Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/khanh-vu/claude-forceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/khanh-vu/claude-force/meta-prompt)<a href="https://agentmods.dev/commands/khanh-vu/claude-force/meta-prompt"><img src="https://agentmods.dev/badge/commands/khanh-vu/claude-force/meta-prompt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/khanh-vu/claude-force/meta-prompt"><img src="https://agentmods.dev/badge/commands/khanh-vu/claude-force/meta-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00007 | $0.03906 |
| Opus 5 | $0.00003 | $0.01953 |
| Sonnet 5 | $0.00001 | $0.00781 |
| Haiku 4.5 | $0.00001 | $0.00391 |
Grade A, and why
meta-prompt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 656 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meta-Prompt Command
Let Claude refine complex objectives into concrete, executable workflows with governance validation.
Philosophy
"Tell Claude what you want, not what to do"
Instead of manually designing agent sequences, describe your high-level goal. Meta-prompting:
- Refines your objective into specific requirements
- Proposes optimal agent workflows
- Validates against governance rules
- Provides alternatives and trade-offs
- Explains reasoning behind suggestions
When to Use
Perfect for:
- Complex, multi-step projects
- Unfamiliar domains (don't know which agents to use)
- Architectural decisions (multiple valid approaches)
- Exploring solution space (what's possible?)
- Learning optimal patterns
Not needed for:
- Simple, single-agent tasks
- Well-known patterns you've done before
- When you already know exact agent sequence
Basic Usage
Describe what you want to achieve:
/meta-prompt "I need to build a user authentication system with email verification"
What happens:
- Analyzes your objective
- Identifies requirements and constraints
- Proposes concrete workflow with agents
- Validates against governance (agents exist, budget, skills)
- Provides alternatives and trade-offs
- Explains reasoning
Output:
## Meta-Prompting Analysis
### Refined Objective
Build a secure user authentication system with:
- Email/password registration
- Email verification (confirm email before access)
- Secure password storage (bcrypt/argon2)
- JWT-based session management
- Password reset flow
- Rate limiting for security
### Proposed Workflow
**Recommended**: `full-stack-feature` (customized)
**Agent Sequence** (8 agents, ~45-60 min, $3.20-4.50):
1. **backend-architect** - Design auth API endpoints, JWT strategy
2. **database-architect** - User schema, indexes, migrations
3. **security-specialist** - Review password storage, rate limiting, vulnerabilities
4. **python-expert** - Implement auth endpoints with FastAPI/Flask
5. **frontend-developer** - Login/register UI components
6. **email-specialist** - Email verification flow (optional: use existing templates)
7. **qc-automation-expert** - Security tests (SQL injection, XSS, CSRF)
8. **deployment-integration-expert** - Environment variables, secrets management
### Reasoning
**Why this sequence:**
- Backend first ensures API contract for frontend
- Security specialist early to catch design issues (cheaper than fixing later)
- Email specialist optional if using third-party service (Sendgrid, etc.)
- QA must include security tests for auth systems
**Alternatives Considered:**
1. **Simpler**: Skip email verification ($2.50, 35min)
- Trade-off: Less secure, but faster to market
2. **More robust**: Add 2FA, OAuth providers ($6.00, 90min)
- Trade-off: Better security, more complex
### Governance Validation
✅ **All checks passed**
- ✅ All agents available
- ✅ Required skills present (backend, database, security, frontend)
- ✅ Budget: $4.50 (within typical range)
- ✅ No security policy violations
- ✅ Timeline: ~60 min (reasonable for scope)
### Success Criteria
I'll know this is done when:
- [ ] Users can register with email/password
- [ ] Email verification required before access
- [ ] Passwords securely hashed (bcrypt/argon2)
- [ ] JWT tokens issued and validated
- [ ] Password reset flow works
- [ ] Security tests pass (no SQL injection, XSS, CSRF)
- [ ] Rate limiting prevents brute force
### Risk Assessment
**Potential risks:**
- ⚠️ Email delivery (use reliable service, test thoroughly)
- ⚠️ Token expiration handling (document clearly)
- ⚠️ Password reset security (verify email ownership)
---
**Ready to proceed?**
[1] Run recommended workflow
[2] Run alternative 1 (simpler)
[3] Run alternative 2 (more robust)
[4] Customize workflow
[5] Save for later (add to todos)
[0] Cancel
Your choice:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 656 lines · 7 tokens per session scan A 39f085e8316a
meta-prompt is a command published in the GitHub repository khanh-vu/claude-force (5 stars, last pushed 9mo ago), licensed MIT. It adds 7 tokens to every session and 3,906 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.