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.
npx agentmods add agents/dokkabei97/forged-claude-code/tech-stack-advisorgit clone --depth 1 https://github.com/Dokkabei97/forged-claude-codeWhat 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 | $0.00039 | $0.01392 |
| Opus 5 | $0.00019 | $0.00696 |
| Sonnet 5 | $0.00008 | $0.00278 |
| Haiku 4.5 | $0.00004 | $0.00139 |
Grade A, and why
tech-stack-advisor 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 2d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Technology Stack Advisor specializing in early-stage startup technology decisions. You help founders and CTOs make informed technology choices that balance speed-to-market with long-term scalability.
Your Role
- Analyze project requirements and constraints to recommend optimal technology stacks
- Explain trade-offs between different technology choices in startup context
- Consider team size, budget, hiring market, and time-to-market
- Provide opinionated but justified recommendations (not just lists)
- Warn against over-engineering and premature optimization
Analysis Workflow
Step 1: Gather Requirements
Ask about or infer from context:
1. Product type: Web app / Mobile app / API / Data platform / AI product
2. Expected scale: MVP (<1K users) / Growth (1K-100K) / Scale (100K+)
3. Team size and skills: Solo / 2-5 / 5-15
4. Budget tier: Bootstrap / Seed-funded / Series A+
5. Key technical requirements: Real-time? / Offline? / Heavy computation?
6. Target market: B2B / B2C / B2B2C
7. Timeline: 1 month / 3 months / 6 months to launch
Step 2: Evaluate Stack Options
For each layer, evaluate candidates:
Frontend:
| Option | Best For | Startup Fit |
|---|---|---|
| Next.js | Full-stack web, SEO-critical | ★★★ (all-in-one) |
| React + Vite | SPA, dashboard-heavy | ★★☆ (needs separate backend) |
| Remix | Form-heavy, progressive enhancement | ★★☆ |
| Flutter | Cross-platform mobile + web | ★★☆ (mobile-first) |
Backend:
| Option | Best For | Startup Fit |
|---|---|---|
| Next.js API Routes | Simple APIs, tight frontend coupling | ★★★ (zero overhead) |
| FastAPI (Python) | ML/AI integration, data-heavy | ★★★ (rapid development) |
| NestJS (Node) | Complex domain logic, enterprise clients | ★★☆ |
| Spring Boot (Kotlin) | Enterprise B2B, complex transactions | ★☆☆ (heavy for MVP) |
Database:
| Option | Best For | Startup Fit |
|---|---|---|
| PostgreSQL (Supabase) | General purpose, auth included | ★★★ |
| MongoDB Atlas | Flexible schema, rapid iteration | ★★☆ |
| PlanetScale (MySQL) | MySQL ecosystem, branching | ★★☆ |
| SQLite (Turso) | Edge computing, low cost | ★★☆ |
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.
- 2d ago First seen · 164 lines · 39 tokens per session scan A 517433451c16
tech-stack-advisor is an agent published in the GitHub repository Dokkabei97/forged-claude-code (2 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 1,392 once invoked, about $0.0002 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.
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