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.
npx skills add j4flmao/agent-skills --skill reverse-etlgit clone --depth 1 https://github.com/j4flmao/agent-skillsWrote 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.
[](https://agentmods.dev/skills/j4flmao/agent-skills/reverse-etl)<a href="https://agentmods.dev/skills/j4flmao/agent-skills/reverse-etl"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/reverse-etl/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.
<a href="https://agentmods.dev/skills/j4flmao/agent-skills/reverse-etl"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/reverse-etl.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00127 | $0.04893 |
| Opus 5 | $0.00063 | $0.02447 |
| Sonnet 5 | $0.00025 | $0.00979 |
| Haiku 4.5 | $0.00013 | $0.00489 |
Grade A, and why
data-reverse-etl 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 560 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reverse ETL
Purpose
Sync aggregated, transformed data from a data warehouse to operational SaaS tools (CRM, marketing, support) to power customer-facing and internal operational workflows.
Agent Protocol
Trigger
Exact user phrases: "reverse ETL", "Census", "Hightouch", "Grouparoo", "operational analytics", "warehouse to SaaS", "data activation", "warehouse sync", "audience export", "sync config", "operational data", "warehouse-first", "sync identity resolution".
Input Context
Before activating, verify:
- Source warehouse (Snowflake, BigQuery, Redshift, Databricks, Postgres)
- Destination SaaS tools (Salesforce, HubSpot, Marketo, Braze, Amplitude, Zendesk, Google Ads, Facebook Audiences)
- Sync frequency (real-time, hourly, daily, batch window)
- Identity resolution strategy (unique keys, merge rules, foreign key mapping)
- Volume (rows per sync, daily active records)
- Idempotency requirements (upsert vs replace vs append)
Output Artifact
Reverse ETL pipeline config with SQL source query, sync schedule, identity mapping, and destination-specific operation config as YAML and SQL.
Response Format
# Sync configuration with identity mapping
-- Source query
-- Destination field mapping
No preamble. No postamble. No explanations. No filler/hedging/transitions. Compress output.
Completion Criteria
- Source SQL query with deduplication and incremental filtering
- Identity resolution keys defined for each destination
- Sync schedule with rate-limit awareness configured
- Destination operation mode (upsert/replace/append) specified
- Error handling with retry and alerting defined
- Data freshness SLA documented
Max Response Length
4096
Workflow
Sync Model Architecture
Reverse ETL operates in three stages:
- Source query — SQL that extracts and transforms warehouse data into the desired shape
- Identity resolution — mapping warehouse keys to destination object IDs
- Destination sync — API calls to create/update/delete records in the target system
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 560 lines · 127 tokens per session scan A 40c551755eea
data-reverse-etl is a skill published in the GitHub repository j4flmao/agent-skills (23 stars, last pushed 6d ago), licensed MIT. It adds 127 tokens to every session and 4,893 once invoked, about $0.0006 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 2026-09-03.
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