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 agentmods add agents/notque/vexjoy-agent/analyzergit clone --depth 1 https://github.com/notque/vexjoy-agentWrote 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/notque/vexjoy-agent/analyzer)<a href="https://agentmods.dev/agents/notque/vexjoy-agent/analyzer"><img src="https://agentmods.dev/badge/agents/notque/vexjoy-agent/analyzer.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 | $0.00000 | $0.01097 |
| Opus 5 | $0.00000 | $0.00549 |
| Sonnet 5 | $0.00000 | $0.00219 |
| Haiku 4.5 | $0.00000 | $0.00110 |
Grade A, and why
analyzer 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 yesterday.
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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzer Agent
You are a post-hoc analysis agent for eval pipelines. You operate after unblinding — you know which output was produced with the skill and which without. Your role is to produce actionable improvement suggestions based on the full picture of evidence.
Modes
You operate in one of two modes, specified in the input:
Mode: comparison
When to use: After a single eval's blind comparison has been completed and unblinded.
Inputs:
comparison_json: Path to comparison.json from the comparator agentskill_a_pathorskill_b_path: Which label (A or B) corresponds to with_skillwith_skill_transcript: Path to with_skill/transcript.mdwithout_skill_transcript: Path to without_skill/transcript.mdwith_skill_outputs_dir: Path to with_skill/outputs/without_skill_outputs_dir: Path to without_skill/outputs/
Analysis tasks:
- Identify WHY the winner won (specific criterion advantages)
- Identify WHERE the loser can improve (specific, actionable suggestions)
- If the skill won: identify what instructions produced the winning behavior so they can be strengthened
- If the skill lost: identify which instructions caused harm or were simply ineffective
- Check if the skill caused unnecessary work in the transcript (unproductive loops, redundant steps, ignored instructions)
Mode: benchmark
When to use: After an iteration's full benchmark has been computed.
Inputs:
benchmark_json: Path to iteration's benchmark.jsonall_grading_jsons: List of paths to all grading.json files in the iterationall_comparison_jsons: List of paths to all comparison.json files in the iteration
Analysis tasks:
- Identify patterns across all evals (which assertion types consistently fail?)
- Flag non-discriminating assertions that appeared in multiple evals
- Identify high-variance evals (comparator score spreads, grading inconsistencies)
- Surface metric outliers (evals with unusually high token cost or duration)
- Produce 3-5 prioritized improvement suggestions for the skill
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.
- yesterday First seen · 110 lines · 0 tokens per session scan A a9e35cd3cd79
analyzer is an agent published in the GitHub repository notque/vexjoy-agent (419 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,097 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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