ai-agents-empirical-probe-toolkit
ai-agents-empirical-probe-toolkit is an LLM evaluation & observability skill for AI agents, published by rjmurillo in the ai-agents repository on GitHub. Skillspace rates ai-agents-empirical-probe-toolkit F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.
Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.
Prove-it methods for this repo. Six recipes for runtime-contract probes, guard and threshold calibration, eval A/B, docs-vs-reality audits, reproduce-on-main CI triage, and negative-control test design, each with a worked example from repo history. Use when you say `probe the runtime contract`, `calibrate this guard`, `prove it empirically`. Do NOT use for the portability battle plan (use `ai-agents-portability-campaign`) or evidence standards (use `ai-agents-validation-and-qa`).
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 38
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- High-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- references sensitive credential env
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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