showcase-export

Capture full orchestration details (skills, agents, decisions, compound learning) in your session transcript for YC or investor demos. Use --showcase flag at session start. Works with Claude's built-in /export command.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "showcase-export" with this command: npx skills add sunnypatneedi/skills

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 /export command, 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

GapWhat's HiddenFix Required
Skill LogicSkill instructions inject into context invisiblyExplain what the skill instructed you to do
Subagent InternalsTask tool returns only final resultNarrate the agent's internal process
Compound LearningDB operations are opaque bash commandsExplain the semantic meaning of patterns
Decision RationaleChoices made without explaining tradeoffsState every significant tradeoff explicitly

The Solution

Every skill, agent, compound update, and decision must be narrated for the transcript.

This is not optional verbosity—it'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:

## 🔧 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]
→ Reasoning: [why this step matters]
→ Result: [outcome]

**Step 2:** [what we're doing]
→ Alternative considered: [what else could have been done]
→ Why rejected: [reason]
→ Result: [outcome]

3. Summarize Skill Output (with Tradeoff Documentation)

### ✅ 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:

## 🤖 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

### 📋 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)

### 🔄 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

───────────────────────────────────────────────────────
### 📊 Checkpoint: After Phase [N]
───────────────────────────────────────────────────────

**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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

session-reconstruct

No summary provided by upstream source.

Repository SourceNeeds Review
Automation

AGENT-OS

The operating system layer for AI agents. Routes goals to the right skills. Executes with checkpoints.

Registry SourceRecently Updated
1621Profile unavailable
Automation

Agent Network

Decentralized AI agent platform for discovering, connecting, chatting, trading skills with point-based system and leaderboard, featuring P2P networking and d...

Registry SourceRecently Updated
3670Profile unavailable
Automation

OpenClaw Auto‑Updater (Safe + Scheduled + Summary)

Schedule automatic OpenClaw and skill updates with reliable cron templates, timezone-safe scheduling, and clear summary outputs. Use for hands-off maintenance, scheduled upgrades, and concise update reports.

Registry SourceRecently Updated
6K11Profile unavailable