Iron Proxy Gateway for NanoClaw
nanocoai/nanoclaw
Installs or refreshes Iron Proxy and its Iron Control web console for NanoClaw, with a local Docker setup, database, credentials and a human approval bridge.
Zero Script QA — test without scripts using structured JSON logging and Docker monitoring.
$ npx skills add ww-w-ai/bkit-claude-code --skill zero-script-qa -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ww-w-ai/bkit-claude-code zero-script-qa --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/ww-w-ai/bkit-claude-code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/zero-script-qa .claude/skills/zero-script-qa && 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 "zero-script-qa" agent skill from https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/zero-script-qa into .claude/skills/zero-script-qa/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zero-script-qa", 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/ww-w-ai/bkit-claude-code/tree/main/skills/zero-script-qaType 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 ww-w-ai/bkit-claude-code --skill zero-script-qa -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ww-w-ai/bkit-claude-code zero-script-qa --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ww-w-ai/bkit-claude-code.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/zero-script-qa .agents/skills/zero-script-qa && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "zero-script-qa" agent skill from https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/zero-script-qa into .agents/skills/zero-script-qa/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zero-script-qa", 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 ww-w-ai/bkit-claude-code --skill zero-script-qa -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ww-w-ai/bkit-claude-code zero-script-qa --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ww-w-ai/bkit-claude-code.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/zero-script-qa .cursor/skills/zero-script-qa && 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 "zero-script-qa" agent skill from https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/zero-script-qa into .cursor/skills/zero-script-qa/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zero-script-qa", 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/ww-w-ai/bkit-claude-code.git --path skills/zero-script-qa--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 ww-w-ai/bkit-claude-code --skill zero-script-qa -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ww-w-ai/bkit-claude-code zero-script-qa --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ww-w-ai/bkit-claude-code.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/zero-script-qa .gemini/skills/zero-script-qa && 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 "zero-script-qa" agent skill from https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/zero-script-qa into .gemini/skills/zero-script-qa/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zero-script-qa", 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 ww-w-ai/bkit-claude-code zero-script-qaInstalls 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 ww-w-ai/bkit-claude-code --skill zero-script-qa -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ww-w-ai/bkit-claude-code.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/zero-script-qa .github/skills/zero-script-qa && 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 "zero-script-qa" agent skill from https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/zero-script-qa into .github/skills/zero-script-qa/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zero-script-qa", 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 ww-w-ai/bkit-claude-code --skill zero-script-qa -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ww-w-ai/bkit-claude-code zero-script-qa --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ww-w-ai/bkit-claude-code.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/zero-script-qa .opencode/skills/zero-script-qa && 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 "zero-script-qa" agent skill from https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/zero-script-qa into .opencode/skills/zero-script-qa/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zero-script-qa", 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.
zero-script-qaZero Script QA — test without scripts using structured JSON logging and Docker monitoring.
Zero Script QA is an agent skill from ww-w-ai/bkit-claude-code. Zero Script QA — test without scripts using structured JSON logging and Docker monitoring. Triggers: zero-script-qa, log testing, docker logs, QA
Its SKILL.md is about 4.1k 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 DevOps & Cloud, covering Containers. It works with Docker. The repository describes itself as: bkit Vibecoding Kit - PDCA methodology + Claude Code mastery for AI-native development. The licence is Apache-2.0.
10 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 85b4913. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadGlobGrepBashFrom allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
dockerclaudecurlFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use docker and curl, which can reach the network depending on how they are called.
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.
Zero Script QA loads about 4.1k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 582 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 noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Read, Glob, Grep, BashAutomated 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 ww-w-ai/bkit-claude-code at commit 85b4913, republished under its Apache-2.0 licence (© ww-w-ai). 582 words, ~4,136 tokens.
.claude/skills/zero-script-qa/SKILL.md (or your agent's skills folder).Zero Script QA is a methodology that verifies features through structured logs and real-time monitoring without writing test scripts.
Traditional: Write test code → Execute → Check results → Maintain
Zero Script: Build log infrastructure → Manual UX test → AI log analysis → Auto issue detection{
"timestamp": "2026-01-08T10:30:00.000Z",
"level": "INFO",
"service": "api",
"request_id": "req_abc123",
"message": "API Request completed",
"data": {
"method": "POST",
"path": "/api/users",
"status": 200,
"duration_ms": 45
}
}| Field | Type | Description |
|---|---|---|
| timestamp | ISO 8601 | Time of occurrence |
| level | string | DEBUG, INFO, WARNING, ERROR |
| service | string | Service name (api, web, worker, etc.) |
| request_id | string | Request tracking ID |
| message | string | Log message |
| data | object | Additional data (optional) |
| Environment | Minimum Level | Purpose |
|---|---|---|
| Local | DEBUG | Development and QA |
| Staging | DEBUG | QA and integration testing |
| Production | INFO | Operations monitoring |
Client → API Gateway → Backend → Database
↓ ↓ ↓ ↓
req_abc req_abc req_abc req_abc
Trackable with same Request ID across all layers// middleware.ts
import { v4 as uuidv4 } from 'uuid';
export function generateRequestId(): string {
return `req_${uuidv4().slice(0, 8)}`;
}
// Propagate via header
headers['X-Request-ID'] = requestId;// API client
const requestId = headers['X-Request-ID'] || generateRequestId();
// Include in all logs
logger.info('Processing request', { request_id: requestId });
// Include in header when calling downstream services
await fetch(url, {
headers: { 'X-Request-ID': requestId }
});# middleware/logging.py
import logging
import time
import uuid
import json
from fastapi import Request
class JsonFormatter(logging.Formatter):
def format(self, record):
log_record = {
"timestamp": self.formatTime(record),
"level": record.levelname,
"service": "api",
"request_id": getattr(record, 'request_id', 'N/A'),
"message": record.getMessage(),
}
if hasattr(record, 'data'):
log_record["data"] = record.data
return json.dumps(log_record)
class LoggingMiddleware:
async def __call__(self, request: Request, call_next):
request_id = request.headers.get('X-Request-ID', f'req_{uuid.uuid4().hex[:8]}')
request.state.request_id = request_id
start_time = time.time()
# Request logging
logger.info(
f"Request started",
extra={
'request_id': request_id,
'data': {
'method': request.method,
'path': request.url.path,
'query': str(request.query_params)
}
}
)
response = await call_next(request)
duration = (time.time() - start_time) * 1000
# Response logging (including 200 OK!)
logger.info(
f"Request completed",
extra={
'request_id': request_id,
'data': {
'status': response.status_code,
'duration_ms': round(duration, 2)
}
}
)
response.headers['X-Request-ID'] = request_id
return response# services/user_service.py
def create_user(data: dict, request_id: str):
logger.info("Creating user", extra={
'request_id': request_id,
'data': {'email': data['email']}
})
# Business logic
user = User(**data)
db.add(user)
db.commit()
logger.info("User created", extra={
'request_id': request_id,
'data': {'user_id': user.id}
})
return user// lib/logger.ts
type LogLevel = 'DEBUG' | 'INFO' | 'WARNING' | 'ERROR';
interface LogData {
request_id?: string;
[key: string]: any;
}
const LOG_LEVELS: Record<LogLevel, number> = {
DEBUG: 0,
INFO: 1,
WARNING: 2,
ERROR: 3,
};
const MIN_LEVEL = process.env.NODE_ENV === 'production' ? 'INFO' : 'DEBUG';
function log(level: LogLevel, message: string, data?: LogData) {
if (LOG_LEVELS[level] < LOG_LEVELS[MIN_LEVEL]) return;
const logEntry = {
timestamp: new Date().toISOString(),
level,
service: 'web',
request_id: data?.request_id || 'N/A',
message,
data: data ? { ...data, request_id: undefined } : undefined,
};
console.log(JSON.stringify(logEntry));
}
export const logger = {
debug: (msg: string, data?: LogData) => log('DEBUG', msg, data),
info: (msg: string, data?: LogData) => log('INFO', msg, data),
warning: (msg: string, data?: LogData) => log('WARNING', msg, data),
error: (msg: string, data?: LogData) => log('ERROR', msg, data),
};// lib/api-client.ts
import { logger } from './logger';
import { v4 as uuidv4 } from 'uuid';
export async function apiClient<T>(
endpoint: string,
options: RequestInit = {}
): Promise<T> {
const requestId = `req_${uuidv4().slice(0, 8)}`;
const startTime = Date.now();
logger.info('API Request started', {
request_id: requestId,
method: options.method || 'GET',
endpoint,
});
try {
const response = await fetch(`/api${endpoint}`, {
...options,
headers: {
'Content-Type': 'application/json',
'X-Request-ID': requestId,
...options.headers,
},
});
const duration = Date.now() - startTime;
const data = await response.json();
// Log 200 OK too!
logger.info('API Request completed', {
request_id: requestId,
status: response.status,
duration_ms: duration,
});
if (!response.ok) {
logger.error('API Request failed', {
request_id: requestId,
status: response.status,
error: data.error,
});
throw new ApiError(data.error);
}
return data;
} catch (error) {
logger.error('API Request error', {
request_id: requestId,
error: error instanceof Error ? error.message : 'Unknown error',
});
throw error;
}
}http {
log_format json_combined escape=json '{'
'"timestamp":"$time_iso8601",'
'"level":"INFO",'
'"service":"nginx",'
'"request_id":"$http_x_request_id",'
'"message":"HTTP Request",'
'"data":{'
'"remote_addr":"$remote_addr",'
'"method":"$request_method",'
'"uri":"$request_uri",'
'"status":$status,'
'"body_bytes_sent":$body_bytes_sent,'
'"request_time":$request_time,'
'"upstream_response_time":"$upstream_response_time",'
'"http_referer":"$http_referer",'
'"http_user_agent":"$http_user_agent"'
'}'
'}';
access_log /var/log/nginx/access.log json_combined;
}version: '3.8'
services:
api:
build: ./backend
environment:
- LOG_LEVEL=DEBUG
- LOG_FORMAT=json
logging:
driver: json-file
options:
max-size: "10m"
max-file: "3"
web:
build: ./frontend
environment:
- NODE_ENV=development
depends_on:
- api
nginx:
image: nginx:alpine
volumes:
- ./nginx/nginx.conf:/etc/nginx/nginx.conf
ports:
- "80:80"
depends_on:
- api
- web# Stream all service logs
docker compose logs -f
# Specific service only
docker compose logs -f api
# Filter errors only
docker compose logs -f | grep '"level":"ERROR"'
# Track specific Request ID
docker compose logs -f | grep 'req_abc123'# Start development environment
docker compose up -d
# Start log monitoring (Claude Code monitors)
docker compose logs -fUser tests actual features in browser:
1. Sign up attempt
2. Login attempt
3. Use core features
4. Test edge casesClaude Code in real-time:
1. Monitor log stream
2. Detect error patterns
3. Detect abnormal response times
4. Track entire flow via Request ID
5. Auto-document issues# QA Issue Report
## Issues Found
### ISSUE-001: Insufficient error handling on login failure
- **Request ID**: req_abc123
- **Severity**: Medium
- **Reproduction path**: Login → Wrong password
- **Log**:
```json
{"level":"ERROR","message":"Login failed","data":{"error":"Invalid credentials"}}
---
## Issue Detection Patterns
### 1. Error Detection
```json
{"level":"ERROR","message":"..."}→ Report immediately
{"data":{"duration_ms":3000}}→ Warning when exceeding 1000ms
3+ consecutive failures on same endpoint→ Report potential system issue
{"data":{"status":500}}→ Report 5xx errors immediately
| Phase | Zero Script QA Integration |
|---|---|
| Phase 4 (API) | API response logging verification |
| Phase 6 (UI) | Frontend logging verification |
| Phase 7 (Security) | Security event logging verification |
| Phase 8 (Review) | Log quality review |
| Phase 9 (Deployment) | Production log level configuration |
Based on bkamp.ai notification feature development:
| Cycle | Pass Rate | Bug Found | Fix Applied |
|---|---|---|---|
| 1st | 30% | DB schema mismatch | Schema migration |
| 2nd | 45% | NULL handling missing | Add null checks |
| 3rd | 55% | Routing error | Fix deeplinks |
| 4th | 65% | Type mismatch | Fix enum types |
| 5th | 70% | Calculation error | Fix count logic |
| 6th | 75% | Event missing | Add event triggers |
| 7th | 82% | Cache sync issue | Fix cache invalidation |
| 8th | 89% | Stable | Final polish |
┌─────────────────────────────────────────────────────────────┐
│ Iterative Test Cycle │
├─────────────────────────────────────────────────────────────┤
│ │
│ Cycle N: │
│ 1. Run test script (E2E or manual) │
│ 2. Claude monitors logs in real-time │
│ 3. Record pass/fail results │
│ 4. Claude identifies root cause of failures │
│ 5. Fix code immediately (hot reload) │
│ 6. Document: Cycle N → Bug → Fix │
│ │
│ Repeat until acceptable pass rate (>85%) │
│ │
└─────────────────────────────────────────────────────────────┘#!/bin/bash
# E2E Test Script Template
API_URL="http://localhost:8000"
TOKEN="your-test-token"
PASS_COUNT=0
FAIL_COUNT=0
SKIP_COUNT=0
GREEN='\033[0;32m'
RED='\033[0;31m'
YELLOW='\033[0;33m'
NC='\033[0m'
test_feature_action() {
echo -n "Testing: Feature action... "
response=$(curl -s -X POST "$API_URL/api/v1/feature/action" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"param": "value"}')
if [[ "$response" == *"expected_result"* ]]; then
echo -e "${GREEN}✅ PASS${NC}"
((PASS_COUNT++))
else
echo -e "${RED}❌ FAIL${NC}"
echo "Response: $response"
((FAIL_COUNT++))
fi
}
# Run all tests
test_feature_action
# ... more tests
# Summary
echo ""
echo "═══════════════════════════════════════"
echo "Test Results:"
echo -e " ${GREEN}✅ PASS: $PASS_COUNT${NC}"
echo -e " ${RED}❌ FAIL: $FAIL_COUNT${NC}"
echo -e " ${YELLOW}⏭️ SKIP: $SKIP_COUNT${NC}"
echo "═══════════════════════════════════════"# Feature Test Results - Cycle N
## Summary
- **Date**: YYYY-MM-DD
- **Feature**: {feature name}
- **Pass Rate**: N%
- **Tests**: X passed / Y total
## Results
| Test Case | Status | Notes |
|-----------|--------|-------|
| Test 1 | ✅ | |
| Test 2 | ❌ | {error description} |
| Test 3 | ⏭️ | {skip reason} |
## Bugs Found
### BUG-001: {Title}
- **Root Cause**: {description}
- **Fix**: {what was changed}
- **Files**: `path/to/file.py:123`
## Next Cycle Plan
- {what to test next}When implementing API/Backend:
When implementing Frontend:
On test request:
docker compose logs -f| Severity | Condition | Action |
|---|---|---|
| Critical | level: ERROR or status: 5xx | Immediate report |
| Critical | duration_ms > 3000 | Immediate report |
| Critical | 3+ consecutive failures | Immediate report |
| Warning | status: 401, 403 | Warning report |
| Warning | duration_ms > 1000 | Warning report |
| Info | Missing log fields | Note for improvement |
| Info | Request ID not propagated | Note for improvement |
✅ Request start (method, path, params)
✅ Request complete (status, duration_ms)
✅ Major business logic steps
✅ Detailed info on errors
✅ Before/after external API calls
✅ DB queries (in development)✅ API call start
✅ API response received (status, duration)
✅ Detailed info on errors
✅ Important user actions© ww-w-ai, Apache-2.0. 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 skills/zero-script-qa of ww-w-ai/bkit-claude-code.
Open the folder on GitHubat commit 85b4913
Zero Script QA 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 |
|---|---|---|---|---|---|---|
| Zero Script QA this skillww-w-ai/bkit-claude-code | 601 | — | ~4.1k | Automated safety check: Notes | Apache-2.0 | |
| Iron Proxy Gateway for NanoClawnanocoai/nanoclaw | 31k | — | ~4.6k | Automated safety check: Notes | MIT | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit | 260 | 6 repos | ~1.1k | Automated safety check: Notes | Custom licence | |
| LangBot Deployment Guidelangbot-app/LangBot | 18k | — | ~1.2k | Automated safety check: Notes | Apache-2.0 | |
| Build Openshell Mxc WindowsNVIDIA/OpenShell | 15k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 |
nanocoai/nanoclaw
Installs or refreshes Iron Proxy and its Iron Control web console for NanoClaw, with a local Docker setup, database, credentials and a human approval bridge.
GreptimeTeam/greptimedb
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
maslennikov-ig/claude-code-orchestrator-kit
Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup…
langbot-app/LangBot
Deploys and configures a LangBot instance with Docker Compose or Kubernetes, covering config.yaml, the Box sandbox runtime, the plugin runtime and the global API key.
NVIDIA/OpenShell
Maintain and validate OpenShell's build-only Windows MSVC lane for x64 and ARM64.
omnigent-ai/omnigent
Brings up the Omnigent server and Postgres as a Docker compose stack on any Docker host, and covers the Dockerfile's runtime and host build targets for extending it to a new platform.
ww-w-ai/bkit-claude-code
View audit logs, decision traces, and session history for AI transparency.
ww-w-ai/bkit-claude-code
bkend.ai authentication — email/social login, JWT tokens, RBAC, session management.
ww-w-ai/bkit-claude-code
bkend.ai project tutorials (todo to SaaS) and common error troubleshooting.
ww-w-ai/bkit-claude-code
bkend.ai onboarding — MCP setup, resource hierarchy, tenant/user model, first project.
ww-w-ai/bkit-claude-code
bkend.ai file storage — upload (presigned URL), download (CDN), visibility levels, buckets.
ww-w-ai/bkit-claude-code
bkit plugin help - list available functions including /pdca (9-phase feature cycle), /sprint (8-phase feature container, v2.1.13), /control (Trust L0-L4 + SPRINTAUTORUNSCOPE), /bkit-explore, and 40+…
Works with
Categories
Zero Script QA — test without scripts using structured JSON logging and Docker monitoring. Zero Script QA is an agent skill from ww-w-ai/bkit-claude-code. Zero Script QA — test without scripts using structured JSON logging and Docker monitoring.
Zero Script QA fits situations like: tasks that involve Containers.
Run `npx skills add ww-w-ai/bkit-claude-code --skill zero-script-qa -a claude-code`. Or copy the skill folder (skills/zero-script-qa in ww-w-ai/bkit-claude-code) into .claude/skills/zero-script-qa in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ww-w-ai/bkit-claude-code --skill zero-script-qa -a codex`. Or copy the skill folder (skills/zero-script-qa in ww-w-ai/bkit-claude-code) into .agents/skills/zero-script-qa 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 ww-w-ai/bkit-claude-code --skill zero-script-qa -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/zero-script-qa, .gemini/skills/zero-script-qa, .github/skills/zero-script-qa and .opencode/skills/zero-script-qa in your project.
Going by SKILL.md and its folder, Zero Script QA needs the command-line tools its instructions call (docker, claude and curl). Our summary lists: Python 3; Docker. Its frontmatter pre-approves these tools: Read, Glob, Grep, Bash.
SKILL.md contains no URLs. Its commands use docker and curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Zero Script QA is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.1k tokens (SKILL.md is roughly 17k 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 Zero Script QA: Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars) and LangBot Deployment Guide (langbot-app/LangBot, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ww-w-ai (a GitHub organization) maintains it in ww-w-ai/bkit-claude-code, which has 601 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on September 27, 2026.
Source: ww-w-ai/bkit-claude-code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.