Back to list
Git-Fg

architecting-prompts

by Git-Fg

1🍴 0📅 Jan 18, 2026

SKILL.md


name: architecting-prompts description: "Applies 2026 Complexity-Based Guidance standards with Attention Management, Sycophancy Prevention, and XML/Markdown decision matrix. Provides theory, patterns, and quality evaluation criteria for AI prompt design. Use when designing, optimizing, or auditing AI prompts, system instructions, or multi-stage chains. Do not use for generating prompt files, basic conversational AI, or single-step interactions." allowed-tools: [Read, Write, Edit, Glob, Grep]

Prompt Architecture & Design Standards

Operational Protocol

  1. Analyze Intent: Determine if the goal is Drafting, Optimizing, or Auditing a prompt.
  2. Consult Standards: PROACTIVELY load references/core-standards.md for Attention Management rules.
  3. Select Pattern (Signal-to-Noise Rule):
    • Markdown-First (Default): Use for 80% of tasks.
    • Hybrid XML: Use ONLY if:
      • Data Isolation (>50 lines raw data)
      • Strict Constraints (NEVER/MUST rules)
      • Internal Monologue (Complex reasoning)
  4. Apply Theory: Use references/optimization.md for refinement workflows.
  5. Verify: Apply references/quality.md gates before final output.

Core Principles (Quick Reference)

Attention Management

Use Markdown headers for hierarchy. XML tags (Max 15, No Nesting) ONLY for semantic data isolation or thinking scaffolding.

Sycophancy Prevention (Truth-First)

If user suggests flawed path → CONTRADICT immediately. No "Great idea!" or superlatives. Speak in code, files, commands.

Signal-to-Noise Rule

  • Default: Markdown (80% of prompts) - fewer tokens, Claude-native
  • Upgrade to XML/Markdown hybrid only when:
    • Data Isolation: >50 lines of raw data
    • Constraint Weight: NEVER/MUST rules that cannot be broken
    • Internal Monologue: Complex reasoning requiring step-by-step

Knowledge Index (Progressive Disclosure)

ReferencePurposeLoad When
core-standards.mdAttention, Sycophancy, Quota, XML/MD matrixALWAYS consult first
design-patterns.mdCoT, Few-Shot, Taxonomy, Structural patternsSelecting technique
optimization.mdSystematic refinement workflowImproving existing prompts
quality.mdProduction quality gatesFinal verification
anti-patterns.mdCommon mistakes to avoidPrevention
taxonomy.mdSingle vs Chain vs Meta categorizationStorage/planning
execution-protocol.mdStandard completion reportingStructured output

Design Patterns

Approved Patterns

  • Chain of Thought (CoT)
  • Few-Shot Learning
  • Structured Output
  • Constraint Encoding

Success Criteria

A prompt meets 2026 standards when:

  • Uses Markdown headers for hierarchy (default)
  • XML tags are < 15 and never nested
  • Instructions are specific, actionable, and truth-focused
  • Examples (if any) are isolated in <example> tags
  • Reasoning is isolated in <thinking> blocks (if needed)
  • Quality gate checklist is included
  • Output format is clearly specified

Note: For generating .md prompt files for Claude-to-Claude pipelines, use generating-prompts skill.

Score

Total Score

60/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

3ヶ月以内に更新がある

0/10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

0/5

Reviews

💬

Reviews coming soon