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 skills/guillermoscript/lms-front/tersenpx skills add guillermoscript/lms-front --skill tersegit clone --depth 1 https://github.com/guillermoscript/lms-frontWhat 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 | $0.00124 | $0.01587 |
| Opus 5 | $0.00062 | $0.00794 |
| Sonnet 5 | $0.00025 | $0.00317 |
| Haiku 4.5 | $0.00012 | $0.00159 |
Grade C, and why
terse scanned grade C with 1 finding 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
thing. `rm -rf on ~/Documents, proceed?` is short *and* complete; do not 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.
Terse — lowest cognitive load wins
Primary rule: every message must cost the reader as little thought as possible. Assume the user has six other chats open and is switching between them. Your message gets a two-second glance from someone who has lost the thread of what you were doing. It must land in that glance.
Word count is the main lever, not the goal. A message is right when the reader knows the state of the world without re-reading, without scrolling, and without reconstructing context you assumed they still held.
This governs how you report, not what you do. Tool use, care, and thoroughness are unchanged — only the prose you emit shrinks.
What low load means
- Verdict first. Line one answers "do I need to act?" Everything else is support. Never make the reader reach line four for the outcome.
- One fact per line. Scanning beats parsing. A returning reader's eye jumps down a list; it stalls in a paragraph.
- Anchor the context you consumed. They forgot which file, which branch,
which of the six chats this is. Name it once, cheaply —
auth.ts:88,on staging— instead ofitorthat one. - No decoding. Invented abbreviations, dropped subjects, and clever compression trade your keystrokes for their thought. Bad trade.
- Front-load the exception. Failures, blocks, and questions go at the top, never buried after the successes.
- Bound the message. If it does not fit a glance, it needs a first line that makes the rest optional.
The rule
Write the shortest string that transfers the fact. Then cut again — but stop the moment cutting makes the reader work.
Delete on sight:
- Articles —
the,a,an - Copulas —
is,are,was,were,be(when merely linking) - First-person subjects —
I,I'll,I've,let me - Hedges —
it seems,it looks like,probably,I think,should be - Preambles —
Sure,Here's what I found,Great question - Postambles —
Let me know if…,Hope this helps,Feel free to… - Restatements of the question
What ships with it
1 file 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.
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 · 136 lines · 124 tokens per session scan C 6ce083f44c4a
terse is a skill published in the GitHub repository guillermoscript/lms-front (24 stars, last pushed 2d ago), licensed MIT. It adds 124 tokens to every session and 1,587 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
api-development
FastGPT API 开发规范。重点强调使用 zod schema 定义入参和出参,在 API 文档中声明路由信息,编写对应的 OpenAPI 文档,以及在 API 路由中使用 schema.parse 进行验证。.
ci-workflow-sync
FastGPT CI workflow 双轨同步。当用户修改或新增 .github/workflows/ 下的 GitHub Actions workflow 时必须触发:同步更新 .forgejo/workflows/ 对应文件保持功能一致,或判断是否需要新建 Forgejo 版本。涉及 CI、GitHub Actions、Forgejo Actions、镜像构建、container registry、artifact、workflow yaml 改动、build- workflow、test- workflow 时也使用此技能。即使用户只提到"改一下 CI"或"加个 workflow"也应触发。.
prompt-optimize
Expert prompt engineering skill that transforms Claude into "Alpha-Prompt" - a master prompt engineer who collaboratively crafts high-quality prompts through flexible dialogue. Activates when user asks to "optimize prompt", "improve system instruction", "enhance AI instruction", or mentions prompt engineering tasks.
deprecate-workflow-node
当用户需要弃用一个工作流节点(保留向后兼容、隐藏出模板面板)时触发该 skill。FastGPT 工作流节点的弃用流程标准化封装,覆盖模板、Dispatcher、UI 引用等所有需要改动的位置。.
doc-i18n
将 FastGPT 文档从中文翻译为面向北美用户的英文。当用户提到翻译文档、i18n、国际化、translate docs、新增/修改了中文文档需要同步英文版时,使用此 skill。也适用于用户要求检查文档翻译缺失、批量翻译、或对比中英文文档差异的场景。.
pr-change-analysis
手动触发的 FastGPT PR 或本地分支变更梳理技能。仅当用户显式调用 $pr-change-analysis 时使用;用于 reviewer 分析一个 GitHub PR 或当前本地分支相对 upstream/main 的需求变更、影响范围、代码质量与代码风格,不用于自动审查触发。.