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/fuyuxiang/echo-agent/flashcardsnpx skills add fuyuxiang/echo-agent --skill flashcardsgit clone --depth 1 https://github.com/fuyuxiang/echo-agentWhat 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 | $0.00025 | $0.00650 |
| Opus 5 | $0.00013 | $0.00325 |
| Sonnet 5 | $0.00005 | $0.00130 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
flashcards 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 3d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flashcards
Spaced repetition system using the SM-2 algorithm. SQLite storage.
Script
python3 scripts/flashcard_engine.py create-deck "Python基础"
python3 scripts/flashcard_engine.py add "Python基础" "GIL是什么?" "Global Interpreter Lock，全局解释器锁"
python3 scripts/flashcard_engine.py add "Python基础" "list和tuple的区别?" "list可变，tuple不可变" --type basic
python3 scripts/flashcard_engine.py add "Python基础" "Python的GIL是{{Global Interpreter Lock}}" --type cloze
python3 scripts/flashcard_engine.py due # show due cards
python3 scripts/flashcard_engine.py review <card_id> 4 # rate 0-5
python3 scripts/flashcard_engine.py stats "Python基础"
python3 scripts/flashcard_engine.py import cards.csv "Python基础"
SM-2 Algorithm
Quality rating (0-5):
- 0-2: Incorrect (reset interval to 1 day)
- 3: Correct but hard (keep interval)
- 4: Correct (normal progression)
- 5: Easy (accelerate interval)
def sm2(quality, repetitions, easiness, interval):
if quality >= 3:
if repetitions == 0: interval = 1
elif repetitions == 1: interval = 6
else: interval = round(interval * easiness)
repetitions += 1
else:
repetitions = 0
interval = 1
easiness = max(1.3, easiness + 0.1 - (5 - quality) * (0.08 + (5 - quality) * 0.02))
return repetitions, easiness, interval
Card Types
- Basic: front → back
- Cloze:
Python的GIL是{{Global Interpreter Lock}}→ shows blank - Reverse: auto-generates both directions
Storage
SQLite at ~/.echo-agent/flashcards.db:
CREATE TABLE decks (id INTEGER PRIMARY KEY, name TEXT UNIQUE, created_at TEXT);
CREATE TABLE cards (
id INTEGER PRIMARY KEY, deck_id INTEGER,
front TEXT, back TEXT, card_type TEXT DEFAULT 'basic',
repetitions INTEGER DEFAULT 0, easiness REAL DEFAULT 2.5,
interval INTEGER DEFAULT 0, next_review TEXT,
created_at TEXT DEFAULT CURRENT_TIMESTAMP
);
Channel Integration
Schedule daily review delivery: send due cards as quiz messages through Telegram/WeChat at configured time.
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.
- 3d ago First seen · 81 lines · 25 tokens per session scan A 142e392364a3
flashcards is a skill published in the GitHub repository fuyuxiang/echo-agent (988 stars, last pushed 3d ago), licensed MIT. It adds 25 tokens to every session and 650 once invoked, about $0.0001 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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