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 skills/vibeeval/vibecosystem/agent-benchmarknpx skills add vibeeval/vibecosystem --skill agent-benchmarkgit clone --depth 1 https://github.com/vibeeval/vibecosystemWrote 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/vibeeval/vibecosystem/agent-benchmark)<a href="https://agentmods.dev/skills/vibeeval/vibecosystem/agent-benchmark"><img src="https://agentmods.dev/badge/skills/vibeeval/vibecosystem/agent-benchmark.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 | $0.00039 | $0.02824 |
| Opus 5 | $0.00019 | $0.01412 |
| Sonnet 5 | $0.00008 | $0.00565 |
| Haiku 4.5 | $0.00004 | $0.00282 |
Grade A, and why
agent-benchmark 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 — 413 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Benchmark Framework
Without benchmarks, we cannot know whether agent changes improve or degrade quality. This skill defines how to measure, track, and protect agent performance.
When to Activate
- Before and after modifying any agent definition file
- When adding a new skill that an agent depends on
- Periodic quality audits (weekly/monthly)
- When a user reports degraded agent output
- Before promoting an agent from experimental to production
Core Concepts
Why Benchmarks Matter
Agent quality degrades silently. A prompt tweak that improves one response can break ten others. Without a baseline to compare against, every change is a guess. Benchmarks make quality visible and regressions detectable.
Benchmark Types
| Type | Scope | Cost | Frequency |
|---|---|---|---|
| Prompt Benchmark | Single agent, single task | Low | Every agent change |
| Task Benchmark | End-to-end scenario | Medium | Feature changes |
| Regression Suite | All critical agents | High | Weekly / before release |
Directory Structure
~/.claude/benchmarks/
fixtures/
code-reviewer/
missing-error-handling.ts # Input: code with no try/catch
sql-injection.py # Input: unparameterized query
clean-code.ts # Input: code with no issues
security-reviewer/
hardcoded-secret.ts # Input: API key in source
parameterized-query.py # Input: safe query (no findings expected)
verifier/
passing-build/ # Input: project that builds
failing-types/ # Input: project with type errors
ground-truth/
code-reviewer/
missing-error-handling.json # Expected findings
sql-injection.json # Expected findings
clean-code.json # Expected: empty findings
security-reviewer/
hardcoded-secret.json
parameterized-query.json
rubrics/
code-reviewer.md # Scoring rubric
security-reviewer.md
verifier.md
baselines/
code-reviewer-2026-03-01.json # Timestamped baseline scores
code-reviewer-2026-03-26.json
security-reviewer-2026-03-26.json
results/
run-2026-03-26T14-00.json # Latest run output
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 · 413 lines · 39 tokens per session scan A 9a931d9affc1
agent-benchmark is a skill published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 27d ago), licensed MIT. It adds 39 tokens to every session and 2,824 once invoked, about $0.0002 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 2026-09-03.
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