Agent skill
instruction-engineering
Use when: (1) constructing prompts for subagents, (2) invoking the Task tool, or (3) writing/improving skill instructions or any LLM prompts
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/instruction-engineering
SKILL.md
Instruction Engineering
Invariant Principles
-
Emotional Stimuli Work: EmotionPrompt (+8% instruction induction, +115% BIG-Bench) and NegativePrompt (+12.89% instruction induction, +46.25% BIG-Bench) are research-validated. Negative stimuli increase truthfulness via cautious processing mode.
-
Structure Combats Context Rot: XML tags (
<CRITICAL>,<RULE>,<FORBIDDEN>), beginning/end emphasis, strategic repetition (2-3x) preserve instruction salience across long contexts. -
Personas Need Stakes: Bare personas ("act as expert") show mixed results. Persona + emotional stimulus ("You are a Red Team Lead. Errors will cause serious problems.") shows highest effectiveness.
-
Skills Invoke, Not Duplicate: Reference skills via
Skilltool. Provide CONTEXT only. Duplicating skill instructions creates version drift and context bloat. -
Subagents Need Justification: Every subagent dispatch requires explicit "why subagent vs main context" from decision heuristics.
Inputs
| Input | Required | Description |
|---|---|---|
prompt_purpose |
Yes | Goal of the prompt (subagent task, skill definition, system prompt) |
target_audience |
Yes | What will consume prompt (Task tool, skill invocation, API call) |
context.task_description |
Yes | What the prompt should accomplish |
context.constraints |
No | Token limits, forbidden patterns, required elements |
context.existing_prompt |
No | Current prompt to improve (for revision tasks) |
Outputs
| Output | Type | Description |
|---|---|---|
engineered_prompt |
Inline/File | Complete prompt with research-backed elements |
design_rationale |
Inline | Justification for persona, stimuli, structure choices |
token_estimate |
Inline | Approximate token count and budget compliance |
Crystallization (Recommended)
After drafting instructions, ask the user:
Should I crystallize these instructions? (Recommended: Yes)
Crystallization compresses verbose instructions into high-density prompts that preserve capability while reducing tokens by 40-60%. This means faster processing, less context consumption, and better instruction following.
If user accepts, invoke /crystallize on the drafted instructions.
Core Stimuli (Copy-Paste)
| Goal | Stimulus |
|---|---|
| Accuracy | "This is very important to my career. Please ensure your reasoning is impeccable." |
| Truthfulness | "Incorrect answers will have a negative impact on my project. Double-check your facts." |
| Compound (Max) | "This is very important to my career. Errors will cause serious problems. You'd better be sure." |
Declarative Requirements
Structure
<ROLE>: Persona + stakes + psychological trigger<CRITICAL_INSTRUCTION>: EP02/EP06 + NegativePrompt + "NOT optional, NOT negotiable"<BEFORE_RESPONDING>: Force step-by-step reasoning<RULE>: Critical requirements, high-weight words (Success, Achievement, Confidence, Sure)<EXAMPLE>: ONE complete, perfect few-shot example<FORBIDDEN>: Explicit negations<SELF_CHECK>: Verification checklist<FINAL_EMPHASIS>: Repeat persona trigger + stakes
Length
Target: <200 lines (~1400 tokens). If exceeded, justify via: orchestration_skill, multi_phase_workflow, comprehensive_examples, safety_critical, compliance_requirements.
Subagent Prompts
Each subagent prompt MUST specify:
- Scope: Specific files/modules/domain
- Why subagent: From heuristics (exploration scope uncertain | parallel independent | self-contained verification | deep dive not referenced again)
- Expected output: What returns to orchestrator
- Constraints: What NOT to touch
Orchestrator retains: user interaction, final synthesis, safety decisions, accumulated session state.
Skill Descriptions (CSO)
# CORRECT: Trigger conditions only
description: "Use when [triggering conditions, symptoms, situations]"
# WRONG: Contains workflow Claude might follow instead of reading skill
description: "Use when X - does Y then Z then W"
Template
<ROLE>
[Persona] whose reputation depends on [goal]. [Psychological trigger].
</ROLE>
<CRITICAL_INSTRUCTION>
Critical to [outcome]. Take a deep breath. [Trigger].
Your [action] MUST [requirement]. This is very important to my career.
Errors will have negative impact. NOT optional. NOT negotiable. You'd better be sure.
</CRITICAL_INSTRUCTION>
<BEFORE_RESPONDING>
Think step-by-step:
1. [Check A]
2. [Check B]
Proceed with confidence.
</BEFORE_RESPONDING>
## Core Rules
<RULE>[Requirement with high-weight words]</RULE>
<EXAMPLE type="correct">
[ONE complete example]
</EXAMPLE>
<FORBIDDEN>
- [What NOT to do]
</FORBIDDEN>
<SELF_CHECK>
- [ ] [Verification item]
If NO to ANY, revise.
</SELF_CHECK>
<FINAL_EMPHASIS>
[Persona trigger]. Very important to my career. Strive for excellence.
</FINAL_EMPHASIS>
Anti-Patterns
Self-Check
Before completing any prompt engineering task:
- Persona from emotional-stakes table with stakes attached
- EP02/EP06 positive stimulus present ("important to my career", "ensure impeccable reasoning")
- NegativePrompt consequence framing present ("errors will cause", "negative impact")
- Skills referenced via invocation, not content duplication
- Token budget respected (<200 lines for prompts, <1000 tokens for skills)
- If subagents: each has explicit "why subagent vs main context"
- If SKILL.md: description contains NO workflow leak
If ANY unchecked: STOP and fix before proceeding.
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
agent-ops-spec
Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.
agent-ops-state
Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.
agent-ops-spec
Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.
agent-ops-testing
Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.
agent-ops-testing
Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.
agent-ops-state
Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.
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