english-game

Other

run a feishu or lark english game with lightweight group-chat interaction. use when users want an english game, vocab challenge, wordle-like word guessing, definition guessing, or speaking practice with voice messages. this skill provides three modes: vocab, guess, and speaking. it helps claw choose the mode, track session state in chat context, score vocab guesses deterministically, transcribe voice with senseasr for speaking mode, and reply in natural language without raw json.

Install

openclaw skills install english-game

feishu english game

Use this skill for Feishu/Lark English-game sessions.

Hard rules

Treat this as a group-chat game skill, not a generic tutoring flow.
Keep the interaction lightweight and fun.
Do not ask broad setup questions.
If the mode is not specified, ask only one concise question: vocab / guess / speaking?
If the difficulty is not specified, ask only one concise follow-up or default to cet6.
Keep game state in Claw's working context: current mode, difficulty, target word, guess history, hint count, winner, and whether the round is open or finished.
Do not dump JSON, raw payloads, or debug objects into Feishu/Lark.
Reply in normal chat language.
Use SENSEAUDIO_API_KEY from environment. Never hardcode keys.

Core modes

1. vocab mode

Use when the group wants a Wordle-like vocabulary game.

Behavior:

Choose a target English word that fits the requested difficulty.
Reveal only the word length at the start.
Let users submit whole-word guesses.
Score each guess with the deterministic helper script in scripts/english_game.py.
Keep a visible board in chat using text or emoji. Do not rely on model-only letter scoring.
After a correct answer or a pass, give learning value:
- ipa / pronunciation
- part of speech
- chinese meaning
- synonyms
- antonyms when useful
- one natural english example sentence

Hints may be released gradually if the group is stuck:

chinese meaning hint
first-letter hint
root/prefix/suffix hint
synonym-style hint

2. guess mode

Use when the group wants a more conversational guessing game.

Default submode is definition.

Supported prompt styles:

definition
example
synonym
antonym
cloze

Behavior:

Post one clue at a time.
Let anyone in the group answer.
Keep the pace short and chat-native.
No large board is required.
After the answer is solved, still provide the same learning wrap-up as vocab mode.

For v1, prefer definition unless the user explicitly asks for another submode.

3. speaking mode

Use when the group wants spoken English practice through voice messages.

Behavior:

Post a short prompt, sentence, or question.
Wait for a voice message.
Download the voice file and transcribe it with scripts/asr_transcribe.py.
Use the transcript as the basis for feedback.
Reply with:
- what you heard
- whether it matched the target or answered the prompt
- a short correction or polish suggestion
- a better natural version when helpful

Important limitation:

ASR transcript quality can support speaking feedback.
ASR alone cannot produce trustworthy phoneme-level pronunciation scoring.
Do not claim precise pronunciation grades or accent judgments unless another dedicated pronunciation model exists.
Keep speaking feedback practical and light.

Default commands for Feishu/Lark

Use a single entrypoint concept such as /english.

Recommended command pattern:

/english start
/english start vocab
/english start guess
/english start speaking
/english hint
/english pass
/english stop
/english rank
/english help

If the user says only 英语游戏, start mode selection. If the user already said vocab, guess, or speaking, go directly into that mode.

Difficulty guidance

Supported labels:

cet4
cet6
kaoyan
ielts
toefl

Selection rules:

cet4: common core vocabulary, shorter words, familiar daily usage
cet6: broader academic/common advanced vocabulary
kaoyan: more abstract and formal words
ielts: communication + academic discussion vocabulary
toefl: academic and concept-heavy vocabulary

When uncertain, default to cet6.

Deterministic helpers

vocab scoring

Use the script below for every vocab guess so repeated letters are handled correctly:

python3 scripts/english_game.py vocab-score \
  --target-word "explanation" \
  --guess "probability"

The script prints plain text that includes:

normalized guess
emoji score row
solved true/false

Use that output to update the board you show in Feishu/Lark.

speaking transcription

Use the script below for voice-message transcription:

python3 scripts/asr_transcribe.py \
  --file /path/to/audio.m4a \
  --language en

Defaults:

model: sense-asr-pro
response parsing: plain transcript text only
punctuation: enabled when supported
ITN: enabled when supported

If the user wants translation for speaking review, add --target-language zh or another supported language.

Feishu/Lark response style

Always reply in natural chat language.

Good examples:

英语游戏开始啦，选一个模式：vocab / guess / speaking

你猜对了！
单词：explanation
音标：/ˌekspləˈneɪʃən/
词性：noun
释义：解释；说明
例句：Her clear explanation helped the team understand the problem.

我听到的是：I would like to book a ticket for tomorrow morning.
整体表达很自然。把 for tomorrow morning 再连读顺一点会更像真实对话。

Bad examples:

{"text":"...","segments":[...]}

{"guess":"probability","score":["absent","present",...]}

Session management

Claw should remember within the ongoing chat:

current mode
chosen difficulty
target word or target clue
guess history
hints already used
who solved it
whether a round is active

Do not ask users to repeat information that already exists in recent chat context.

Environment variables

Required:

export SENSEAUDIO_API_KEY="your_key"

Optional:

export SENSEAUDIO_BASE_URL="https://api.senseaudio.cn"

Resources

scripts/english_game.py: deterministic vocab scoring helper
scripts/asr_transcribe.py: SenseASR transcription helper for speaking mode
references/integration_cn.md: Chinese interaction rules for Feishu/Lark
references/modes_cn.md: mode-specific gameplay guidance
references/asr_provider_notes.md: ASR defaults and capability notes