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A tool to solve the Agent Supply Chain pandora box

Hacker News

A tool to solve the Agent Supply Chain pandora box

An OSS tool I built to manage agent configuration (plugins, skills, et al) as we do code dependencies. With a portable manifest, lockfile, and audits. APM ships as a CLI. Install it first e.g. with brew or pip and then: "apm install <org>/<repo>" or "apm install plugin@marketplace" That will resolve the dependency (through Artifactory if configured too) and pin the sha or version to the lockfile after scanning for hidden unicode. It then deploys to any agent runtime you may be using (e.g. Copilot, Codex, Cursor, Claude). I built this over a year working with large scale enterprises clamoring for it.

Visit product View on Hacker NewsMar 31, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, cursor, claude · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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