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Adopt AI agents without adopting their risk.
Skills, MCP servers, instruction files, hooks, and agent configuration now decide what your agents read, execute, and send outside your environment. Heeler inventories that agent supply chain across every repository, scores what it finds, and enforces policy at the pull request — so teams can move fast on agents without inheriting unreviewed trust.
Agent adoption outran agent governance.
The old model — scan, triage a backlog, file tickets — assumed humans set the pace. Agents broke that assumption. By the time a finding reaches a queue, ten more PRs have merged. Security has to run at the speed the code is written.
An unreviewed supply chain
Skills and MCP servers arrive from marketplaces and public repositories, get copied between teams, and change after anyone looked at them. Most never pass through code review at all.
Developer-level access
An instruction file can lead a trusted agent to read secrets, run commands, or reach an external service — with whatever access the developer running it already has.
Invisible to existing tooling
SAST and SCA were built for source code and dependencies. Agent configuration is neither, so it lands in your repositories without ever being examined.
Know what your agents are actually running.
Heeler discovers every agent file across your repositories — skills, subagents, hooks, MCP configuration, and instruction files — whichever assistant produced them, and keeps that inventory current as they change.
Exploitable, not theoretical
Reachability and runtime context filter findings down to the ones that can actually be reached and run — the rest drop in priority.
Across functions and files
Interprocedural analysis follows tainted data through the whole call path, catching flaws a single-file scanner misses.
Secrets, proven live
Leaked credentials are validated against the real provider — you chase the keys that still work, not dead strings.
Dependencies that matter
Vulnerable and malicious packages are flagged when they're reachable and running, with the safe version to move to.
Stop risky agent configuration before it merges.
Agent files are evaluated on the pull request like any other change, on your SCM's native checks. Risky configuration can warn the reviewer or block the merge — so policy applies at the moment new agent capability enters the codebase.
PR guardrails
Block, warn, or observe net-new vulnerabilities, secrets, and risky dependencies at the pull request — without failing on inherited debt.
At the keyboard
The same checks run in the terminal and pre-commit, so the agent and the developer catch issues before a commit is ever made.
Before code is written
The skills and configs your agents run are vetted too — so the agent itself isn't the thing introducing risk.
Own it like any other finding class.
Every file carries a safety score and a verdict explaining what it would have done. Findings route to the team that owns the repository through the trackers and channels they already use, so agent risk is worked and closed rather than noted.
Deterministic remediation
The exact upgrade or change is computed and compile-checked, not guessed — a fix you can trust to merge.
Merge-ready PRs
Fixes arrive as pull requests routed to the owning team, not as tickets that sit in a queue.
Burns down the backlog
Existing debt is grouped and remediated alongside the net-new — the pile actually shrinks.
See which agent files are already in your repositories.
A demo runs Heeler across your repos — the exploitable flaws, live secrets, and risky dependencies your AI agents introduced, each with the fix.
