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Fastest route to a deployed live evaluation using a pre-built Truesight template. Use when the user wants a quick start without building judgment configs from scratch.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | bootstrap-template-evaluation |
| description | Fastest route to a deployed live evaluation using a pre-built Truesight template. Use when the user wants a quick start without building judgment configs from scratch. |
Use this skill when a pre-built template likely covers the target use case.
If template choice is ambiguous, ask one question at a time using the structured question tool (loaded per the HARD-GATE above).
Example question structure:
Which template family best matches your goal?
A) AI writing detection
B) Code quality
C) Unsure, list all templates first
Rules:
list_templates.slug.provision_template(slug).create_and_deploy_evaluation(dataset_id).api_key immediately because it is returned only once.run_eval with representative inputs.dataset_idlive_evaluation_idcreate-evaluation.list_templates requires datasets:readprovision_template requires datasets:writecreate_and_deploy_evaluation requires evaluations:write, live-evaluations:writerun_eval requires live-evaluations:executeScope what quality should be measured, convert it into one or more actionable binary evaluations, deploy those evaluations through Truesight MCP, and generate a companion skill that applies them correctly. Use when a user wants to create new evals, quality checks, guardrails, or pass/fail criteria for AI outputs.
Generate synthetic test data for LLM evaluations using dimension-based tuple expansion. Use when the user needs synthetic traces, test cases, eval datasets, or when create-evaluation needs synthetic fallback data.
Orchestrator for Truesight MCP skills. Use this when the user needs help choosing the right Truesight workflow or when intent is ambiguous across LLM evaluate, error analysis, review, templates, or evaluation creation.
Build a custom web interface for trace annotation and review. Use when users need a bespoke review surface for their workflow.
Systematically identify and categorize failure modes in evaluated traces using Truesight datasets and error-analysis tools. Use when quality issues are unclear, after major pipeline changes, or when incidents indicate drift.
Audit an existing evaluation workflow and produce severity-ranked findings with concrete next actions. Use when inheriting an eval setup, diagnosing quality regressions, or checking LLM evaluation process maturity.