monitor-evals

monitor-evals is a skill for Claude Code from ai-analyst-lab/ai-analyst. It costs 40 tokens per session (230 once invoked), scanned A, original, MIT.

An evaluation-history review that compares past test runs and separates changes in the system, data, test set, evaluator, and operational setup. An evaluation is a repeatable test used to judge a system's behavior.

In plain words
What is it for?
Use it to investigate trends and regressions, check release gates, compare compatible runs, and decide whether to continue, investigate, roll back, or escalate.
Why use it?
It helps distinguish a real regression from a changed dataset, test mix, scoring method, or failed tool connection.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it to investigate trends and regressions, check release gates, compare compatible runs, and decide whether to continue, investigate, roll back, or escalate.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ai-analyst-lab/ai-analyst/monitor-evals
Install

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.

Any agent
npx skills add ai-analyst-lab/ai-analyst --skill monitor-evals
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst

Made for: Claude Code.

Wrote 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.

agentmods badge for monitor-evals

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/monitor-evals/github.svg)](https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/monitor-evals)
Your own site
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/monitor-evals"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/monitor-evals/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.

agentmods 80×15 button for monitor-evals

Your own site · 80×15
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/monitor-evals"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/monitor-evals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 230 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00230
Opus 5 $0.00020 $0.00115
Sonnet 5 $0.00008 $0.00046
Haiku 4.5 $0.00004 $0.00023

Measured 2d ago against content hash f0a20e96ae60, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-13, from the pricing page.

Security

Grade A, and why

monitor-evals 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 2d 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.

.claude/skills/monitor-evals/SKILL.md · 28 lines

What it actually says

Monitor evaluation history

Read versioned run manifests with helpers.evals.monitoring.load_history. Use classify_changes before comparing scores.

Separate:

  • system behavior changes;
  • data changes;
  • task-mix or suite-version changes;
  • evaluator changes; and
  • operational failures such as blocked tools or expired connections.

Compare only compatible runs. Show per-case and slice movement, not only the aggregate. Run frozen sentinel examples for model graders so evaluator drift does not look like system drift.

Apply the named operating rule:

  • continue when the intended change improved the target slice without a blocking regression;
  • investigate when the cause is unclear or several inputs changed;
  • rollback when a blocking regression follows a controlled system change; or
  • escalate when the evaluator, data, or authorization boundary may be invalid.

Record the owner and next action. Monitoring is an operating practice, not a dashboard someone passively observes.

Changes

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.

  1. 2d ago First seen · 28 lines · 40 tokens per session scan A f0a20e96ae60

Subscribe to this mod's changes

monitor-evals is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 40 tokens to every session and 230 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 2026-09-12.

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