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-prior-conventionsgit 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-prior-conventions)<a href="https://agentmods.dev/skills/getsimba-ai/simba-mcp/simba-prior-conventions"><img src="https://agentmods.dev/badge/skills/getsimba-ai/simba-mcp/simba-prior-conventions/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-prior-conventions"><img src="https://agentmods.dev/badge/skills/getsimba-ai/simba-mcp/simba-prior-conventions.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 | $0.00033 | $0.00246 |
| Opus 5.5 | $0.00013 | $0.00098 |
| Sonnet 5.5 | $0.00007 | $0.00049 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
simba-prior-conventions 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
Configure prior overrides
- Read conventions before constructing any override.
- Match media priors to channels[].name and control priors to exact selected columns.
- Select one saturation anchor and one coefficient coordinate. For generalised-log human coordinates include the required curvature pairing.
- Preserve smart defaults for omitted fields. Do not claim those defaults are externally validated evidence.
- Check capabilities for explicit control priors and retain all requested settings. Refused or unsupported requests must not silently fall back.
- After creation compare resolved priors and overridden_fields to the request. Unknown fields, wrong units or inactive parameters require correction, not a claim of success.
Role availability: full/data_scientist can change priors during authorised model or recipe authoring. Narrow profiles may inspect existing evidence but stop before authoring and reconnect with full. Retain schema capability checks, exact coordinates and accepted-not-used semantics; never fit solely to repair missing prior evidence.
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 6f7e11055f8a
- 28d ago Changed · -74 lines · -27 tokens per session eb00ff746648
- 1mo ago Changed · +35 lines 5c1f803b0166
- 1mo ago First seen · 55 lines · 60 tokens per session scan A 8fe14ce40d36
simba-prior-conventions is a skill published in the GitHub repository getsimba-ai/simba-mcp (3 stars, last pushed 14d ago), licensed MIT. It adds 33 tokens to every session and 246 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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