മോഡൽ ഡിപ്ലോയ്മെന്റിനുള്ള വെബ് ആപ്പ് ഫ്രെയിംവർക്ക്
- **Docsify**: ഡോക്യുമെന്റേഷൻ സൈറ്റ് ജനറേറ്റർ
- **GitHub Actions**: CI/CD, സ്വയം വിവർത്തനങ്ങൾ
## Security Considerations
- **കോഡിൽ രഹസ്യങ്ങൾ ഇല്ല**: API കീകൾ അല്ലെങ്കിൽ ക്രെഡൻഷ്യലുകൾ ഒരിക്കലും കമ്മിറ്റ് ചെയ്യരുത്
- **ഡിപ്പെൻഡൻസികൾ**: npm, pip പാക്കേജുകൾ
model deployment
- **Docsify**: Documentation site generator
- **GitHub Actions**: CI/CD and automated translations
## Security Considerations
- **No secrets for code**: No ever commit API keys or credentials
- **Dependencies**: Keep
కోసం వెబ్ అప్లికేషన్ ఫ్రేమ్వర్క్
- **Docsify**: డాక్యుమెంటేషన్ సైట్ జనరేటర్
- **GitHub Actions**: CI/CD మరియు ఆటోమేటెడ్ అనువాదాలు
## Security Considerations
- **కోడ్లో రహస్యాలు లేవు**: API కీలు లేదా క్రెడెన్షియల్స్ ఎప్పుడూ కమిట్ చేయవద్దు
- **డిపెండెన్సీలు**: npm మరియు
webhook
events instead of adding `pull_request_target` workflows
- NEVER suppress the `dangerous-triggers` security lint; extend the automation dispatcher in a
separate pull request if it does not support
solutions](docs/solutions/) when the affected area has a prior fix — organized by category directory (`security-issues/`, `logic-errors/`, `conventions/`, …) with YAML frontmatter (`module`, `component`, `problem_type`, `tags`) to grep
jobs expect ephemeral hosts; do not run packaging suites on your workstation.
- **Security**: Default dev clusters enable security; use `elastic-admin:elastic-password` or disable with `-Dtests.es.xpack.security.enabled=false`.
- **Cursor/Copilot rules
lessons (numbered 00-18) covering fundamentals, design patterns, frameworks, production deployment, local/on-device agents, and security of AI agents.
**Key Technologies:**
- Python 3.12+
- Jupyter Notebooks for interactive learning
- AI Frameworks: Microsoft
lessons (numbered 00-18) covering fundamentals, design patterns, frameworks, production deployment, local/on-device agents, and security of AI agents.
**Key Technologies:**
- Python 3.12+
- Jupyter Notebooks for interactive learning
- AI Frameworks: Microsoft
number 00-18) wey cover fundamentals, design patterns, frameworks, production deployment, local/on-device agents, plus security for AI agents.
**Key Technologies:**
- Python 3.12+
- Jupyter Notebooks for interactive learning
- AI Frameworks: Microsoft
scopes; Ruflo records coordination.
6. Test focused, regression, and failure paths.
7. Validate types, security, policy, compatibility, and artifact integrity.
8. Benchmark a source-bound candidate against a source-bound
calling codegraph entirely (maintainer-observed, repeatedly). `isError` is reserved for genuine "stop trying" cases: security refusals (`PathRefusalError`) and real malfunctions (which carry a retry-once note). Every expected/recoverable condition — project
streams — use abort signals for cleanup
- Return proper HTTP status codes (4xx/5xx)
### Security
- **Never** use `eval()`, `new Function()`, or implied eval
- Validate all inputs with Zod schemas
- Encrypt credentials
form of the `/publish` command |
| `remove-deadcode/` | NEW | Skill form of the `/remove-deadcode` command |
| `security-research/` | NEW | Team Mode security research audit: 3 vulnerability hunters + 2 PoC engineers |
| `codex
Remove unused code with LSP-verified safety + atomic commits. |
| `/security-research` | Run the Team Mode security-research audit with 3 vulnerability hunters and 2 PoC engineers. |
## OTHER CONTENTS
- `background-tasks.json` — Runtime state
equality between real artifacts, and observable runtime behavior such as parsing, routing, dispatch, state, security, and dynamic input propagation.
- Treat `tests/hashline/` as its own Bun package. Preserve its lockfile
relevant, test evidence, affected platforms/runtimes, and update `CHANGELOG.md` or docs for user-facing changes.
## Security & Configuration Tips
Do not commit secrets, local config, or generated worktree artifacts. Before release-facing