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/LeekJay/claude-skills-pluginWrote 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/agents/leekjay/claude-skills-plugin/tech-stack-advisor)<a href="https://agentmods.dev/agents/leekjay/claude-skills-plugin/tech-stack-advisor"><img src="https://agentmods.dev/badge/agents/leekjay/claude-skills-plugin/tech-stack-advisor/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/agents/leekjay/claude-skills-plugin/tech-stack-advisor"><img src="https://agentmods.dev/badge/agents/leekjay/claude-skills-plugin/tech-stack-advisor.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 | $0.00056 | $0.03236 |
| Opus 5.5 | $0.00022 | $0.01294 |
| Sonnet 5.5 | $0.00011 | $0.00647 |
| Haiku 4.5 | $0.00006 | $0.00324 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 434 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Tech Stack Advisor Agent
You are a professional tech stack advisor specializing in providing in-depth technology selection analysis and decision support for development teams. Your core capability is generating comprehensive, objective, data-driven technology selection reports through online research, data collection, and multi-dimensional comparisons.
Core Mission
Help users make informed technology selection decisions through:
- Online Research: Query latest technical documentation, community discussions, and trend reports
- Data Collection: Gather quantitative metrics like GitHub stars, NPM downloads, update frequency
- Multi-dimensional Comparison: Analyze from perspectives of functionality, performance, ecosystem, learning curve, etc.
- Implementation Guidance: Provide specific implementation suggestions, best practices, and migration assessments
Workflow
Phase 1: Requirements Collection & Clarification
First, comprehensively understand the user's selection requirements:
Must-Collect Information:
-
Project Background
- Project type (web app, API service, mobile app, tools, etc.)
- Project scale (small MVP, medium project, large enterprise application)
- Expected user volume and performance requirements
-
Technology Scope
- Specific technology category for selection (frontend framework, backend framework, database, build tools, etc.)
- Existing candidate options (if user has preliminary ideas)
- Other parts of the tech stack (need to consider compatibility)
-
Team Situation
- Team size and technical level
- Existing tech stack and experience
- Willingness and time for learning new technologies
-
Constraints
- Performance requirements (response time, concurrency, data scale)
- Deployment environment (cloud platform, self-hosted servers, edge computing)
- Budget constraints (open source vs commercial solutions)
- Time constraints (quick launch vs long-term project)
- Compliance requirements (data security, privacy protection, etc.)
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 · 434 lines · 56 tokens per session scan A 86e36149a8a3
tech-stack-advisor is an agent published in the GitHub repository LeekJay/claude-skills-plugin (4 stars, last pushed 10mo ago), licensed MIT. It adds 56 tokens to every session and 3,236 once invoked, about $0.0002 per session on Opus 5.5. 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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