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Bootstrap template evaluation

Skill Goodeye-Labs/truesight-mcp-skills/skills/bootstrap-template-evaluation

Agent skills for the Truesight MCP. Step-by-step workflow playbooks for scoring inputs, building live evaluations, error analysis, and the review loop. Works with Claude Code, Cursor, ChatGPT, VS Code, Windsurf, and any client that supports the agent skills standard.

Install
npx -y skills add Goodeye-Labs/truesight-mcp-skills --skill bootstrap-template-evaluation

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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.

SKILL.md

2.1 KB, as published. Nobody here has run it

Bootstrap Template Evaluation

Use this skill when a pre-built template likely covers the target use case.

Interactive Q&A protocol (mandatory)

<HARD-GATE> BEFORE the first scoping question, search for a structured question tool (e.g., `AskUserQuestion` or similar interactive widget) and load it. Use that tool for EVERY scoping question. Fall back to plain-text lettered options ONLY if no such tool exists in the environment. </HARD-GATE>

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:

  • Ask one question per message.
  • Use the structured question tool for every question. Structure each with a short header, 2-4 options with labels and descriptions, and place the recommended option first. Do not add "(Recommended)" or similar annotations to option labels.
  • Ask one follow-up only when needed.

Workflow

  1. Discover templates:
    • Call list_templates.
  2. Select template:
    • Match use case to template slug.
  3. Provision private dataset:
    • Call provision_template(slug).
  4. Deploy live evaluation:
    • Call create_and_deploy_evaluation(dataset_id).
    • Capture api_key immediately because it is returned only once.
  5. Verify:
    • Run run_eval with representative inputs.
  6. Return deployment artifacts:
    • dataset_id
    • live_evaluation_id
    • verification result

Guardrails

  • If no template fits, hand off to create-evaluation.
  • Do not skip verification after deployment.

Scopes reference

  • list_templates requires datasets:read
  • provision_template requires datasets:write
  • create_and_deploy_evaluation requires evaluations:write, live-evaluations:write
  • run_eval requires live-evaluations:execute

Keep looking

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