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 liqiongyu/lenny_skills_plus --skill evaluating-new-technologygit clone --depth 1 https://github.com/liqiongyu/lenny_skills_plusWrote 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/liqiongyu/lenny_skills_plus/evaluating-new-technology)<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/evaluating-new-technology"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/evaluating-new-technology/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/liqiongyu/lenny_skills_plus/evaluating-new-technology"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/evaluating-new-technology.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 | $0.00039 | $0.02141 |
| Opus 5 | $0.00019 | $0.01071 |
| Sonnet 5 | $0.00008 | $0.00428 |
| Haiku 4.5 | $0.00004 | $0.00214 |
Grade A, and why
evaluating-new-technology 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 12d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evaluating New Technology
Scope
Covers
- Evaluating a new tool/platform/vendor (including AI products) for adoption
- Emerging tech “should we use this?” decisions
- Build vs buy decisions and tech stack changes
- Running a proof-of-value pilot and capturing evidence
- First-pass risk review (security/privacy/compliance, vendor claims, operational readiness)
When to use
- “Evaluate this new AI tool/vendor for our team.”
- “Should we build this in-house or buy a vendor?”
- “We’re considering changing our analytics/experimentation stack—make a recommendation.”
- “Create a technology evaluation doc with a pilot plan, risks, and decision memo.”
When NOT to use
- You don’t have a real problem/job to solve yet (use
problem-definitionfirst). - You need a full product strategy/roadmap (use
ai-product-strategy). - You’re designing how to build an LLM system (use
building-with-llms). - You need a formal security assessment / penetration testing (engage security; this skill produces a structured first pass).
- You are weighing trade-offs within an existing design or architecture decision (use
evaluating-trade-offs). - You need to manage or pay down existing technical debt rather than adopt something new (use
managing-tech-debt). - You already chose the technology and need an implementation/migration plan (use
managing-tech-debtorplatform-infrastructure).
Inputs
Minimum required
- Candidate technology (what it is, vendor/build option, links if available)
- Problem/workflow to improve + who it’s for
- Current approach/stack and what’s not working
- Constraints: data sensitivity, privacy/compliance, budget, timeline, regions, deployment model (SaaS/on-prem)
- Decision context: who decides, adoption scope, risk tolerance
Missing-info strategy
- Ask up to 5 questions from references/INTAKE.md (3–5 at a time).
- If still missing, proceed with explicit assumptions and present 2–3 options (e.g., buy vs build vs defer).
- Do not request secrets. If asked to run tools, change production systems, or sign up for vendors, require explicit confirmation.
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- eval/eval_config.json 953 B
- eval/SHOWCASE.md 4.6 KB
- eval/with_skill.md 34 KB
- eval/without_skill.md 24 KB
- README.md 1.9 KB
- references/CHECKLISTS.md 1.7 KB
- references/EXAMPLES.md 1.5 KB
- references/INTAKE.md 2.6 KB
- references/RUBRIC.md 5.9 KB
- references/SOURCE_SUMMARY.md 2.2 KB
- references/TEMPLATES.md 5.2 KB
- references/WORKFLOW.md 3.1 KB
- skillpack.json 396 B
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.
- 12d ago First seen · 136 lines · 39 tokens per session scan A 910af5064565
evaluating-new-technology is a skill published in the GitHub repository liqiongyu/lenny_skills_plus (52 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 2,141 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 2026-08-30.
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