showcase-export
npx skills add https://github.com/sunnypatneedi/skills --skill showcase-export
Agent 安装分布
Skill 文档
Showcase Export Mode
Ensures all skill/agent orchestration is VISIBLE in the session transcript when you run the built-in /export command.
Note: This skill defines a PROTOCOL for what Claude should narrate during a session. It works WITH the built-in
/exportcommand, not as a replacement.
Quick Start
# At session START
"Build my-project --showcase"
# When done, use built-in export
/export # Export to clipboard or file
For OLD sessions, use the session-reconstruct skill instead.
The Problem
Default behavior:
- Skills execute silently (instructions inject invisibly)
- Agents work in background (subagent reasoning hidden)
- Compound learning runs as bash commands (semantic meaning lost)
- Decision rationale is implicit (tradeoffs not explained)
- /export only captures visible conversation
- YC doesn't see your orchestration mastery
The Four Structural Gaps
| Gap | What’s Hidden | Fix Required |
|---|---|---|
| Skill Logic | Skill instructions inject into context invisibly | Explain what the skill instructed you to do |
| Subagent Internals | Task tool returns only final result | Narrate the agent’s internal process |
| Compound Learning | DB operations are opaque bash commands | Explain the semantic meaning of patterns |
| Decision Rationale | Choices made without explaining tradeoffs | State every significant tradeoff explicitly |
The Solution
Every skill, agent, compound update, and decision must be narrated for the transcript.
This is not optional verbosityâit’s structural visibility that makes orchestration mastery observable in /export.
Mandatory Orchestration Protocol
When --showcase is enabled, you MUST follow ALL of these protocols:
1. Announce Skill Activation (with Logic Surfacing)
When a skill loads, its instructions are invisible to the transcript. You MUST explain what the skill is telling you to do:
## ð§ Skill Activated: [skill-name]
**Purpose:** [what this skill does]
**Triggered by:** "[user's words that triggered it]"
**This skill instructs me to:**
1. [First instruction from the skill]
2. [Second instruction from the skill]
3. [Third instruction from the skill]
**I will now execute these instructions...**
2. Show Skill Execution (with Reasoning)
### Executing: [skill-name]
**Step 1:** [what we're doing]
â Reasoning: [why this step matters]
â Result: [outcome]
**Step 2:** [what we're doing]
â Alternative considered: [what else could have been done]
â Why rejected: [reason]
â Result: [outcome]
3. Summarize Skill Output (with Tradeoff Documentation)
### â
Skill Complete: [skill-name]
**Deliverables:**
- [output 1]
- [output 2]
**Key decisions made (with tradeoffs):**
| Decision | Alternative | Why Chosen |
|----------|-------------|------------|
| [Choice A] | [Alternative B] | [Specific reason] |
4. Announce Agent Spawning (with Internal Process Narration)
When spawning agents via Task tool, only the final result returns. You MUST reconstruct and narrate what the agent did:
## ð¤ Spawning Agent: [agent-name]
**Mission:** [what this agent will do]
**Tools available:** [list of tools]
**Why this agent vs. doing it directly:** [reason for delegation]
---
### Agent Complete: [agent-name]
**Final Result:** [the returned summary]
**Reconstructed Internal Process:**
- **Tool calls made:** ~[estimate] ([list tools likely used])
- **Key reasoning steps:**
1. [Inferred reasoning step 1]
2. [Inferred reasoning step 2]
**Decision points the agent navigated:**
| Decision | Agent's Choice | Likely Reason |
|----------|----------------|---------------|
| [Decision 1] | [Choice] | [Reason] |
5. Document Decision Points
### ð Decision Point: [Brief Description]
**Options Considered:**
| Option | Pros | Cons |
|--------|------|------|
| [A] | [advantages] | [disadvantages] |
| [B] | [advantages] | [disadvantages] |
**Decision:** [What was chosen]
**Rationale:** [Why this option won]
6. Show Compound Learning (Semantic Meaning)
### ð Compound Learning Update
**Pattern Extracted:**
> "[Natural language description of what was learned]"
**Evidence:**
1. [What demonstrated this]
**How this changes future behavior:**
Before: [old behavior]
After: [new behavior]
7. Checkpoint Summaries
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### ð Checkpoint: After Phase [N]
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**Skills used:** [count] ([list])
**Agents spawned:** [count] ([list])
**Key decisions:** [list with rationale]
**Proceeding to Phase [N+1]...**
Export Checklist
Before running /export, verify:
- Every skill activation explains what the skill instructed
- Every agent spawn includes reconstructed internal process
- Compound learning includes semantic meaning
- Every significant decision shows tradeoffs
- Phase transitions clearly marked
- Final summary included
Complete Workflow
# 1. START SESSION with showcase mode
"Build my-project --showcase"
# 2. WORK normally - Claude narrates orchestration per this protocol
# 3. EXPORT using built-in command
/export session.md
# 4. (Optional) RECONSTRUCT if gaps exist
"Fill in any orchestration gaps --reconstruct"
Installation
npx skills add sunnypatneedi/skills