Infra Audit
SethGammon/Citadel
Reads docker-compose, env files, ORM configs, and connection strings to map current infrastructure.
Redisデータ構造パターン、キャッシング戦略、分散ロック、レート制限、Pub/Sub、本番アプリケーション用コネクション管理。
$ npx skills add affaan-m/ECC --skill redis-patterns -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install affaan-m/ECC redis-patterns --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/ja-JP/skills/redis-patterns .claude/skills/redis-patterns && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "redis-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ja-JP/skills/redis-patterns into .claude/skills/redis-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "redis-patterns", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/affaan-m/ECC/tree/main/docs/ja-JP/skills/redis-patternsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add affaan-m/ECC --skill redis-patterns -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install affaan-m/ECC redis-patterns --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .agents/skills && cp -r skills-src/docs/ja-JP/skills/redis-patterns .agents/skills/redis-patterns && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "redis-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ja-JP/skills/redis-patterns into .agents/skills/redis-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "redis-patterns", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill redis-patterns -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install affaan-m/ECC redis-patterns --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/docs/ja-JP/skills/redis-patterns .cursor/skills/redis-patterns && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "redis-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ja-JP/skills/redis-patterns into .cursor/skills/redis-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "redis-patterns", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/affaan-m/ECC.git --path docs/ja-JP/skills/redis-patterns--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add affaan-m/ECC --skill redis-patterns -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install affaan-m/ECC redis-patterns --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/docs/ja-JP/skills/redis-patterns .gemini/skills/redis-patterns && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "redis-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ja-JP/skills/redis-patterns into .gemini/skills/redis-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "redis-patterns", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install affaan-m/ECC redis-patternsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add affaan-m/ECC --skill redis-patterns -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .github/skills && cp -r skills-src/docs/ja-JP/skills/redis-patterns .github/skills/redis-patterns && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "redis-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ja-JP/skills/redis-patterns into .github/skills/redis-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "redis-patterns", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill redis-patterns -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install affaan-m/ECC redis-patterns --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/docs/ja-JP/skills/redis-patterns .opencode/skills/redis-patterns && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "redis-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ja-JP/skills/redis-patterns into .opencode/skills/redis-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "redis-patterns", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
redis-patternsRedisデータ構造パターン、キャッシング戦略、分散ロック、レート制限、Pub/Sub、本番アプリケーション用コネクション管理。
Redis Patterns is an agent skill from affaan-m/ECC. Redisデータ構造パターン、キャッシング戦略、分散ロック、レート制限、Pub/Sub、本番アプリケーション用コネクション管理。
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Databases, covering Event-driven systems. It works with Redis. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.
Read from SKILL.md and the folder at commit ef648e0. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python and lua).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Redis Patterns loads about 2.7k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 387 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from affaan-m/ECC at commit ef648e0, republished under its MIT licence (© affaan-m). 387 words, ~2,707 tokens.
.claude/skills/redis-patterns/SKILL.md (or your agent's skills folder).一般的なバックエンド使用例に対するRedisベストプラクティスの参考資料。
Redisはメモリ内データ構造ストアで、文字列、ハッシュ、リスト、セット、ソート済みセット、ストリームなどをサポートします。単一インスタンスでは個々のRedisコマンドは原子的ですが、マルチステップワークフローはLuaスクリプト、MULTI/EXECトランザクション、または明示的な同期化が必要です。RDBスナップショットまたはAOFログを通じてデータをオプションで永続化します。クライアントはRESPプロトコルを使用してTCP経由で通信します。接続プール不可欠でリクエストごとのハンドシェイクオーバーヘッドを回避します。
| Use Case | Structure | Example Key |
|---|---|---|
| Simple cache | String | product:123 |
| User session | Hash | session:abc |
| Leaderboard | Sorted Set | scores:weekly |
| Unique visitors | Set | visitors:2024-01-01 |
| Activity feed | List | feed:user:456 |
| Event stream | Stream | events:orders |
| Counters / rate limits | String (INCR) | ratelimit:user:123 |
| Bloom filter / HLL | HyperLogLog | hll:pageviews |
import redis
import json
r = redis.Redis(host='localhost', port=6379, decode_responses=True)
def get_product(product_id: int):
cache_key = f"product:{product_id}"
cached = r.get(cache_key)
if cached:
return json.loads(cached)
product = db.query("SELECT * FROM products WHERE id = %s", product_id)
r.setex(cache_key, 3600, json.dumps(product)) # TTL: 1 hour
return productdef update_product(product_id: int, data: dict):
# DB書き込み先
db.execute("UPDATE products SET ... WHERE id = %s", product_id)
# キャッシュを即座に更新
cache_key = f"product:{product_id}"
r.setex(cache_key, 3600, json.dumps(data))# タグベース削除 — セット内で関連キーをグループ化
def cache_product(product_id: int, category_id: int, data: dict):
key = f"product:{product_id}"
tag = f"tag:category:{category_id}"
pipe = r.pipeline(transaction=True)
pipe.setex(key, 3600, json.dumps(data))
pipe.sadd(tag, key)
pipe.expire(tag, 3600)
pipe.execute()
def invalidate_category(category_id: int):
tag = f"tag:category:{category_id}"
keys = r.smembers(tag)
if keys:
r.delete(*keys)
r.delete(tag)import time
import uuid
def create_session(user_id: int, ttl: int = 86400) -> str:
session_id = str(uuid.uuid4())
key = f"session:{session_id}"
pipe = r.pipeline(transaction=True)
pipe.hset(key, mapping={
"user_id": user_id,
"created_at": int(time.time()),
})
pipe.expire(key, ttl)
pipe.execute()
return session_id
def get_session(session_id: str) -> dict | None:
data = r.hgetall(f"session:{session_id}")
return data if data else None
def delete_session(session_id: str):
r.delete(f"session:{session_id}")def is_rate_limited(user_id: int, limit: int = 100, window: int = 60) -> bool:
key = f"ratelimit:{user_id}:{int(time.time()) // window}"
pipe = r.pipeline(transaction=True)
pipe.incr(key)
pipe.expire(key, window)
count, _ = pipe.execute()
return count > limit-- sliding_window.lua
local key = KEYS[1]
local now = tonumber(ARGV[1])
local window = tonumber(ARGV[2])
local limit = tonumber(ARGV[3])
redis.call('ZREMRANGEBYSCORE', key, 0, now - window)
local count = redis.call('ZCARD', key)
if count < limit then
-- Use unique member (now + sequence) to avoid collisions within the same millisecond
local seq_key = key .. ':seq'
local seq = redis.call('INCR', seq_key)
redis.call('EXPIRE', seq_key, math.ceil(window / 1000))
redis.call('ZADD', key, now, now .. '-' .. seq)
redis.call('EXPIRE', key, math.ceil(window / 1000))
return 1
end
return 0sliding_window = r.register_script(open('sliding_window.lua').read())
def allow_request(user_id: int) -> bool:
key = f"ratelimit:sliding:{user_id}"
now = int(time.time() * 1000)
return bool(sliding_window(keys=[key], args=[now, 60000, 100]))import uuid
def acquire_lock(resource: str, ttl_ms: int = 5000) -> str | None:
lock_key = f"lock:{resource}"
token = str(uuid.uuid4())
acquired = r.set(lock_key, token, px=ttl_ms, nx=True)
return token if acquired else None
def release_lock(resource: str, token: str) -> bool:
release_script = """
if redis.call('get', KEYS[1]) == ARGV[1] then
return redis.call('del', KEYS[1])
else
return 0
end
"""
result = r.eval(release_script, 1, f"lock:{resource}", token)
return bool(result)
# Usage
token = acquire_lock("order:payment:123")
if token:
try:
process_payment()
finally:
release_lock("order:payment:123", token)マルチノード設定の場合、フルRedlockアルゴリズムを実装する
redlock-pyライブラリを使用してください。
# Publisher
def publish_event(channel: str, payload: dict):
r.publish(channel, json.dumps(payload))
# Subscriber (blocking — run in separate thread/process)
def subscribe_events(channel: str):
pubsub = r.pubsub()
pubsub.subscribe(channel)
for message in pubsub.listen():
if message['type'] == 'message':
handle(json.loads(message['data']))# Producer
def emit(stream: str, event: dict):
r.xadd(stream, event, maxlen=10000) # Cap stream length
# Consumer group — guarantees at-least-once delivery
try:
r.xgroup_create('events:orders', 'processor', id='0', mkstream=True)
except Exception:
pass # Group already exists
def consume(stream: str, group: str, consumer: str):
while True:
messages = r.xreadgroup(group, consumer, {stream: '>'}, count=10, block=2000)
for _, entries in (messages or []):
for msg_id, data in entries:
process(data)
r.xack(stream, group, msg_id)配信保証、コンシューマーグループ、または再生が必要な場合、Pub/Sub代わりにStreamsを優先してください。
# Pattern: resource:id:field
user:123:profile
order:456:status
cache:product:789
# Pattern: namespace:resource:id
myapp:session:abc123
myapp:ratelimit:user:123
# Pattern: resource:date (time-bound keys)
stats:pageviews:2024-01-01| Data Type | Suggested TTL |
|---|---|
| User session | 24h (86400) |
| API response cache | 5–15 min |
| Rate limit window | Match window size |
| Short-lived tokens | 5–10 min |
| Leaderboard | 1h–24h |
| Static/reference data | 1h–1 week |
常にTTLを設定してください。TTLなしのキーは無限に蓄積してメモリ圧力を引き起こします。
from redis import ConnectionPool, Redis
pool = ConnectionPool(
host='localhost',
port=6379,
db=0,
max_connections=20,
decode_responses=True,
socket_connect_timeout=2,
socket_timeout=2,
)
r = Redis(connection_pool=pool)from redis.cluster import RedisCluster
r = RedisCluster(
startup_nodes=[{"host": "redis-1", "port": 6379}],
decode_responses=True,
skip_full_coverage_check=True,
)from redis.sentinel import Sentinel
sentinel = Sentinel(
[('sentinel-1', 26379), ('sentinel-2', 26379)],
socket_timeout=0.5,
)
master = sentinel.master_for('mymaster', decode_responses=True)
replica = sentinel.slave_for('mymaster', decode_responses=True)| Policy | Behavior | Best For |
|---|---|---|
noeviction | Error on write when full | Queues / critical data |
allkeys-lru | Evict least recently used | General cache |
volatile-lru | LRU only among keys with TTL | Mixed data store |
allkeys-lfu | Evict least frequently used | Skewed access patterns |
volatile-ttl | Evict soonest-to-expire | Prioritize long-lived data |
redis.confを通じて設定:maxmemory-policy allkeys-lru
| Anti-Pattern | Problem | Fix |
|---|---|---|
| Keys with no TTL | Memory grows unbounded | Always set TTL |
KEYS * in production | Blocks the server (O(N)) | Use SCAN cursor |
| Storing large blobs (>100KB) | Slow serialization, memory pressure | Store reference + fetch from object store |
| Single Redis for everything | No isolation between cache & queue | Use separate DBs or instances |
| Ignoring connection pool limits | Connection exhaustion under load | Size pool to workload |
| Not handling cache miss stampede | Thundering herd on cold start | Use locks or probabilistic early expiry |
FLUSHALL without thought | Wipes entire instance | Scope deletes by key pattern |
import threading
_locks: dict[str, threading.Lock] = {}
_locks_mutex = threading.Lock()
def get_with_lock(key: str, fetch_fn, ttl: int = 300):
cached = r.get(key)
if cached:
return json.loads(cached)
with _locks_mutex:
if key not in _locks:
_locks[key] = threading.Lock()
lock = _locks[key]
with lock:
cached = r.get(key) # Re-check after acquiring lock
if cached:
return json.loads(cached)
value = fetch_fn()
r.setex(key, ttl, json.dumps(value))
return valueマルチプロセスデプロイメント:インプロセスロックを上記の分散ロックセクション から
acquire_lock/release_lockに置き換えてください。
Django/Flask APIエンドポイントにキャッシング追加: レスポンスに5分TTLでCache-asideを使用。リクエストパラメータでキーを指定。
ユーザーごとにAPIレート制限:
低トラフィックエンドポイントに固定ウィンドウを pipeline(transaction=True) で使用;正確なユーザーごと制限にはsliding-windowの Lua使用。
ワーカー間のバックグラウンドジョブ調整:
予想ジョブ期間を超えるTTLで acquire_lock を使用。常に finally ブロックでリリース。
複数購読者への通知のファンアウト: ファイアアンドフォーゲットにPub/Subを使用。保証配信または再生が必要な場合、Streamsに切り替え。
| Pattern | When to Use |
|---|---|
| Cache-aside | Read-heavy, tolerate slight staleness |
| Write-through | Strong consistency required |
| Distributed lock | Prevent concurrent access to a resource |
| Sliding window rate limit | Accurate per-user throttling |
| Redis Streams | Durable event queue with consumer groups |
| Pub/Sub | Broadcast with no delivery guarantees needed |
| Sorted Set leaderboard | Ranked scoring, pagination |
| HyperLogLog | Approximate unique count at low memory |
postgres-patterns — リレーショナルデータパターンbackend-patterns — APIおよびサービスレイヤーパターンdatabase-migrations — スキーマバージョニングdjango-patterns — Djangoキャッシュフレームワーク統合database-reviewer — 全データベースレビューワークフロー© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in docs/ja-JP/skills/redis-patterns of affaan-m/ECC.
Open the folder on GitHubat commit ef648e0
Redis Patterns next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Redis Patterns this skillaffaan-m/ECC | 276k | — | ~2.7k | Automated safety check: Pass | MIT | |
| Infra AuditSethGammon/Citadel | 923 | — | ~2.1k | Automated safety check: Notes | MIT | |
| Cache FrameworkRain-kl/OpenFlare | 288 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Use Sealoshashgraph-online/awesome-codex-plugins | 1.3k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Redis Patternsrohitg00/awesome-claude-code-toolkit | 2.7k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Bun Redissecondsky/claude-skills | 227 | — | ~1.8k | Automated safety check: Pass | MIT |
SethGammon/Citadel
Reads docker-compose, env files, ORM configs, and connection strings to map current infrastructure.
Rain-kl/OpenFlare
Wavelet 项目专用:当新增或修改业务缓存(RAM/Redis/DB 三层读路径)、缓存失效、多节点 pub/sub 同步、或评估高频读是否应接入缓存时必须使用。本技能说明系统标准缓存框架、参考实现、禁止写法与分布式一致性要求。
hashgraph-online/awesome-codex-plugins
Deploy and operate apps on Sealos Cloud: sign in to a Sealos account, deploy any project or self-hosted app (from the template store, an official Docker image, or project source code), provision…
rohitg00/awesome-claude-code-toolkit
Redis patterns including caching strategies, pub/sub, streams for event processing, Lua scripts, and data structures
secondsky/claude-skills
A skill your agent uses when working with Redis in Bun (ioredis, Upstash), caching, pub/sub, session storage, or key-value operations.
godatadriven/whirl
Create a new Whirl environment in the envs/ directory. An agent skill from godatadriven/whirl.
affaan-m/ECC
Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.
affaan-m/ECC
Ingests, indexes, searches, edits and monitors video, audio and live streams through the VideoDB Python SDK, returning stream links, clips and timestamps.
affaan-m/ECC
Scans installed skills for principles that recur across them and proposes rule-file changes: append, revise, add a section, create a file or leave as covered.
affaan-m/ECC
Builds DRAFT counterparty agreements from one markdown template and a small JSON spec per party, with clauses picked by the party's role.
affaan-m/ECC
Measures whether agents actually follow a skill, rule or agent definition by generating scenarios at three strictness levels and scoring tool-call traces.
affaan-m/ECC
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
Works with
Categories
Redisデータ構造パターン、キャッシング戦略、分散ロック、レート制限、Pub/Sub、本番アプリケーション用コネクション管理。. Redis Patterns is an agent skill from affaan-m/ECC.
Redis Patterns fits situations like: tasks that involve Event-driven systems.
Run `npx skills add affaan-m/ECC --skill redis-patterns -a claude-code`. Or copy the skill folder (docs/ja-JP/skills/redis-patterns in affaan-m/ECC) into .claude/skills/redis-patterns in your project. Claude Code loads it when a task matches its description.
Run `npx skills add affaan-m/ECC --skill redis-patterns -a codex`. Or copy the skill folder (docs/ja-JP/skills/redis-patterns in affaan-m/ECC) into .agents/skills/redis-patterns in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill redis-patterns -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/redis-patterns, .gemini/skills/redis-patterns, .github/skills/redis-patterns and .opencode/skills/redis-patterns in your project.
SKILL.md names no scripts, command-line tools or credentials: Redis Patterns is instructions for the agent only. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Redis Patterns is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Redis Patterns: Infra Audit (SethGammon/Citadel, 923 stars), Cache Framework (Rain-kl/OpenFlare, 288 stars), Use Sealos (hashgraph-online/awesome-codex-plugins, 1.3k stars) and Redis Patterns (rohitg00/awesome-claude-code-toolkit, 2.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 275,546 GitHub stars. The repository holds 673 skills in this directory. The repository was last updated on October 5, 2026.
Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.