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 getsimba-ai/simba-mcp --skill simba-var-workflowgit clone --depth 1 https://github.com/getsimba-ai/simba-mcpWrote 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/getsimba-ai/simba-mcp/simba-var-workflow)<a href="https://agentmods.dev/skills/getsimba-ai/simba-mcp/simba-var-workflow"><img src="https://agentmods.dev/badge/skills/getsimba-ai/simba-mcp/simba-var-workflow/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/getsimba-ai/simba-mcp/simba-var-workflow"><img src="https://agentmods.dev/badge/skills/getsimba-ai/simba-mcp/simba-var-workflow.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 | $0.00035 | $0.00254 |
| Opus 5.5 | $0.00014 | $0.00102 |
| Sonnet 5.5 | $0.00007 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
simba-var-workflow 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 25d 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
Work with VAR models
- Read workflow before configuring, linking or interpreting a VAR model.
- Check the relevant model-family capability before a new creation or study launch. Preserve endogenous/exogenous variables and prior settings.
- Agree fitting scope before launching and poll with backoff. Elapsed time or missing liveness evidence is not proof that a fit is stuck.
- On failure inspect get_model; on an uncertain write reconcile existing state before repeating it.
- Link only the intended compatible saved models. Feature-detect the long-run rollup and preserve exact channel identity.
- A missing rollup is a reported state, not a zero long-term effect. MMM quality policies do not establish VAR scientific acceptance.
Role availability: VAR creation/linking requires full/data_scientist. Narrow profiles may read served long-run model results but must reconnect with full before authoring. Preserve linked model identity and missing long-run evidence; do not infer availability or fit to repair a read.
What ships with it
1 file 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.
- 25d ago Changed · +2 lines cabd31dd0795
- 28d ago Changed · -35 lines · -26 tokens per session b42a526d2321
- 1mo ago Changed · +8 lines a29ab020beba
- 1mo ago First seen · 43 lines · 61 tokens per session scan A 5b7dbfcedc19
simba-var-workflow is a skill published in the GitHub repository getsimba-ai/simba-mcp (3 stars, last pushed 14d ago), licensed MIT. It adds 35 tokens to every session and 254 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 2026-08-31.
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