返回技能列表

basic-obedience

pjt222
更新于 6 days ago
13 次查看
17
2
17
在 GitHub 上查看
其他ai

关于

This Claude Skill provides structured guidance for training dogs in foundational obedience commands using positive reinforcement and marker training. It covers core techniques like timing, session structure, and distraction proofing for commands such as sit, stay, and come. Developers can integrate this skill to assist users with initial puppy training, re-establishing commands with adult dogs, or preparing for advanced behavioral work.

快速安装

Claude Code

推荐
主要方式
npx skills add pjt222/agent-almanac -a claude-code
插件命令备选方式
/plugin add https://github.com/pjt222/agent-almanac
Git 克隆备选方式
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/basic-obedience

在 Claude Code 中复制并粘贴此命令以安装该技能

技能文档

基順

以正強與標訓教基命(坐、留、來、跟、伏)。

  • 新犬(八週以上)宜基訓
  • 成犬無穩基命
  • 救犬或新家犬當學家命辭
  • 升繁行或脫繩前
  • 舊命已衰宜重立

  • :犬(不拘種、八週以上)
  • :高值獎食(小、軟、速食)
  • :哨或聲標辭(如「yes」)
  • :六呎繩與平頸圈或挽具
  • :初訓宜靜寡擾處

一:立標

標乃欲行與獎之橋。

Marker Training Protocol:
1. Choose your marker: clicker (precise) or verbal "yes" (always available)
2. Charge the marker (10-15 reps):
   - Mark (click or "yes") then immediately deliver a treat
   - No behavior required — just marker → treat, marker → treat
   - Dog should begin orienting toward you at the sound of the marker
3. Test: mark when the dog is looking away. Does the dog turn toward
   you expecting a treat? If yes, the marker is charged.

Timing Rule:
The marker must occur WITHIN 1 second of the desired behavior.
Late marking teaches the wrong behavior.
Mark → then reach for the treat (not the reverse).

得: 犬聞標即穩向人,候獎。

敗: 二十次仍不應→獎值低。換更高值(酪、雞、肝)。若犬擾而不食→境過刺→移靜處。

二:教五基命

每課一命至穩,而後混習。

Command Protocols:

SIT:
1. Hold treat above dog's nose, slowly arc backward over the head
2. As the dog's head follows up, the rear naturally lowers
3. The instant the rear touches the ground → mark and treat
4. Add the verbal cue "sit" AFTER the dog is offering the behavior reliably
   (cue comes before behavior only once the dog understands the behavior)

DOWN:
1. From a sit, hold treat at the dog's nose then lower slowly to the ground
2. Draw the treat slightly forward along the ground
3. As elbows touch the ground → mark and treat
4. If the dog stands instead, reset and try with less forward movement

STAY:
1. Ask for a sit or down
2. Open palm toward the dog, say "stay"
3. Wait 1 second → mark and treat while the dog is still in position
4. Gradually increase duration: 2s, 5s, 10s, 30s, 1 min
5. Add distance: one step back, then two, then five
6. Add distraction: only after duration and distance are solid
   (the "three Ds": Duration, Distance, Distraction — increase one at a time)

COME (recall):
1. Start on a long line (15-30 ft) in a low-distraction environment
2. Let the dog wander, then call name + "come" in an upbeat tone
3. If the dog turns toward you → mark → reward generously when the dog arrives
4. NEVER call "come" for something unpleasant (bath, crate, leaving the park)
5. Recall is the most important safety command — make it the most rewarding

HEEL:
1. Dog on your left side, treat in left hand at your hip
2. Take one step, if the dog moves with you → mark and treat
3. Gradually increase to two steps, five steps, ten steps
4. Mark and treat for maintaining position (head roughly at your knee)
5. If the dog pulls ahead, stop walking. Resume when the leash is loose.

得: 寡擾境中每命以獎為動穩行。

敗: 三課未進→細分之。犬或需中行(如「伏」先獎低頭之動而後全肘著地)。

三:構課

Session Guidelines:
+--------------------+------------------------------------------+
| Parameter          | Guideline                                |
+--------------------+------------------------------------------+
| Duration           | 5-10 minutes (puppies: 3-5 minutes)      |
| Frequency          | 2-3 sessions per day                     |
| End on success     | Always end after a successful rep, not   |
|                    | after a failure                          |
| Reward rate        | Initially: every correct rep             |
|                    | Later: intermittent (variable schedule)  |
| Energy management  | High-energy dog? Exercise BEFORE training|
|                    | Low-energy dog? Train when most alert    |
| Session structure  | Warm-up (easy known command) → new       |
|                    | material → cool-down (easy command)      |
+--------------------+------------------------------------------+

The 80/20 Rule:
- 80% of reps should succeed (dog is getting it right)
- If success rate drops below 80%, the criteria is too high — go easier
- 20% challenge keeps the dog engaged without frustrating

得: 短而成之課,犬欲更多。

敗: 犬離(嗅、視他、臥)→課過長、過難或獎不足。結課而再評。

四:擾下穩命

靜中穩後漸增擾。

Distraction Ladder (work through sequentially):
1. Quiet room, no distractions (starting point)
2. Room with a family member present
3. Backyard or garden
4. Front yard with street noise
5. Quiet park or trail
6. Busy park with other dogs at a distance
7. Busy park with other dogs nearby
8. Novel environments (pet store, cafe patio)

At each new level:
- Expect performance to decrease — this is normal
- Increase reward rate back to every correct rep
- Do not add more distraction until the current level is reliable
- If the dog fails 3 reps in a row, you moved up too fast — go back one level

得: 命於漸擾環境中穩行。

敗: 某擾(他犬、松鼠)常破訓→需別對條反訓(見 behavioral-modification)。

  • 標已充而犬穩應
  • 五命於寡擾境皆行
  • 課 5-10 分,終於成
  • 每命成率八成以上
  • 命依擾梯泛化
  • 主人時機(標於一秒內)穩

  • 復命:言「坐、坐、SIT」→教犬首「坐」可略。言一次而待
  • 晚獎:獎當於標後 2-3 秒內。晚獎破聯
  • 久誘:手帶獎之動(誘)宜於 10-20 次內淡去。否則犬唯見食而應
  • 罰失召:呼「來」而責(因緩、因口銜物)→永毒召令
  • 久訓:疲犬無學。勝而止
  • 命不一:諸家員當用同辭與勢於每命

  • behavioral-modification — 處擾基順之不欲行

GitHub 仓库

pjt222/agent-almanac
路径: i18n/wenyan-ultra/skills/basic-obedience
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

相关推荐技能

llamaguard

其他

LlamaGuard是Meta推出的7-8B参数内容审核模型,专门用于过滤LLM的输入和输出内容。它能检测六大安全风险类别(暴力/仇恨、性内容、武器、违禁品、自残、犯罪计划),准确率达94-95%。开发者可通过HuggingFace、vLLM或Sagemaker快速部署,并能与NeMo Guardrails集成实现自动化安全防护。

查看技能

cost-optimization

其他

这个Claude Skill帮助开发者优化云成本,通过资源调整、标记策略和预留实例来降低AWS、Azure和GCP的开支。它适用于减少云支出、分析基础设施成本或实施成本治理策略的场景。关键功能包括提供成本可视化、资源规模调整指导和定价模型优化建议。

查看技能

quantizing-models-bitsandbytes

其他

这个Skill使用bitsandbytes库量化大语言模型,能在GPU内存有限时通过8位或4位量化减少50-75%内存占用,同时保持精度损失最小。它支持INT8、NF4、FP4等多种量化格式,可与HuggingFace Transformers无缝集成,适用于需要部署更大模型或加速推理的场景。还提供QLoRA训练和8位优化器支持,让开发者能轻松实现高效模型压缩。

查看技能

dispatching-parallel-agents

其他

该Skill用于并行处理3个以上无依赖关系的独立故障,可为每个问题域分派专属Claude代理同时执行调查修复。它通过并发处理多个独立问题显著提升故障排查效率,特别适用于测试文件、子系统等无共享状态的场景。

查看技能