Skill Quality Engineering: The Model, a Practical Guide, and 12 Articles
An introduction to SQEM’s seven quality domains, eight principles, evidence levels, practical adoption, common questions, and the 12-article series.
Quality Analyst, Not Quality Assurance.
An introduction to SQEM’s seven quality domains, eight principles, evidence levels, practical adoption, common questions, and the 12-article series.
Connect Match, Design, Validate, Evaluate, Benchmark, Release, Observe, Regress, and Improve into a sustainable quality loop for Agent Skills.
Separate static, evaluation, runtime, and real-world evidence, and use PASS, PARTIAL, NOT_RUN, BLOCKED, and INSUFFICIENT_EVIDENCE without overclaiming.
Assess description, instruction, reference, model, and runtime changes with targeted regression evidence that catches silent Skill failures.
Bring Agent Host, Model, Tools, Environment, and Language into compatibility evidence, and separate specification compatibility from runtime compatibility.
Use a controlled with-Skill versus without-Skill comparison to determine whether an Agent Skill creates real uplift instead of treating one PASS as effectiveness evidence.
Turn Skill success criteria into executable Eval Cases, choose a suitable judge, and preserve run metadata, traces, artifacts, and limitations.
Define observable Agent Skill behavior with MUST, SHOULD, and MUST NOT, then evaluate outcomes, trajectories, artifacts, and side effects instead of fixed wording.
Test Skill routing from discovery to trigger and neighboring capability selection with positive, negative, boundary, and paraphrase cases.
Use L1 through L4 test depth and E1 through E4 evidence levels to choose how far an Agent Skill should be tested.
Use SQEM’s seven quality domains and eight principles to connect Agent Skill quality claims to evidence without hiding everything behind one score.
Break an Agent Skill into SKILL.md, metadata, references, progressive disclosure, and the runtime chain that turns a package into behavior.