledb"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/timescaledb/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for timescaledb

Your own site · 80×15
<a href="https://agentmods.dev/skills/g1joshi/agent-skills/timescaledb"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/timescaledb.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,152 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00043 $0.01152
Opus 5.5 $0.00017 $0.00461
Sonnet 5.5 $0.00009 $0.00230
Haiku 4.5 $0.00004 $0.00115

Measured 23d ago against content hash ad6ce6b71ced, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

timescaledb 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 23d 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.

skills/databases/timescaledb/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TimescaleDB

TimescaleDB is a time-series database built as an extension on top of PostgreSQL. It gives you the scale of NoSQL time-series with the reliability and tooling of Postgres.

When to Use

  • High-Velocity Time-Series on PostgreSQL: Ingesting and querying millions of metrics, IoT sensor data, and financial ticks within PostgreSQL.
  • Continuous Aggregations & Materialized Views: Automatically computing real-time 1-minute, hourly, or daily rollups as data arrives.
  • Native Columnar Compression: Reducing time-series storage footprints by 90%+ using chunk-level columnar compression.
  • Data Retention & Automated Tiering: Automatically dropping or migrating historical time-series data to cold object storage.

Quick Start

-- Convert standard table to hypertable
SELECT create_hypertable('conditions', 'time');

-- Query using standard SQL time-bucket functions
SELECT time_bucket('15 minutes', time) AS bucket,
       avg(temperature)
FROM conditions
GROUP BY bucket
ORDER BY bucket DESC;

Core Concepts

Hypertables & Automated Time Chunking

A hypertable exposes a unified SQL table interface while partitioning data into time-based chunks automatically in the background:

CREATE EXTENSION IF NOT EXISTS timescaledb;

CREATE TABLE stock_ticks (
    time TIMESTAMPTZ NOT NULL,
    symbol VARCHAR(10) NOT NULL,
    price DOUBLE PRECISION NOT NULL,
    volume INT NOT NULL
);

-- Convert to Hypertable with 1-day chunk intervals
SELECT create_hypertable('stock_ticks', 'time', chunk_time_interval => INTERVAL '1 day');

Continuous Aggregates (Real-Time Rollups)

Maintains incrementally updated aggregate views that combine historical materializations with raw live incoming data:

CREATE MATERIALIZED VIEW stock_candlestick_1h
WITH (timescaledb.continuous) AS
SELECT
    time_bucket('1 hour', time) AS bucket,
    symbol,
    first(price, time) AS open_price,
    max(price) AS high_price,
    min(price) AS low_price,
    last(price, time) AS close_price,
    sum(volume) AS total_volume
FROM stock_ticks
GROUP BY bucket, symbol;

Read the full file on GitHub · 139 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. 23d ago Changed ad6ce6b71ced
  2. 27d ago Changed · +80 lines · +22 tokens per session 98794c9e6b9f
  3. 1mo ago First seen · 59 lines · 21 tokens per session scan A 95c39f91b941

Subscribe to this mod's changes

timescaledb is a skill published in the GitHub repository G1Joshi/Agent-Skills (15 stars, last pushed 24d ago), licensed MIT. It adds 43 tokens to every session and 1,152 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.

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