Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add jaroslavsoucek-art/Giovanni/plugin install giovanniWrote 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/jaroslavsoucek-art/giovanni/calibration-report)<a href="https://agentmods.dev/skills/jaroslavsoucek-art/giovanni/calibration-report"><img src="https://agentmods.dev/badge/skills/jaroslavsoucek-art/giovanni/calibration-report/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/jaroslavsoucek-art/giovanni/calibration-report"><img src="https://agentmods.dev/badge/skills/jaroslavsoucek-art/giovanni/calibration-report.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 | $0.00029 | $0.01536 |
| Opus 5.5 | $0.00012 | $0.00614 |
| Sonnet 5.5 | $0.00006 | $0.00307 |
| Haiku 4.5 | $0.00003 | $0.00154 |
Grade A, and why
calibration-report 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 today.
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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/giovanni:calibration-report
Aggregate the previous month's shadow hypothesis outcomes into a calibration report. This command is a thin shell — the aggregation logic and the > 80% accuracy guard rail live in the giovanni:prediction-runtime agent. This file is the invocation contract.
Usage
/giovanni:calibration-report # default — previous full month
/giovanni:calibration-report --month <YYYY-MM> # explicit month
Argument syntax
| Arg | Type | Default | Meaning |
|---|---|---|---|
--month <YYYY-MM> |
parameterized date | previous full calendar month | Explicit month to aggregate. Must be in the past (no in-progress months — cohort would be incomplete). |
If --month is in the future or current month → STOP: ERROR: --month <YYYY-MM> is in the future or current. Calibration aggregates completed months only.
Pre-flight (binding — STOP on failure)
Before spawning giovanni:prediction-runtime:
- CWD check. Working directory is a Giovanni repo. Otherwise STOP.
- Agent definition present.
${CLAUDE_PLUGIN_ROOT}/agents/prediction-runtime.mdexists. Missing → STOP. - Calibration directories present.
memory/calibration/exists. (actor-scores.yamlis created on first run if missing.) Missing dir → STOP:ERROR: memory/calibration/ missing. The predictive layer hasn't been initialized. - Month boundary enforced. If
--monthis omitted, the default is the previous full calendar month (today is 2026-05-21 → default is 2026-04). If today is the 1st-2nd of a month, the previous month's cohort may still have horizon spillover from the month before — surface advisory but continue. - Cohort non-empty. If no shadow hypotheses match the month → STOP:
INFO: no hypotheses created/resolved/expired in <YYYY-MM>. Nothing to aggregate this month.Don't write an empty report. - Already-reported guard. If
memory/calibration/monthly/<YYYY-MM>.mdalready exists, surface advisory:WARN: report for <YYYY-MM> already exists. Re-run will overwrite. Proceed? [y/N]. Default = abort.
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.
- today First seen · 106 lines · 29 tokens per session scan A 71f30da8fd86
calibration-report is a skill published in the GitHub repository jaroslavsoucek-art/Giovanni (2 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 1,536 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 2026-10-17.
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