tech-eval

tech-eval is a skill for Claude Code from lync-cyber/CataForge. It costs 52 tokens per session (748 once invoked), scanned A, original, MIT.

A framework for comparing technical options, such as programming libraries, databases, or API styles, and recording the reasoning behind a choice.

In plain words
What is it for?
Use it for technology selection, version and maintenance checks, comparison tables, recommendations, and decision records; the user makes the final choice.
Why use it?
It makes trade-offs and risks visible before a technical decision is finalized.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it for technology selection, version and maintenance checks, comparison tables, recommendations, and decision records; the user makes the final choice.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lync-cyber/cataforge/tech-eval
Install

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.

Any agent
npx skills add lync-cyber/CataForge --skill tech-eval
Clone the repo
git clone --depth 1 https://github.com/lync-cyber/CataForge

Made for: Claude Code.

Wrote 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.

agentmods badge for tech-eval

README.md
[![agentmods](https://agentmods.dev/badge/skills/lync-cyber/cataforge/tech-eval/github.svg)](https://agentmods.dev/skills/lync-cyber/cataforge/tech-eval)
Your own site
<a href="https://agentmods.dev/skills/lync-cyber/cataforge/tech-eval"><img src="https://agentmods.dev/badge/skills/lync-cyber/cataforge/tech-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.

agentmods 80×15 button for tech-eval

Your own site · 80×15
<a href="https://agentmods.dev/skills/lync-cyber/cataforge/tech-eval"><img src="https://agentmods.dev/badge/skills/lync-cyber/cataforge/tech-eval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 748 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.00748
Opus 5.5 $0.00021 $0.00299
Sonnet 5.5 $0.00010 $0.00150
Haiku 4.5 $0.00005 $0.00075

Measured 1mo ago against content hash ccf836d47863, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

tech-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.

.cataforge/skills/tech-eval/SKILL.md · 43 lines

What it actually says

技术评估 (tech-eval)

能力边界

  • 能做: 技术方案对比分析、选型推荐、产出选型决策记录(调研数据经 research 的 research-note 获取,本 skill 在其上附对比矩阵与推荐)
  • 不做: 最终决策(由用户确认)、代码实现

输入规范

  • 待评估的技术领域(如: 前端框架、数据库、API风格)
  • PRD中的非功能需求约束

输出规范

  • 方案对比表(优势/劣势/适用场景)
  • 选型推荐(含理由)
  • research-note 记录(通过context产出)

执行流程

  1. 明确评估维度(性能/生态/学习成本/维护性)
  2. 调用research skill的web-search指令检索方案
  3. 版本与生命周期验证 — 对每个候选方案:
    • 通过web-search查询其最新稳定版本号和发布日期
    • 确认维护状态(Active/LTS/Maintenance/EOL)
    • 若候选方案已EOL或最新版本发布超过12个月未更新,标注风险并寻找替代
    • 对比矩阵中使用验证后的最新稳定版,而非训练数据中的默认版本
  4. 多方案对比 → 调用research skill的user-interview指令让用户比选
  5. 记录选型决策和理由

Anti-Patterns

  • 禁止: 用训练数据中的默认版本号做"最新版"评估 —— 必须实际检索 release notes 验证;否则推荐过期版本
  • 避免: 以训练集热门度做选型依据 —— 如不经评估直接推荐 "React + PostgreSQL + Redis" 组合;须用对比矩阵展示 ≥2 个备选并按 PRD 非功能需求打分,生态热度仅作其中一维、不得是唯一理由
  • 禁止: 单一维度比较("X 比 Y 快")—— 性能 / 生态 / 学习成本 / EOL 风险 / license 至少四维并列才能产出可决策矩阵
  • 禁止: 输出"看情况"等无承诺结论 —— tech-eval 的产出必须是带理由的明确推荐;含糊收尾让 architect 无法定稿 ARCH
  • 避免: 把候选方案矩阵塞进 ARCH 主卷 —— 选型理由进 research-note 或 decision-log,ARCH 只承载终态决策
  • 禁止: release notes / 版本检索不可达时退回训练数据默认值充当结论 —— 按 COMMON-RULES §通用 Error Handling 标 [ASSUMPTION] 注明未在线验证的版本假设与影响,不伪装成已验证推荐
Changes

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.

  1. 1mo ago First seen · 43 lines · 52 tokens per session scan A ccf836d47863

Subscribe to this mod's changes

tech-eval is a skill published in the GitHub repository lync-cyber/CataForge (128 stars, last pushed 2mo ago), licensed MIT. It adds 52 tokens to every session and 748 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 2026-08-30.

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