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 skills add Maudeunfledged834/startup-founder-skills --skill tech-stack-evalgit clone --depth 1 https://github.com/Maudeunfledged834/startup-founder-skillsWrote 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/skills/maudeunfledged834/startup-founder-skills/tech-stack-eval)<a href="https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/tech-stack-eval"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/tech-stack-eval/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/skills/maudeunfledged834/startup-founder-skills/tech-stack-eval"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/tech-stack-eval.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 | $0.00055 | $0.01821 |
| Opus 5.5 | $0.00022 | $0.00728 |
| Sonnet 5.5 | $0.00011 | $0.00364 |
| Haiku 4.5 | $0.00006 | $0.00182 |
Grade A, and why
tech-stack-eval 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 1mo 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.
This is a copy
100% identical to tech-stack-eval — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tech Stack Evaluation
When to Use
- Comparing frontend/backend frameworks or libraries for new projects
- Evaluating cloud providers (AWS vs Azure vs GCP) for specific workloads
- Planning technology migrations with risk and effort assessment
- Calculating TCO including hidden costs; making build vs. buy decisions
- Assessing open-source library viability and ecosystem health
Do NOT use when: the decision is trivial (use team preference), the technology is already mandated, or this is an emergency production issue.
Context Required
From startup-context: product type, team skills, tech stack, stage, scale, budget. Also ask:
- What problem are you solving? (push back on solution-first thinking)
- Non-negotiable requirements (performance, compliance, team familiarity)
- Team experience with each option and timeline pressure (tight deadlines favor familiar tools)
- Growth expectations that affect scalability requirements
Workflow
- Clarify the decision — What exactly is being decided and what are the real requirements? Push back if the user picks tech before defining the problem.
- Identify candidates — List 2-4 realistic options. Exclude clearly wrong choices early.
- Define weighted evaluation criteria — Select 6-8 criteria from the master list below. Assign weights based on the user's priorities (total = 100%).
- Score each candidate — Rate 1-5 on each criterion with one-line justification per score.
- Assess ecosystem health — Evaluate GitHub activity, npm/PyPI adoption, community strength, corporate backing, and trajectory (growing, stable, declining).
- Calculate TCO — Project 5-year total cost including compute, storage, bandwidth, licensing, engineering time (setup + ongoing), and operational overhead. Engineering time is usually the largest cost for startups.
- Analyze migration path — If migrating, estimate effort, risks, timeline, and recommend phased approach (strangler fig pattern).
- Deliver recommendation — Clear winner with rationale and confidence level. No "it depends" without a follow-up question to resolve the ambiguity.
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.
- 1mo ago First seen · 153 lines · 55 tokens per session scan A bff539d89bcb
tech-stack-eval is a skill published in the GitHub repository Maudeunfledged834/startup-founder-skills (8 stars, last pushed 16d ago), licensed MIT. It adds 55 tokens to every session and 1,821 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to tech-stack-eval, differing in 0 lines, and is treated as a copy.
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