prompt-engineer-agent-prompts-evals
|
Works with
Claude CodeCursorCodex CLIGitHub CopilotGemini CLI
--- name: prompt-engineer-agent-prompts-evals description: | license: MIT --- # Prompt Engineer — Agent Prompts & Evals ## When to Use - Write or refactor **system/developer prompts** for agents with tools - Design **tool descriptions** and parameter schemas the model must choose correctly - Build **golden datasets** and scenario suites (multi-turn, failures, edge cases) - Implement **offline eval harnesses** and CI regression for prompts - Define **LLM-as-judge** rubrics and human calibration samples - Set **release gates** when prompts or tool lists change - Debug **wrong tool**, **looping**, or **format break** in agent traces ## When NOT to Use - General prompt patterns without agent/eval focus → `prompt-engineer` - End-to-end RAG indexing, retrieval, serving → `ai-engineer` - Jailbreak and abuse red-team engagements → `ai-redteam` - Org-wide model rollout and incident ops → `ai-lead-ops` - Token cost program across product → `ai-token-improvement-plan-engineer` - Vertical squad management and launch PM → `engineering-manager-vertical-ai-products` - Prompt/eval team management and governance → `engineering-manager-agent-prompts-evals` ## Related skills | Need | Skill | |---|---| | Broad prompt design and production guardrails | `prompt-engineer` | | RAG, agents in production code | `ai-engineer` | | Launch eval gates (manager view) | `engineering-manager-vertical-ai-products` | | Risk tier and policy | `ai-risk-governance` | | Adversarial testing | `ai-redteam` | ## Core Workflows ### 1. Agent prompt structure System vs developer messages, tools block, constraints, handoffs. **See `references/agent_system_prompts.md`.** ### 2. Eval datasets Golden sets, coverage matrix, synthetic and SME-labeled examples. **See `references/eval_dataset_design.md`.** ### 3. Harness and metrics Offline runs, pass/fail, tool accuracy, trajectory checks. **See `references/eval_harness_patterns.md`.** ### 4. Judges and rubrics LLM judge design, bias controls, human agreement. **See `references/llm_judge_rubrics.md`.** ### 5. Versioning and regression Prompt semver, baselines, CI gates, rollback. **See `references/prompt_versioning_regression.md`.** ### 6. Scenario catalog Multi-turn, tool error, refusal, escalation cases. **See `references/agent_eval_scenarios.md`.** ## Output standards - Every eval case has **input**, **expected behavior** (not always exact text), **tags** - Tool schema changes include **eval delta** in PR description - Judge rubrics published with **scoring scale** and known failure modes - No production prompt change without **baseline comparison** on golden set ## When to load references - **Prompts** → `references/agent_system_prompts.md` - **Data** → `references/eval_dataset_design.md` - **Harness** → `references/eval_harness_patterns.md` - **Judges** → `references/llm_judge_rubrics.md` - **CI** → `references/prompt_versioning_regression.md` - **Scenarios** → `references/agent_eval_scenarios.md`
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