slashcommandcreator

name	slashcommandcreator
description	Autonomous meta-skill for creating high-quality custom slash commands using 5-phase workflow with multi-agent validation and quality gates. Use when user requests new slash command, reusable prompt automation, or wants to convert repetitive workflows into documented commands.
version	1.0.0
license	MIT

SlashCommandCreator Skill

Purpose

Create production-ready custom slash commands following ai-agents quality standards.

Triggers

• create slash command for {purpose}
• SlashCommandCreator: {description}
• design slash command that {does something}

When to Use

• User requests "create slash command for [purpose]"
• Repetitive prompts identified in workflow
• Converting manual workflows to automation
• Need reusable, documented command patterns

5-Phase Workflow

Phase 1: Discovery & Analysis

Agent Mode: Analyst

Tasks:

1. Clarify user intent: What prompt is being repeated?
2. Search existing commands: ls .claude/commands/**/*.md
3. Decision: Slash command vs skill (see decision matrix in CLAUDE.md)
4. Apply 11 thinking models from skillcreator framework
5. Document findings in .agents/analysis/slashcommand-[name]-analysis.md

Deliverable: Analysis document with recommendation

Phase 2: Design

Agent Mode: Architect

Tasks:

1. Command naming (namespace conventions)
2. Argument design:
   • Simple commands: use $ARGUMENTS
   • Complex commands: use $1, $2, $3 (positional)
3. Frontmatter schema:
   • description (trigger-based per creator-001)
   • argument-hint (if using arguments)
   • allowed-tools (if using bash commands with ! or file references with @)
   • model (opus for complex reasoning)
   • disable-model-invocation (if pure prompt template)
4. Dynamic context evaluation:
   • Bash execution (!git log --oneline -5)
   • File references (@.agents/HANDOFF.md)
5. Extended thinking evaluation:
   • Add ultrathink keyword for complex reasoning (>5 steps)
   • Token budget consideration (<31,999 tokens)

Deliverable: Design specification with frontmatter + prompt

Phase 3: Multi-Agent Validation

Agent Mode: Orchestrator (coordinates 4 agents)

Agents:

1. Security:

   • Review allowed-tools constraints
   • Flag overly permissive wildcards
   • Verify bash commands are safe

2. Architect:

   • Check for duplication (similar existing commands)
   • Verify appropriate scope (not too broad/narrow)
   • Validate namespace conventions

3. Independent-Thinker:

   • Challenge necessity: Is this really needed?
   • Propose alternatives
   • Question assumptions

4. Critic:

   • Frontmatter completeness check
   • Trigger-based description validation
   • Argument-hint clarity

Unanimous Approval Required: All 4 agents must approve.

Invocation Pattern:

# Security review
`agent_type: "project-toolkit:security"` with prompt "Review allowed-tools for command: [spec]"

# Architecture review
`agent_type: "project-toolkit:architect"` with prompt "Check for duplication: [spec]"

# Challenge necessity
`agent_type: "project-toolkit:independent-thinker"` with prompt "Is this command truly needed? [spec]"

# Frontmatter completeness
`agent_type: "project-toolkit:critic"` with prompt "Validate frontmatter completeness: [spec]"

Deliverable: Validation report with approvals or revision requests

Phase 4: Implementation

Agent Mode: Implementer

Tasks:

1. Run python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/slashcommandcreator/scripts/new_slash_command.py"
2. Create .claude/commands/[namespace]/[command].md
3. Write frontmatter + prompt body
4. Test invocation with sample arguments
5. Update command catalog (if exists)

Portable script invocations (Required): If the generated command body invokes a repo skill script, resolve the script root through a plugin-root env var. Never emit a bare .claude/skills/... path: it works only in the upstream checkout and fails silently in Claude Code and Copilot CLI plugin installs.

SCRIPTS_DIR="${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/<skill>/scripts"
python3 "$SCRIPTS_DIR/<script>.py"

See docs/SKILL-AUTHORING.md ("Portable Script Invocations") for the full rule.

Deliverable: Working slash command file

Phase 5: Quality Gates (Automatic)

Agent Mode: Implementer (automatic validation)

Tasks:

1. Run python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/slashcommandcreator/scripts/validate_slash_command.py" --path [file]
2. Fix violations if any
3. Re-run validation until exit code 0
4. Commit with conventional commit message

Deliverable: Validated slash command ready for use

Invocation Examples

SlashCommandCreator: create command for exporting Forgetful memories to JSON

SlashCommandCreator: design slash command for running security audit

create slash command that summarizes recent PR comments

Decision Matrix: Slash Command vs Skill

Use Slash Command When:

• Prompt is <200 lines
• No multi-step conditional logic
• Simple argument substitution
• No external script orchestration

Use Skill When:

• Prompt is >200 lines
• Multi-agent coordination required
• Complex scripting logic
• Requires dedicated tests

Verification/Success Criteria

Before marking complete:

• Frontmatter has description (trigger-based)
• Frontmatter has argument-hint (if uses arguments)
• Frontmatter has allowed-tools (if uses bash/file refs)
• No overly permissive wildcards in allowed-tools
• Description follows trigger-based pattern (creator-001)
• File is <200 lines (or converted to skill)
• No bare .claude/skills/... exec path in the generated command; use the portable ${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}} form (see docs/SKILL-AUTHORING.md). Verify: grep -nE '(python3?|bash|sh)[[:space:]].*\.claude/skills/[^[:space:]]+\.(py|sh)|\./\.claude/skills/[^[:space:]]+\.(py|sh)' [file] returns no match
• Passes markdownlint-cli2 validation
• Passes validate_slash_command.py validation
• Tested with sample arguments
• Committed with conventional commit message

Success Criteria:

Metric	Target
Validation	Exit code 0 from validate_slash_command.py
Testing	Command runs without errors with sample arguments
Documentation	Description clearly explains when to use command
Security	All bash/file refs have explicit allowed-tools entries

Anti-Patterns

Avoid	Why	Instead
Creating commands > 200 lines	Too complex for slash command format	Convert to a skill instead
Overly permissive allowed-tools wildcards	Security risk	List specific tools needed
Skipping multi-agent validation	Miss security, scope, or necessity issues	Run all 4 validation agents
Duplicate commands for similar purposes	Confusing discoverability	Check existing commands first
Generic description without trigger keywords	Model cannot find the command	Include specific "Use when" phrases
Restating pre-trained knowledge in the body	The model already knows Git, SOLID, and the refactoring catalog. A command body that recites them costs tokens on every invocation and buys no behavior change	Write only what the model cannot know: repo gotchas, local conventions, which gate blocks this branch
Prose the description already carries	The description is what routes the invocation; the body is loaded in full afterward. A body that only elaborates its own description was never the reason the command worked	Put the decision rule in the description, the depth behind a file the body points at
Bare .claude/skills/... exec path in a generated command	Works only upstream; fails in plugin installs	Resolve via ${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/...

A command body is progressive disclosure, so it is not billed on every request the way an always-on rule is. That makes the admission test in ../context-optimizer/references/model-context-doctrine.md the wrong gate here: apply it to always-on text, not to a command body. What does carry over is the second half of the doctrine. A body is loaded in full the moment the command runs, so length still costs, and content the model already knows still buys nothing.

Cut with the same caution the doctrine records. Eight eval runs found a rule whose full body beat its description alone in 7 of 8 runs, reversing the expected result. Content that looks like restatement can be arbitration: which principle wins here, which threshold this repo uses, which gate runs first. That is repo knowledge wearing a textbook's clothes, and cutting it unmeasured is how you lose behavior you cannot see you lost.

Quality Gates Checklist

All checks from Verification section plus:

• Multi-agent approval (security, architect, independent-thinker, critic)
• No duplication with existing commands
• Appropriate scope (not too broad/narrow)
• Frontmatter completeness validated
• Every claim in the body is something the model could not already know; generic engineering knowledge deleted or moved behind a pointer
• Body earns its length: if the description alone would route and drive the same behavior, cut the body to what it adds
• Body under 200 lines (see Anti-Patterns); past that it is a skill

Scripts

new_slash_command.py

Creates a new slash command from a template.

SCRIPTS_DIR="${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/slashcommandcreator/scripts"
python3 "$SCRIPTS_DIR/new_slash_command.py" --name <name> --description <desc>

validate_slash_command.py

Validates slash command structure and frontmatter.

SCRIPTS_DIR="${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/slashcommandcreator/scripts"
python3 "$SCRIPTS_DIR/validate_slash_command.py" <skill-dir>

References

• .agents/analysis/custom-slash-commands-research.md
• .agents/archive/planning/slashcommandcreator-skill-spec.md
• .serena/memories/slashcommand-best-practices.md