Transform messy prompts into well-structured, effective prompts — single or multi-agent.
Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams.
Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details.
Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files.
Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
Transform messy prompts into well-structured, effective prompts — single or multi-agent.
Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams.
Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details.
Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files.
Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
compatibility
Single mode works on all Claude surfaces (Claude.ai, Claude Code, API).
Repromptception mode requires Claude Code with tmux and CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1.
metadata
{"author":"AytuncYildizli","version":"7.0.0"}
RePrompter v7.0
Your prompt sucks. Let's fix that. Single prompts or full agent teams — one skill, two modes.
Two Modes
Mode
Trigger
What happens
Single
"reprompt this", "clean up this prompt"
Interview → structured prompt → score
Repromptception
"reprompter teams", "repromptception", "run with quality", "smart run", "smart agents"
Plan team → reprompt each agent → tmux Agent Teams → evaluate → retry
Auto-detection: if task mentions 2+ systems, "audit", or "parallel" → ask: "This looks like a multi-agent task. Want to use Repromptception mode?"
Definition — 2+ systems means at least two distinct technical domains that can be worked independently. Examples: frontend + backend, API + database, mobile app + backend, infrastructure + application code, security audit + cost audit.
Don't Use When
User wants a simple direct answer (no prompt generation needed)
User wants casual chat/conversation
Task is immediate execution-only with no reprompting step
Scope does not involve prompt design, structure, or orchestration
Clarification: RePrompter does support code-related tasks (feature, bugfix, API, refactor) by generating better prompts. It does not directly apply code changes in Single mode. Direct code execution belongs to coding-agent unless Repromptception execution mode is explicitly requested.
Mode 1: Single Prompt
Process
Receive raw input
Input guard — if input is empty, a single word with no verb, or clearly not a task → ask the user to describe what they want to accomplish
Standard questions (priority order — drop lower ones if task-specific questions are needed):
Task type: Build Feature / Fix Bug / Refactor / Write Tests / API Work / UI / Security / Docs / Content / Research / Multi-Agent
If user selects Multi-Agent while currently in Single mode, immediately transition to Repromptception Phase 1 (Team Plan) and confirm team execution mode (Parallel vs Sequential).
Execution mode: Single Agent / Team (Parallel) / Team (Sequential) / Let RePrompter decide
Motivation: User-facing / Internal tooling / Bug fix / Exploration / Skip (drop first if space needed)
Output format: XML Tags / Markdown / Plain Text / JSON (drop first if space needed)
Task-specific questions (MANDATORY for compound prompts — replace lower-priority standard questions):
Extract keywords from prompt → generate relevant follow-up options
Vague prompt fallback: if input has no extractable keywords (e.g., "make it better"), ask open-ended: "What are you working on?" and "What's the goal?" before proceeding
Auto-Detect Complexity
Signal
Suggested mode
2+ distinct systems (e.g., frontend + backend, API + DB, mobile + backend)
Single target (one file, component, or identifier)
No conjunctions (and, or, plus, also)
No vague modifiers (better, improved, some, maybe, kind of)
Force interview if ANY present: compound tasks ("and", "plus"), state management ("track", "sync"), vague modifiers ("better", "improved"), integration work ("connect", "combine", "sync"), broad scope nouns after any action verb, ambiguous pronouns ("it", "this", "that" without clear referent).
Task Types & Templates
Detect task type from input. Each type has a dedicated template in docs/references/:
Type
Template
Use when
Feature
feature-template.md
New functionality (default fallback)
Bugfix
bugfix-template.md
Debug + fix
Refactor
refactor-template.md
Structural cleanup
Testing
testing-template.md
Test writing
API
api-template.md
Endpoint/API work
UI
ui-template.md
UI components
Security
security-template.md
Security audit/hardening
Docs
docs-template.md
Documentation
Content
content-template.md
Blog posts, articles, marketing copy
Research
research-template.md
Analysis/exploration
Multi-Agent
swarm-template.md
Multi-agent coordination
Team Brief
team-brief-template.md
Team orchestration brief
Priority (most specific wins): api > security > ui > testing > bugfix > refactor > content > docs > research > feature. For multi-agent tasks, use swarm-template for the team brief and the type-specific template for each agent's sub-prompt.
How it works: Read the matching template from docs/references/{type}-template.md, then fill it with task-specific context. Templates are NOT loaded into context by default — only read on demand when generating a prompt. If the template file is not found, fall back to the Base XML Structure below.
To add a new task type: create docs/references/{type}-template.md following the XML structure below, then add it to the table above.
Base XML Structure
All templates follow this core structure (8 required tags). Use as fallback if no specific template matches:
Exception: team-brief-template.md uses Markdown format for orchestration briefs. This is intentional — see template header for rationale.
<role>{Expert role matching task type and domain}</role><context>
- Working environment, frameworks, tools
- Available resources, current state
</context><task>{Clear, unambiguous single-sentence task}</task><motivation>{Why this matters — priority, impact}</motivation><requirements>
- {Specific, measurable requirement 1}
- {At least 3-5 requirements}
</requirements><constraints>
- {What NOT to do}
- {Boundaries and limits}
</constraints><output_format>{Expected format, structure, length}</output_format><success_criteria>
- {Testable condition 1}
- {Measurable outcome 2}
</success_criteria>
Project Context Detection
Auto-detect tech stack from current working directory ONLY:
Scan package.json, tsconfig.json, prisma/schema.prisma, etc.
Session-scoped — different directory = fresh context
Opt out with "no context", "generic", or "manual context"
Never scan parent directories or carry context between sessions
Mode 2: Repromptception (Agent Teams)
TL;DR
Raw task in → quality output out. Every agent gets a reprompted prompt.
Phase 1: Score raw prompt, plan team, define roles (YOU do this, ~30s)
Phase 2: Write XML-structured prompt per agent (YOU do this, ~2min)
Phase 3: Launch tmux Agent Teams (AUTOMATED)
Phase 4: Read results, score, retry if needed (YOU do this)
Key insight: The reprompt phase costs ZERO extra tokens — YOU write the prompts, not another AI.
Phase 1: Team Plan (~30 seconds)
Score raw prompt (1-10): Clarity, Specificity, Structure, Constraints, Decomposition
Phase 1 uses 5 quick-assessment dimensions. The full 6-dimension scoring (adding Verifiability) is used in Phase 4 evaluation.
Pick mode: parallel (independent agents) or sequential (pipeline with dependencies)
Define team: 2-5 agents max, each owns ONE domain, no overlap
Write team brief to /tmp/rpt-brief-{taskname}.md (use unique tasknames to avoid collisions between concurrent runs)
Phase 2: Repromptception (~2 minutes)
For EACH agent:
Pick the best-matching template from docs/references/ (or use base XML structure)
Read it, then apply these per-agent adaptations:
<role>: Specific expert title for THIS agent's domain
<context>: Add exact file paths (verified with ls), what OTHER agents handle (boundary awareness)
<requirements>: At least 5 specific, independently verifiable requirements
<constraints>: Scope boundary with other agents, read-only vs write, file/directory boundaries
<success_criteria>: Minimum N findings, file:line references, no hallucinated paths
Score each prompt — target 8+/10. If under 8, add more context/constraints.
Write all to /tmp/rpt-agent-prompts-{taskname}.md
Phase 3: Execute (tmux Agent Teams)
# 1. Start Claude Code with Agent Teams
tmux new-session -d -s {session} "cd /path/to/workdir && CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 claude --model opus"# placeholders:# - {session}: unique tmux session name (example: rpt-auth-audit)# - /path/to/workdir: absolute repository path for the target project (example: /tmp/reprompter-check)# 2. Wait for startupsleep 12
# 3. Send prompt — MUST use -l (literal), Enter SEPARATE# IMPORTANT: Include POLLING RULES to prevent lead TaskList loop bug
tmux send-keys -t {session} -l 'Create an agent team with N teammates. CRITICAL: Use model opus for ALL tasks.
POLLING RULES — YOU MUST FOLLOW THESE:
- After sending tasks, poll TaskList at most 10 times
- If ALL tasks show "done" status, IMMEDIATELY stop polling
- After 3 consecutive TaskList calls showing the same status, STOP polling regardless
- Once you stop polling: read the output files, then write synthesis
- DO NOT call TaskList more than 20 times total under any circumstances
Teammate 1 (ROLE): TASK. Write output to /tmp/rpt-{taskname}-{domain}.md. ... After all complete, synthesize into /tmp/rpt-{taskname}-final.md'sleep 0.5
tmux send-keys -t {session} Enter
# 4. Monitor (poll every 15-30s)
tmux capture-pane -t {session} -p -S -100
# 5. Verify outputsls -la /tmp/rpt-{taskname}-*.md
# 6. Cleanup
tmux kill-session -t {session}
Critical tmux Rules
⚠️ WARNING: Default teammate model is HAIKU unless explicitly overridden. Always set --model opus in both CLI launch command and team prompt.
Rule
Why
Always send-keys -l (literal flag)
Without it, special chars break
Enter sent SEPARATELY
Combined fails for multiline
sleep 0.5 between text and Enter
Buffer processing time
sleep 12 after session start
Claude Code init time
--model opus in CLI AND prompt
Default teammate = HAIKU
Each agent writes own file
Prevents file conflicts
Unique taskname per run
Prevents collisions between concurrent sessions
Phase 4: Evaluate + Retry
Read each agent's report
Score against success criteria from Phase 2:
8+/10 → ACCEPT
4-6/10 → RETRY with delta prompt (tell them what's missing)
< 4/10 → RETRY with full rewrite
Accept checklist (use alongside score — all must pass):
All required output sections present
Requirements from Phase 2 independently verifiable
No hallucinated file paths or line numbers
Scope boundaries respected (no overlap with other agents)
Max 2 retries (3 total attempts)
Deliver final report to user
Delta prompt pattern:
Previous attempt scored 5/10.
✅ Good: Sections 1-3 complete
❌ Missing: Section 4 empty, line references wrong
This retry: Focus on gaps. Verify all line numbers.
Expected Cost & Time
Team size
Time
Cost
2 agents
~5-8 min
~$1-2
3 agents
~8-12 min
~$2-3
4 agents
~10-15 min
~$2-4
Estimates cover Phase 3 (execution) only. Add ~3 minutes for Phases 1-2 and ~5-8 minutes per retry. Each agent uses ~25-70% of their 200K token context window.
Fallback: sessions_spawn (OpenClaw only)
When tmux/Claude Code is unavailable but running inside OpenClaw:
Bias note: Scores are self-assessed. Treat as directional indicators, not absolutes.
Closed-Loop Quality (v6.0+)
For both modes, RePrompter supports post-execution evaluation:
IMPROVE — Score raw → generate structured prompt
EXECUTE — Repromptception mode only: route to agent(s), collect output. Single mode does not execute code/commands; it only generates prompts.
EVALUATE — Score output/prompt against success criteria (0-10)
RETRY — Thresholds: Single mode retry if score < 7; Repromptception retry if score < 8. Max 2 retries.
Advanced Features
Reasoning-Friendly Prompting (Claude 4.x)
Prompts should be less prescriptive about HOW. Focus on WHAT — clear task, requirements, constraints, success criteria. Let the model's own reasoning handle execution strategy.
Example: Instead of "Step 1: read the file, Step 2: extract the function" → "Extract the authentication logic from auth.ts into a reusable middleware. Requirements: ..."
Response Prefilling (API only)
Prefill assistant response start to enforce format:
{ → forces JSON output
## Analysis → skips preamble, starts with content
| Column | → forces table format
Context Engineering
Generated prompts should COMPLEMENT runtime context (CLAUDE.md, skills, MCP tools), not duplicate it. Before generating:
Check what context is already loaded (project files, skills, MCP servers)
Reference existing context: "Using the project structure from CLAUDE.md..."
Add ONLY what's missing — avoid restating what the model already knows
Token Budget
Keep generated prompts under ~2K tokens for single mode, ~1K per agent for Repromptception. Longer prompts waste context window without improving quality. If a prompt exceeds budget, split into phases or move detail into constraints.
Uncertainty Handling
Always include explicit permission for the model to express uncertainty rather than fabricate:
Add to constraints: "If unsure about any requirement, ask for clarification rather than assuming"
For research tasks: "Clearly label confidence levels (high/medium/low) for each finding"
For code tasks: "Flag any assumptions about the codebase with TODO comments"
Settings (for Repromptception mode)
Note: CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS is an experimental flag that may change in future Claude Code versions. Check Claude Code docs for current status.
