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.
git clone --depth 1 https://github.com/kumaran-is/claude-code-onboardingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/kumaran-is/claude-code-onboarding/security-hardening)<a href="https://agentmods.dev/commands/kumaran-is/claude-code-onboarding/security-hardening"><img src="https://agentmods.dev/badge/commands/kumaran-is/claude-code-onboarding/security-hardening.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00027 | $0.01014 |
| Opus 5 | $0.00014 | $0.00507 |
| Sonnet 5 | $0.00005 | $0.00203 |
| Haiku 4.5 | $0.00003 | $0.00101 |
Grade A, and why
security-hardening 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 4d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Hardening Pipeline
Scope: $ARGUMENTS (default: entire project if no argument provided).
Phase 1: Assessment
Step 1 -- Initial vulnerability scan
Dispatch security-reviewer agent (model: opus) to perform:
- SAST analysis across changed files
- Secret scanning (API keys, tokens, passwords in source)
- OWASP Top 10 checklist review
Output: findings categorized by CVSS severity (Critical / High / Medium / Low).
Step 2 -- Threat modeling
Dispatch threat-modeling-expert agent (model: sonnet) to perform:
- STRIDE analysis on the target scope
- Attack surface mapping (entry points, data flows, external integrations)
- Trust boundary identification
Output: threat model document with risk scores per threat.
Step 3 -- Architecture security review
Dispatch architect agent to evaluate:
- Zero-trust architecture compliance
- Defense-in-depth gaps (missing layers)
- Privileged access patterns and service-to-service auth
Output: architecture security assessment with remediation priorities.
Phase 2: Remediation
Step 4 -- Critical fix dispatch
Dispatch security-reviewer agent (model: opus) to fix all CVSS 7+ findings:
- SQL injection -- parameterized queries / prepared statements
- XSS injection points -- output encoding, sanitization
- Authentication bypass patterns -- secure session validation
- Insecure direct object references -- authorization checks on every access
Step 5 -- Backend hardening
Apply hardening across all backend layers:
- Java/Spring Boot: Spring Security config, CSRF protection, security headers
- NestJS: Helmet middleware, rate limiting (
@nestjs/throttler), global validation pipes - Python/FastAPI: Input validation with Pydantic v2, dependency injection for auth guards
- Common: AES-256 encryption for PII fields, OAuth2/OIDC integration, secure session config
Step 6 -- Mobile hardening
Dispatch flutter-security-expert agent (model: sonnet) to apply:
- Certificate pinning for all API endpoints
- Flutter Secure Storage for tokens and sensitive data
- Code obfuscation configuration (--obfuscate with --split-debug-info)
- Jailbreak/root detection with runtime integrity checks
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.
- 4d ago First seen · 112 lines · 27 tokens per session scan A b47d46cf7675
security-hardening is a command published in the GitHub repository kumaran-is/claude-code-onboarding (35 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 1,014 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 2026-09-03.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.