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 DataSQRL/sqrl --skill manage-connectorgit clone --depth 1 https://github.com/DataSQRL/sqrlWrote 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/datasqrl/sqrl/manage-connector)<a href="https://agentmods.dev/skills/datasqrl/sqrl/manage-connector"><img src="https://agentmods.dev/badge/skills/datasqrl/sqrl/manage-connector/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/datasqrl/sqrl/manage-connector"><img src="https://agentmods.dev/badge/skills/datasqrl/sqrl/manage-connector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00036 | $0.04263 |
| Opus 5.5 | $0.00014 | $0.01705 |
| Sonnet 5.5 | $0.00007 | $0.00853 |
| Haiku 4.5 | $0.00004 | $0.00426 |
Grade A, and why
manage-connector 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.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Creating External Connectors
Use CREATE TABLE statements with WITH clause to connect external data sources and sinks:
CREATE TABLE MyTable (
column1 TYPE,
column2 TYPE,
event_time TIMESTAMP_LTZ(3) NOT NULL METADATA FROM 'timestamp',
WATERMARK FOR event_time AS event_time - INTERVAL '1' SECOND
) WITH (
'connector' = 'connector-name',
'option1' = 'value1',
...
);
Formatting rules — always follow, never compress onto a single line:
CREATE TABLE name (on its own line; each column definition on its own line with 2-space indent;) WITH (on its own line- Each connector property goes on its own line inside
WITH (, indented 4 spaces, with spaces around=(e.g.'connector' = 'kafka-safe') - Connector options that apply to only one runtime mode (streaming vs. batch) go inside conditional mustache blocks —
{{#is_batch}} … {{/is_batch}}for batch-only options,{{^is_batch}} … {{/is_batch}}for streaming-only ones;{{#is_batch}}/{{/is_batch}}each go on their own line with no leading indent - Separate each
CREATE TABLEblock with a blank line when multiple tables appear in the same file
Connector Sources
Before writing or editing a WITH (...) clause, every time, fully read the linked documentation of the connector you are about to use for the connector specific configuration options, even when you are copying a CREATE TABLE that already exists in the project.
- kafka and kafka-safe: Read or write append-only streams from Kafka-compatible data sources. Prefer the
-safeversion which adds DLQ and smart watermark support. - upsert-kafka and upsert-kafka-safe: Read or write change streams for Kafka-compatible data sources. Prefer the
-safeversion which adds DLQ support. - filesystem: Read or write data from local and cloud storage systems.
- iceberg: Read or write data from Apache Iceberg.
- jdbc: Write data via JDBC or use for lookup joins.
- datagen: Generate synthetic data for testing.
- print: Print output to stdout for debugging.
- blackhole: Discards all output (useful for testing).
What ships with it
24 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.
- connectors/blackhole.md 193 B
- connectors/datagen.md 1.8 KB
- connectors/filesystem.md 4.1 KB
- connectors/iceberg.md 3.6 KB
- connectors/jdbc.md 2.7 KB
- connectors/kafka-safe.md 1.2 KB
- connectors/kafka.md 3.1 KB
- connectors/mysql-cdc.md 3.3 KB
- connectors/postgres-cdc.md 3.7 KB
- connectors/print.md 658 B
- connectors/sqlserver-cdc.md 2.5 KB
- connectors/upsert-kafka.md 1.8 KB
- formats/avro-confluent.md 1.5 KB
- formats/avro.md 676 B
- formats/canal.md 1.5 KB
- formats/csv.md 2.5 KB
- formats/debezium.md 2.3 KB
- formats/json.md 1.7 KB
- formats/maxwell.md 1.3 KB
- formats/ogg.md 1.2 KB
- formats/orc.md 373 B
- formats/parquet.md 768 B
- formats/protobuf.md 1.0 KB
- formats/raw.md 599 B
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.
- 3d ago Changed · +12 lines 3373ee51c939
- 11d ago First seen · 222 lines · 36 tokens per session scan A 9c726c2f4b9b
manage-connector is a skill published in the GitHub repository DataSQRL/sqrl (230 stars, last pushed yesterday), licensed Apache-2.0. It adds 36 tokens to every session and 4,263 once invoked, about $0.0001 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 2026-09-30.
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