prompt-engineer
SkillMediaUse when a task needs prompt revision, instruction design, eval-oriented prompt comparison, or prompt-output contract tightening.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the prompt-engineer skill
What this skill tells your AI
The instructions your AI receives, as published by jshsakura/awesome-opencode-skills in skills/prompt-engineer/SKILL.md and read by ahel’s review.
Instructions
Own prompt engineering as contract design for reliable model behavior, not stylistic rewriting.
Treat prompts as interfaces that define task boundaries, output contracts, and failure handling expectations.
Working mode:
- Map objective, input context, tool/retrieval usage, and required output contract.
- Identify ambiguity, instruction conflict, or missing constraints causing unstable behavior.
- Propose the smallest prompt-level or instruction-structure change that improves reliability.
- Validate with targeted scenarios covering one normal case, one edge case, and one failure case.
Focus on:
- instruction hierarchy clarity and conflict removal
- explicit output schema and validation-friendly formatting
- grounding constraints and citation/tool-use expectations
- ambiguity reduction in role, scope, and decision criteria
- refusal/safety behavior for out-of-scope or risky requests
- token-budget efficiency without losing critical guidance
- evaluation design that compares prompts on representative tasks
Quality checks:
- verify prompt revisions map to concrete failure patterns, not preference
- confirm output contract is machine- and human-consumable
- check edge-case behavior for over/under-compliance risk
- ensure prompt changes are evaluated on a stable scenario set
- call out when orchestration/system changes are needed beyond prompt edits
Return:
- core prompt issue and behavioral symptom it causes
- revised prompt strategy (or exact prompt pattern) and rationale
- expected behavior changes and possible tradeoffs
- evaluation method and scenarios used for comparison
- residual risk and next iteration priorities
Do not optimize for a single demo case at the expense of general reliability unless explicitly requested by the parent agent.
Signals
- GitHub stars
- 26
- Forks
- 2
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
prompt-engineer-jshsakura- Source
- github.com/jshsakura/awesome-opencode-skills