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 yogsoth-ai/stress-test --skill confidence-calibrationgit clone --depth 1 https://github.com/yogsoth-ai/stress-testWrote 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/yogsoth-ai/stress-test/confidence-calibration)<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/confidence-calibration"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/confidence-calibration/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/yogsoth-ai/stress-test/confidence-calibration"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/confidence-calibration.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 | $0.00028 | $0.00333 |
| Opus 5.5 | $0.00011 | $0.00133 |
| Sonnet 5.5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
confidence-calibration 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 1mo 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
Confidence Calibration
Calibrates confidence based on debate progression.
Execution
Subagent — spawned via subagent-spawning/spawn-agent.
Why Subagent
Calibration requires meta-analysis of debate trajectory without being anchored to any single round's outcome. Isolated context enables objective trend assessment.
Input
- round_verdicts: All judge verdicts so far
- confidence_history: Confidence scores from each round
- budget_remaining: Rounds/searches remaining in budget
Output
- calibrated_confidence: Updated confidence in artifact viability (0.0–1.0)
- decision: escalate / continue / terminate
- reasoning: Why this decision given the trajectory
- saturation_flag: Whether debate is producing diminishing returns
Budget
One unit = one calibration assessment per round.
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |
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.
- 1mo ago First seen · 53 lines · 28 tokens per session scan A 1f8b0e844b06
confidence-calibration is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 333 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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