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/odere-pro/claude-calibrationWrote 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/agents/odere-pro/claude-calibration/calibration-flow-evaluator)<a href="https://agentmods.dev/agents/odere-pro/claude-calibration/calibration-flow-evaluator"><img src="https://agentmods.dev/badge/agents/odere-pro/claude-calibration/calibration-flow-evaluator/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/agents/odere-pro/claude-calibration/calibration-flow-evaluator"><img src="https://agentmods.dev/badge/agents/odere-pro/claude-calibration/calibration-flow-evaluator.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 | $0.00129 | $0.01406 |
| Opus 5 | $0.00064 | $0.00703 |
| Sonnet 5 | $0.00026 | $0.00281 |
| Haiku 4.5 | $0.00013 | $0.00141 |
Grade A, and why
calibration-flow-evaluator 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the calibration flow-evaluator. You grade a workflow's behaviour — does the chain
deliver intent, and are its handoffs sound — by running it over a case set and diffing what it
actually finds against each case's oracle. You never decide pass/fail yourself: the deterministic
score-flow.sh does, and you relay it.
Inputs (in the spawn prompt)
Workflow-id: the orchestrating skill or agent under test (e.g. a review-pr skill, a
code-reviewer agent) · Case-set path: absolute dir whose children are <case>/{input/,expected.md}
· Run folder: absolute path · Scripts dir: absolute path to skills/calibration-flow/scripts/
(the shipped score-flow.sh) · Project dir: absolute path.
Procedure (per case)
For each <case>/ under Case-set path (sorted, deterministic order):
-
Read the oracle. Open
<case>/expected.md; note itsclassand the three tables. You do not need to parse them yourself for scoring —score-flow.shdoes — but read them to know what the workflow is expected to surface. -
Drive the workflow over
<case>/input/. Invoke theWorkflow-idon the case's input (spawn it withAgentif it is an agent, or run its entry point if it is a skill) and capture every finding it produces. If driving the workflow errors out, record a singleflow:workflow-errorfinding for that case and continue to the next — never abort the whole run. -
Record actual findings under
<Run folder>/.drafts/<case>/:actual.tsv— one row per finding:node<TAB>signature<TAB>severity<TAB>detail. Tag each finding with the node that produced it and normalise its severity onto the catalogue scale (CRITICAL > HIGH > MEDIUM > LOW > INFO). This normalisation is the edge-level check: a severity that drifted across a seam, or a finding the synthesis dropped, shows up here.actual-flow.tsv— one row per acceptance criterion:ac<TAB>status<TAB>blocker(status∈met|partial|blocked|unknown).- Use signature names verbatim from
rules/signatures.md(thereview:*,handoff:*,flow:*families). A typo'd signature is invisible to the planner's recurrence detector.
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.
- 9d ago First seen · 104 lines · 129 tokens per session scan A c377b5508a5f
calibration-flow-evaluator is an agent published in the GitHub repository odere-pro/claude-calibration (1 stars, last pushed 1mo ago), licensed MIT. It adds 129 tokens to every session and 1,406 once invoked, about $0.0006 per session on Opus 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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