Higher agent success rate
Increase your reliability score, reduce failure.
Works with
Works with
Increase your reliability score, reduce failure.
IDE integration enables inline suggested fixes.
Solve issues before they become problems.
Maps to compliance frameworks, hardens agents.
Better tool calling, limits failed retries.
For OpenShell, Microsoft ACS, and more.
Total visibility with CycloneDX and VEX.
Generates production-grade metadata for you.
| Category | Example Finding |
|---|---|
| Tool definition | Missing tool description causing incorrect LLM selection |
| Input validation | User-controlled parameter passed without validation |
| Shell safety | Shell command built from unsanitized input |
| Path safety | Path traversal vulnerability in file tool |
| Network | HTTP request without timeout or SSRF protection |
| Retry logic | Duplicate execution because retries aren't idempotent |
| Error handling | Exception swallowed, agent silently fails |
| Observability | Missing traces, logs, or token cost reporting |
| Guardrails | Dangerous tool callable without approval |
| Repository hygiene | SDK version drift, missing configuration, stale metadata |
| Specialized | Framework-specific issues across Claude SDK, OpenAI Agents SDK, Google ADK, MCP, Skills, and OpenShell |
Coverage
Every declaration, config captured
Markdown agent definitions
Custom function tools
Built-ins: shell, search, computer
SKILL.md + bundled files
Command prompts
Registrations + configs
Input / output
Memory + persistence
Agent-to-agent edges
Manifests + marketplaces
Settings + tool grants
The headline 187 rules: missing guardrails, over-broad permissions, shell and code execution, SSRF.
Credentials committed in agent and skill artifacts.
Vulnerable dependencies, matched against an OSV snapshot (opt-in).
Least-privilege sandbox policies
Native integration (MCP, GitAgent)
Reduced load, smarter high risk policy
SLSA + Sigstore attestations
Better tool calling accuracy
Resilient execution and self-recovery
Superior prompting and docs
Trustabl scans AI agents, tools, and skills for production-readiness issues — flagging reliability, safety, and configuration gaps with clear fix suggestions. Free remediation via VS Code, Cursor, and Skill.md is coming soon. Think of it as a specialized linter for agentic systems.
Trustabl is built for AI engineers, platform teams, and security/compliance teams who are building or running agentic systems in production and want tools that are reliable, observable, and policy-compliant.
Most tools are fully hardened in under 60 seconds. You connect your GitHub repo, and Trustabl scans, enriches, and generates most of the metadata automatically.
No. Trustabl works on top of your existing tools. It analyzes your code, documentation, and behavior, then generates enriched metadata and optional policy files without modifying your source code.
No. Skills (SKILL.md) teach the agent how to perform a task or workflow. Trustabl Agent Analyzer (TAA) makes the tools themselves reliable, safe, and production-ready. Skills focus on process. TAA focuses on resilience, validation, policy, observability, and supply-chain trust. The two are highly complementary — great skills need hardened tools underneath them.
Yes. OpenShell secures the runtime environment. Trustabl hardens the tools the agents call inside that environment. TAA automatically generates least-privilege policies, egress rules, binary requirements, and sandbox compatibility metadata that OpenShell can consume directly. Together they deliver defense-in-depth: secure runtime + production-hardened tools.
Smarter models can describe tools better, but they cannot reliably harden them for production. Trustabl adds critical production-grade elements models cannot consistently provide: structured validation rules, circuit breakers, policy enforcement, cryptographic attestations, least-privilege OpenShell policies, and SLSA supply-chain provenance.
Yes. Trustabl generates audit-ready metadata, including structured logging schemas, data lineage, retention policies, and SLSA attestations that make compliance evidence much easier to produce.
Complementary. Trustabl automatically generates OpenTelemetry (OTEL) tracing, structured logging, and metrics configurations that feed directly into LangSmith, Langfuse, or any observability platform. We also surface key aggregated metrics and production readiness insights ourselves.
They focus on securing the agent runtime and detecting threats. Trustabl focuses on hardening the tools agents use so they are production-safe, policy-compliant, and resilient by design. We prevent problems at the source rather than only detecting them at runtime.
Yes. The Trustabl Agent Analyzer is fully open source — scan any agent codebase for free, no account required. Free remediation via VS Code, Cursor, and Skill.md is coming soon. No credit card, no gates.
We're focused on the free remediation experience: GitHub Actions integration, expanded Skill.md support, and skills file scanning. Team governance and compliance features are planned for later.
Yes. Trustabl is essentially a specialized linter for AI agents. While traditional linters (like ESLint or Ruff) focus on code style, syntax, and general bugs, Trustabl analyzes your AI agents, tools, prompts, and SDK configurations for reliability, safety, and production readiness — flagging patterns that expose you to prompt injection, missing timeouts, tool misconfigurations, and guardrail gaps that standard linters miss. Think of it as "ESLint for AI agents" — it runs in CI/CD, gives clear explanations and fix suggestions, and helps you ship safer, more robust agentic systems.
After scanning, Trustabl generates fix suggestions for every finding. Safe, low-risk fixes will be applied automatically. Higher-risk changes will be surfaced for your review before anything is committed. Remediation will be available as a VS Code/Cursor extension and as a Skill.md for other agent environments. Coming soon.
No. You have full control. Trustabl auto-applies safe fixes (like adding missing timeouts or standardizing retry logic) and surfaces higher-risk changes for your explicit review and approval. You decide what gets committed.