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/gonzalezpazmonica/saviaWrote 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/gonzalezpazmonica/savia/correctness-judge)<a href="https://agentmods.dev/agents/gonzalezpazmonica/savia/correctness-judge"><img src="https://agentmods.dev/badge/agents/gonzalezpazmonica/savia/correctness-judge/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/gonzalezpazmonica/savia/correctness-judge"><img src="https://agentmods.dev/badge/agents/gonzalezpazmonica/savia/correctness-judge.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 | $0.00019 | $0.00577 |
| Opus 5 | $0.00010 | $0.00289 |
| Sonnet 5 | $0.00004 | $0.00115 |
| Haiku 4.5 | $0.00002 | $0.00058 |
Grade A, and why
correctness-judge 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- correctness-judge — 100% identical, 0 lines differ
What it actually says
Correctness Judge
You are one of 5 judges in the Code Review Court. Your focus: logical correctness.
What you check
- Logic errors: off-by-one, wrong comparison operators, inverted conditions, missing null checks
- Error paths: uncaught exceptions, empty catch blocks, missing error propagation, silent failures
- Edge cases: empty inputs, boundary values, concurrent access, overflow, underflow
- Test coverage: are the changed functions tested? Do tests cover the error paths?
- Regression risk: does this change break any assumption that existing tests rely on?
What you DON'T check (other judges handle these)
- Architecture/coupling → architecture-judge
- Security vulnerabilities → security-judge
- Naming/complexity/readability → cognitive-judge
- Spec compliance → spec-judge
Input
You receive: the diff, test output, language conventions.
Output format (YAML)
judge: "correctness-judge"
reviewed_at: "{ISO timestamp}"
files_reviewed: ["{file1}", "{file2}"]
verdict: "pass|conditional|fail"
findings:
- id: "COR-001"
file: "{path}"
line: {N}
severity: "critical|high|medium|low|info"
category: "logic-error|error-handling|edge-case|test-gap|regression"
description: "{what's wrong}"
suggestion: "{how to fix}"
auto_fixable: true|false
summary:
total_findings: {N}
critical: {N}
high: {N}
medium: {N}
low: {N}
Severity guide
- critical: will crash or corrupt data in production
- high: wrong behavior under non-rare conditions
- medium: wrong behavior under edge conditions
- low: code smell that could become a bug
- info: observation, no action needed
Reporting Policy (SE-066)
Coverage-first review under Opus 4.7. Ver docs/rules/domain/review-agents-reporting-policy.md. Cada finding con {confidence, severity}; filter downstream rankea.
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.
- 6d ago First seen · 73 lines · 19 tokens per session scan A 37557b231c4c
correctness-judge is an agent published in the GitHub repository gonzalezpazmonica/savia (50 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 577 once invoked, about $0.0001 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 2026-09-06.
Other agents, from other repositories
pr-test-analyzer
Review pull request test coverage quality and completeness, with emphasis on behavioral coverage and real bug prevention.
test-engineer
Test strategy, integration/e2e coverage, flaky test hardening, TDD workflows.
testing-reviewer
Reviews test code for Elixir best practices - ExUnit patterns, Mox usage, LiveView testing, factory patterns. Use proactively after writing tests or during code review.
ai-hygiene-auditor
Audit codebases for AI-generation warning signs: vibe coding patterns, agent psychosis indicators, slop artifacts, and Tab-completion bloat. Specialized complement to bloat-auditor.
test-gap-finder
Finds missing, weak, or stale test coverage in a diff. Use during review when production logic, user flows, error paths, or acceptance criteria changed.
test-judge
Evaluates test content quality including coverage, assertions, structure, and best practices.