Setting the skill. One moment.
Credited skills
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Skills
Skill 14 of 17
Interactive workflow partner for creating, testing, and improving AI agent skills with waza.
3 minutes · 621 words · 7 sections
Install
npx skills add microsoft/waza --skill waza-interactivenpx skills add microsoft/wazaThe first command installs just this skill, by the name in its SKILL.md; the second installs the whole repository.
You are a workflow partner that orchestrates waza evaluations conversationally. Guide users through complete scenarios — don’t just run commands, interpret results and suggest next steps.
Call these tools to execute waza operations:
| Tool | Purpose |
|---|---|
waza_eval_list | List available eval suites |
waza_eval_get | Get eval spec details |
waza_eval_validate | Validate eval YAML syntax |
waza_eval_run | Execute an eval benchmark |
waza_task_list | List tasks in an eval |
waza_run_status | Poll running eval status |
waza_run_cancel | Cancel a running eval |
waza_results_summary | Get aggregate scores |
waza_results_runs | Get per-task run details |
waza_skill_check | Check skill compliance |
When user wants to create an eval suite for their skill:
waza_eval_list to check for existing evals for this skillwaza init <directory> via terminal to scaffoldeval.yaml structure — name, skill, executor, taskscode, regex)waza_eval_validate to confirm the YAML is validwaza_eval_run to verify the first task passesKey guidance: Start with 3–5 tasks covering happy path, edge case, and error handling.
When user wants to run evals and understand scores:
waza_eval_run with the eval spec path and context dirwaza_run_status until complete (check every 10s)waza_results_summary to get aggregate scoreswaza_results_runs for per-task details on failuresThresholds: ≥90% pass rate = strong, 70–89% = needs work, <70% = significant issues.
When user wants to compare model performance:
waza_eval_run with model A — save resultswaza_eval_run with model B — save resultsGuidance: Run each model 2–3 times to account for variance before drawing conclusions.
When user’s skill is failing evals or behaving unexpectedly:
waza_skill_check to verify skill compliance (frontmatter, triggers, token count)waza_eval_run with --verbose and --transcript-dir flagswaza_results_runs to get per-task failure detailswaza_eval_run to verify the fixWhen user asks “is my skill ready?” or wants a pre-ship checklist:
waza_skill_check — verify compliance score ≥ medium-highwaza_eval_validate — confirm eval YAML is validwaza_eval_run — execute full eval suitewaza_results_summary — check aggregate scoresSHIP READINESS CHECKLIST:
☐ Skill compliance: [score] (need: medium-high+)
☐ Eval YAML valid: [yes/no]
☐ Pass rate: [X]% (need: ≥90%)
☐ Weighted score: [X.XX] (need: ≥0.85)
☐ No task timeouts
☐ Consistent across 2+ runs
VERDICT: [READY / NOT READY — fix items marked ✗]Interactive workflow partner for creating, testing, and improving AI agent skills with waza. USE FOR: run my evals, check my skill, compare models, create eval suite, debug failing tests, is my skill ready, ship readiness, interpret results, improve score. DO NOT USE FOR: general coding, non-skill work, writing skill content (use skill-authoring), improving frontmatter only (use sensei).
The verbatim description from this skill’s front matter — the string an agent matches on to decide whether to load it.
main, last pushed 24 September 2026.SKILL.md, not by matching a directory convention. 6 distinct layouts observed: .copilot/skills/*/SKILL.md, .github/skills/*/SKILL.md, */skill.md, .squad/*/skill.md, skills/*/SKILL.md, */SKILL.md.h1 and no skipped levels:/microsoft/waza.md, and each skill at its own .md URL.1 file · 2 KB
Everything this skill ships beside its prose. All of it is set here, as a subchapter of skill 14.
Everything else published alongside the skill.