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 init-sqrlgit 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/init-sqrl)<a href="https://agentmods.dev/skills/datasqrl/sqrl/init-sqrl"><img src="https://agentmods.dev/badge/skills/datasqrl/sqrl/init-sqrl/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/init-sqrl"><img src="https://agentmods.dev/badge/skills/datasqrl/sqrl/init-sqrl.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 | $0.00037 | $0.00627 |
| Opus 5.5 | $0.00015 | $0.00251 |
| Sonnet 5.5 | $0.00007 | $0.00125 |
| Haiku 4.5 | $0.00004 | $0.00063 |
Grade A, and why
init-sqrl 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 10d 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.
What it actually says
Follow these steps to initialize a DataSQRL project:
- When an available examples directory contains a useful starting point, review its
README.mdand relevant projects. Treat its contents as optional reference material, not required templates. - Adapt relevant example files into the working directory only when they fit the task. Don't overwrite existing files.
- Review provided source/sink table definitions in sub-folders to identify the sqrl files that define the sources and sinks required for the implementation. If the requirements reference a provided data catalog, include that catalog and delete copied connectors unless the requirements specifically ask to create additional sources/sinks outside the catalog.
- Update copied files to match user requirements by:
- ALWAYS invoke the relevant skill before updating or implementing anything
- Use user-provided source/sink definitions from sub-folders or an included data catalog if they exist (include/import them, reusing what exists), otherwise update the template connectors. Invoke the
/manage-connectorskill (Connector Organization) before writing or editing any source/sink definition. - Updating the SQRL files to use those sources & sinks and adjust implementation by matching the code to the updated table schemas and removing features that are not required. Invoke the
/implement-sqrlskill before writing or significantly modifying any SQRL logic during this step. - When renaming the main
.sqrlscript, updatescript.mainkey in the (sub-)project's base config so every package.json reference matches the actual filename before the first compile. When creating or updating any configuration, invoke/configure-sqrlskill. - Update the project configuration if necessary.
- Update the GraphQL API definition and defined operations to match the new schema.
- Create or update the configuration files: a
*-shared-package.jsonbase plus*-<env>-package.jsonthin per-environment overlays. Invoke the/configure-sqrlskill (Base Config and Environment Overlays). - Add
/*+test */annotated SQL test queries at the end of the main SQRL script(s) for each exposed table. These test queries should SELECT from the table with a WHERE filter on a known test data value and produce deterministic results. Invoke the/test-sqrlskill (Writing Tests) for the test and test-data rules, then delete the template's existing snapshots and run the tests to generate fresh ones (Running Tests, Snapshot Lifecycle). - Create or update the test runner script
run-tests.shwhich is the entry point for the project's tests. Invoke the/test-sqrlskill for details. - Update
README.mdwith user requirements and project description. Add a list of features that are required by the user but not part of the template and need to be implemented
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.
- 10d ago First seen · 22 lines · 37 tokens per session scan A 454b0f9888ce
init-sqrl is a skill published in the GitHub repository DataSQRL/sqrl (230 stars, last pushed today), licensed Apache-2.0. It adds 37 tokens to every session and 627 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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