| name | prompt-engineering |
| description | Structured prompt construction and quality validation for Jerry Framework. Invoke when building structured prompts, generating NPT-009/NPT-013 constraints, or scoring prompt quality. Guides users through the 5-element prompt anatomy, generates formatted constraints with XML wrapping, and scores prompts against the 7-criterion rubric. |
| version | 1.0.0 |
| allowed-tools | Read, Write, Edit, Glob, Grep |
| activation-keywords | ["/prompt-engineering","build prompt","create prompt","prompt template","NPT pattern","constraint generation","prompt quality","score prompt"] |
Prompt Engineering Skill
Version: 1.0.0
Framework: Jerry Framework v0.9.0
Constitutional Compliance: Jerry Constitution v1.0
SSOT Reference: .context/rules/prompt-quality.md, .context/rules/prompt-templates.md
Document Sections
Document Audience (Triple-Lens)
This SKILL.md serves multiple audiences:
Overview
The Prompt Engineering skill operationalizes PROJ-014 negative prompting research findings into a reusable tool for constructing high-quality structured prompts within the Jerry Framework. PROJ-014 validated that NPT-013 structured negation (NEVER + consequence + alternative) achieves 100% compliance vs 92.2% for positive-only framing (p=0.016, CONDITIONAL GO via PG-003).
Core Capabilities
- Interactive Prompt Builder: Walks users through the 5-element prompt anatomy (routing, scope, data source, quality gate, output path) producing XML-wrapped structured prompts.
- NPT Constraint Generator: Converts intent descriptions into NPT-009/NPT-013 formatted constraints with
<forbidden_actions> and <constraint> XML wrapping.
- Prompt Quality Scorer: Evaluates prompts against the 7-criterion rubric (C1 Task Specificity through C7 Positive Framing) and returns dimension scores with improvement suggestions.
NPT Format Reference
| Format | Structure | Use Case |
|---|
| NPT-009 | {PRINCIPLE} VIOLATION: NEVER {action} -- Consequence: {impact} | Agent forbidden actions, constitutional guardrails |
| NPT-013 | NEVER {action} -- Consequence: {impact}. Instead: {alternative} | Behavioral constraints, routing rules, methodology guardrails |
When to Use This Skill
Invoke /prompt-engineering when you need to:
- Build a structured Jerry prompt from scratch using the 5-element anatomy.
- Generate NPT-009 or NPT-013 formatted constraints for agent definitions, rule files, or skill documentation.
- Score an existing prompt against the 7-criterion rubric to identify quality gaps.
- Convert positive-only instructions to structured negation format per PROJ-014 findings.
- Produce XML-wrapped constraint blocks (
<forbidden_actions>, <constraint>) for agent governance YAML.
NEVER invoke this skill when:
- Task requires adversarial quality review of a deliverable -- Consequence: prompt engineering generates constraints and scores prompts, not deliverables; quality assessment of artifacts requires
/adversary with S-014 rubric scoring
- Task requires research, analysis, or root cause investigation -- Consequence: prompt engineering is a construction tool, not an analytical methodology; no research capability, no causal investigation; use
/problem-solving instead
- Task is executing an existing prompt template from
.context/rules/prompt-templates.md -- Consequence: template execution does not require prompt construction; the 5 templates are self-contained and ready to use with placeholder substitution
- Task is modifying agent definition YAML frontmatter or governance files -- Consequence: agent definition structure follows
agent-development-standards.md schema, not prompt anatomy; use direct file editing with schema validation per H-34
See Routing Disambiguation for full exclusion conditions with consequences.
Available Agents
| Agent | File | Model | Cognitive Mode | Purpose |
|---|
pe-builder | skills/prompt-engineering/agents/pe-builder.md | opus | integrative | Interactive prompt assembly -- walks user through 5 elements, generates XML-wrapped structured prompt |
pe-constraint-gen | skills/prompt-engineering/agents/pe-constraint-gen.md | sonnet | systematic | NPT pattern selector and constraint formatter -- takes intent, outputs NPT-009/NPT-013 XML blocks |
pe-scorer | skills/prompt-engineering/agents/pe-scorer.md | haiku | convergent | Prompt quality scorer -- evaluates against 7-criterion rubric, returns dimension scores + improvement suggestions |
Agent Routing Guide
| Keywords in Request | Likely Agent | Rationale |
|---|
| build, create, construct, assemble, walk me through, 5 elements | pe-builder | Interactive prompt construction with element-by-element guidance |
| constraint, NPT, forbidden, NEVER, consequence, XML, guardrail | pe-constraint-gen | Systematic constraint formatting using NPT pattern catalog |
| score, evaluate, rate, quality, rubric, dimensions, improve | pe-scorer | Convergent evaluation against 7-criterion rubric |
P-003 Compliance
All prompt engineering agents are workers, NOT orchestrators. The MAIN CONTEXT (Claude session) orchestrates the workflow.
P-003 AGENT HIERARCHY:
======================
+-------------------+
| MAIN CONTEXT | <-- Orchestrator (Claude session)
| (orchestrator) |
+-------------------+
| | |
v v v
+------+ +------+ +------+
| pe- | | pe- | | pe- | <-- Workers (max 1 level)
|build | |const | |score |
+------+ +------+ +------+
Agents CANNOT invoke other agents.
Agents CANNOT spawn subagents.
Only MAIN CONTEXT orchestrates the sequence.
Invoking an Agent
Option 1: Natural Language Request
Simply describe what you need:
"Build a prompt for researching authentication patterns for a .NET microservice"
"Generate NPT-013 constraints for a research agent that must not hallucinate sources"
"Score this prompt against the quality rubric"
"Convert these positive instructions to NPT-009 format for agent governance"
The orchestrator selects the appropriate agent based on keywords and context.
Option 2: Explicit Agent Request
Request a specific agent:
"Use pe-builder to walk me through constructing a C3 orchestration prompt"
"Have pe-constraint-gen produce NPT-009 forbidden actions for a T4 research agent"
"I need pe-scorer to evaluate this prompt and tell me what to fix"
Option 3: Task Tool Invocation
For programmatic invocation within workflows:
Task(
description="pe-constraint-gen: Generate NPT-013 constraints",
subagent_type="general-purpose",
prompt="""
You are the pe-constraint-gen agent (v1.0.0).
## INPUT
- **Intent:** Prevent hallucinated source citations in a research agent
- **Target Context:** Agent governance YAML forbidden_actions
- **NPT Format:** NPT-009 (governance YAML context)
## REFERENCE
Load pattern reference: skills/prompt-engineering/rules/npt-pattern-reference.md
## TASK
Generate NPT-009 formatted constraints for the specified intent.
Persist output to: {output_path}
"""
)
Quick Reference
Build a Structured Prompt
"Build a prompt for researching authentication patterns for a .NET microservice project"
pe-builder walks through: (1) skill routing, (2) domain scope, (3) data source, (4) quality gate, (5) output path. Produces a complete XML-wrapped prompt.
Generate NPT-013 Constraints
"Generate NPT-013 constraints for a new research agent that must not hallucinate sources"
pe-constraint-gen produces XML blocks:
<forbidden_actions>
<constraint format="NPT-013">
NEVER fabricate or hallucinate source citations -- Consequence: downstream agents
build analysis on nonexistent evidence, compounding errors through the pipeline.
Instead: explicitly state when no source is available and mark confidence as low.
</constraint>
</forbidden_actions>
Score an Existing Prompt
"Score this prompt against the quality rubric:
'Research authentication patterns and write them up somewhere'"
pe-scorer returns dimension-level scores (C1-C7) with weighted composite and specific improvement suggestions per failing criterion.
Common Workflows
| Need | Agent | Example |
|---|
| Build prompt from scratch | pe-builder | "Help me build a prompt for a C3 architecture decision" |
| Generate agent guardrails | pe-constraint-gen | "Generate NPT-009 forbidden actions for a T4 research agent" |
| Convert positive to negation | pe-constraint-gen | "Convert these DOs to NPT-013 format: 'Always cite sources'" |
| Evaluate prompt quality | pe-scorer | "Score this prompt and tell me what to fix" |
| Full build-and-score cycle | pe-builder + pe-scorer | "Build a prompt for X, then score it" |
| Build, score, iterate | pe-builder + pe-scorer (loop) | "Build a prompt for X, score it, and iterate until it reaches 90+" |
End-to-End Build-Score-Iterate Workflow:
1. pe-builder constructs prompt (5-element anatomy)
2. pe-scorer evaluates prompt (7-criterion rubric)
3. If score < target: pe-builder revises based on scorer findings
4. Repeat steps 2-3 until score >= target or 3 iterations reached
Default target: >= 90 for standard prompts; adjust per prompt-quality.md threshold table. The orchestrator (main context) coordinates this loop. Agents do not call each other (P-003).
Integration Points
| Skill/Resource | Relationship | Integration Pattern |
|---|
/adversary | Distinct scope | /adversary scores deliverables against S-014 quality gate; /prompt-engineering scores prompts against the 7-criterion rubric. Different rubrics, different targets. |
/problem-solving | Consumer | ps-researcher, ps-analyst, and other agents consume prompts constructed by pe-builder. The prompt quality directly affects downstream research quality. |
.context/rules/prompt-templates.md | Complement | Templates provide ready-to-use prompts with placeholder substitution. pe-builder constructs new prompts when no template fits. Use templates first; invoke pe-builder when templates are insufficient. |
.context/rules/prompt-quality.md | Source rubric | pe-scorer implements the 7-criterion rubric defined in prompt-quality.md. The rubric is the SSOT; pe-scorer operationalizes it. |
Routing Disambiguation
When this skill is the wrong choice and what happens if misrouted.
| Condition | Use Instead | Consequence of Misrouting |
|---|
| Adversarial quality review of a deliverable | /adversary | Prompt engineering scores prompts against the 7-criterion rubric, not deliverables against the S-014 quality gate; wrong rubric applied, wrong scoring dimensions used |
| Research, analysis, or investigation tasks | /problem-solving | Prompt engineering constructs prompts, not research artifacts; no analytical methodology, no data source access, no root cause investigation |
| Requirements, design, or architecture work | /nasa-se | Prompt engineering produces prompts and constraints, not requirements specifications or architecture documents; wrong deliverable type |
| Executing an existing prompt template | Direct template use | Template execution requires placeholder substitution only; invoking prompt engineering adds unnecessary construction overhead to a ready-to-use artifact |
| Agent definition schema validation | /ast or direct H-34 validation | Agent governance YAML follows JSON Schema validation per H-34, not prompt quality rubric; wrong validation mechanism applied |
| Transcript parsing or meeting notes | /transcript | Prompt engineering has no audio/VTT/SRT processing capability; fundamentally different domain |
Constitutional Compliance
All agents adhere to the Jerry Constitution v1.0:
P-002 scope note: P-002 applies to pe-builder and pe-constraint-gen (output.required: true). pe-scorer supports optional file persistence (output.required: false); inline scoring output is permitted per its evaluation-only role.
| Principle | Requirement | Consequence of Violation |
|---|
| P-002 | NEVER produce transient-only output -- persist all artifacts to files | Work products lost on session end; no audit trail; downstream agents cannot reference output |
| P-003 | NEVER spawn recursive subagents -- max 1 level | Agent hierarchy violation; uncontrolled token consumption |
| P-004 | NEVER omit source attribution for generated constraints | Constraint provenance untraceable; reviewers cannot verify NPT pattern compliance |
| P-020 | NEVER override user intent -- ask before destructive ops | Unauthorized action; trust erosion |
| P-022 | NEVER deceive about actions, capabilities, or confidence | Governance undermined; quality assessment invalidated |
Architecture Notes
Design Rationale
This skill operationalizes three knowledge sources into reusable tooling:
- PROJ-014 Research Findings: NPT-013 structured negation achieves statistically significant compliance improvement over positive-only framing. The pe-constraint-gen agent encodes this finding into a systematic constraint generation workflow.
- Prompt Quality Rubric: The 7-criterion rubric from
.context/rules/prompt-quality.md is encoded as the pe-scorer evaluation framework. Scoring uses the same weighted formula: total = sum((raw_score_N / 3) * weight_N * 100).
- 5-Element Prompt Anatomy: The pe-builder agent implements the structured prompt construction pattern from
.context/rules/prompt-quality.md (routing, scope, data source, quality gate, output path).
References
| Source | Content |
|---|
.context/rules/prompt-quality.md | 7-criterion rubric, 5-element anatomy, anti-patterns |
.context/rules/prompt-templates.md | 5 copy-paste templates (research spike, implementation, orchestration, architecture, batch) |
skills/prompt-engineering/rules/npt-pattern-reference.md | NPT pattern catalog (NPT-009, NPT-013 formats) |
projects/PROJ-014-negative-prompting-research/orchestration/neg-prompting-20260227-001/phase-6/final-synthesis.md | PROJ-014 research synthesis (NPT-013 validation data: 100% vs 92.2%, p=0.016) |
projects/PROJ-014-negative-prompting-research/orchestration/neg-prompting-20260227-001/ab-testing/ab-testing-synthesis.md | A/B testing results (CONDITIONAL GO via PG-003) |
.context/rules/agent-development-standards.md | Agent definition schema, guardrails template, forbidden action format |
.context/rules/quality-enforcement.md | Quality gate SSOT, criticality levels, enforcement architecture |
projects/PROJ-006-jerry-prompt/ | PROJ-006 research: 5-element anatomy derivation, quality rubric development, template validation |
Skill Version: 1.0.0
Constitutional Compliance: Jerry Constitution v1.0
SSOT: .context/rules/prompt-quality.md, .context/rules/prompt-templates.md
Source: PROJ-014 Negative Prompting Research
Created: 2026-03-01
