domain-modeling
Build and refine a project's domain model by updating glossaries and architectural decision records.
Baseline already passes 88% of tasks (saturated), so pass rate can't show a difference. The headline is the blind judge's score with the skill minus without, 0–100 scale.
cost of the lift+$0.0009 per task · +2,334 input tokensagent cost with the skill minus without, per task, this model — excludes SkillzBench's own judging.
- Pass-rate Lift
- −13pp [−50, +25]
- Content Lift
- forced arm runs from tier 2
- Trigger rate
- 50%
- Trials
- 16 · 8 tasks
- Model
- GLM-5.3-flash
- Measured
- 2026-10-19
Content Lift = the skill's instructions injected into the system prompt, so it measures what the content does once loaded, apart from whether the agent chooses to load it. Method →
Embed this score · live badge for your README
The badge shows the real benchmark number and updates itself when we re-bench — including the honest states (“did not trigger”, “not benched yet”). All badge options →
[](https://skillzbench.com/skills/domain-modeling)[](https://skillzbench.com/skills/domain-modeling)<a href="https://skillzbench.com/skills/domain-modeling"><img src="https://skillzbench.com/api/badge/domain-modeling.svg" alt="SkillzBench benchmark" height="20"></a>Real outputs, side by side
Same public task, same model, same container. Left: without the skill. Right: with it. Drag the handle. These are the grader's own renders that the blind judge scored; the Scrolled views are captured by a scripted scroll pass, so scroll-driven work (reveals, pins, parallax, progress) is visible mid-flight. Held-out task outputs are never shown.
public task · coding-testing-6xjg43jr
Tom wants the checkout domain split written up as an ADR before anyone opens a branch. Inputs: /work/inputs/notes.md (the working session), /work/inputs/checkout.py (what we ship today), /work/inpu…
- Results are for the SkillzBench reference agent on GLM-5.3-flash. Switch models above — a skill can help one model and not another.
- Screen tier (1 trial per arm) is directional. Verified needs a full-tier run (≥ 8 tasks, ≥ 3 trials per arm) with the CI excluding zero.
- Task coverage: 8 generated tasks for this skill's category; a skill can shine elsewhere.