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.
git clone --depth 1 https://github.com/stratalab/strata-coreWrote 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/commands/stratalab/strata-core/inference.rank)<a href="https://agentmods.dev/commands/stratalab/strata-core/inference.rank"><img src="https://agentmods.dev/badge/commands/stratalab/strata-core/inference.rank.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00121 |
| Opus 5 | $0.00000 | $0.00060 |
| Sonnet 5 | $0.00000 | $0.00024 |
| Haiku 4.5 | $0.00000 | $0.00012 |
Grade A, and why
inference.rank 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.
What it actually says
Scores each candidate passage against a query with a ranking model and returns one outcome per passage. Each item carries the passage's original index and either a relevance score or a per-item error with a stable code and a redacted message, so callers can reorder passages by score while keeping them tied to their inputs. Ranking is a local-only operation: it requires a build with the local execution feature and a ranking-capable model.
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 First seen · 7 lines · 0 tokens per session scan A 1e213db80eb6
inference.rank is a command published in the GitHub repository stratalab/strata-core (2 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 121 tokens. 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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vector-db
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