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@hypabolic/hypa

Skill Development Usable
Works inClaude Code
Usable Scanned — metadata only

Reduces token overhead in agentic workflows by compressing verbose shell output while maintaining MCP tool access, enabling faster inference and lower API co…

Local context runtime for coding agents: compress shell output, query code, and proxy MCP tools

155 starsFSL-1.1-ALv2Free
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Reduces token overhead in agentic workflows by compressing verbose shell output while maintaining MCP tool access, enabling faster inference and lower API costs for code-generation tasks.

Teams deploying AI coding agents who need efficient local context management and tool integration without external service dependencies.

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https://www.npmjs.com/package/@hypabolic/hypa

By GitHub Actions

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
npx @hypabolic/hypa

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.

First thing to try

After installing, paste this into Claude:

Help me compress large shell command outputs to reduce token usage in agent workflows
CostFree

Trust Signals Auto-scanned

Stars155Contributors7Last updated2026-07-17LicenseFSL-1.1-ALv2Weekly downloads3,073Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-07-25 · scanner v1

Community Pulse New

No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 155 GitHub stars; 7 contributors; last commit 8d ago; license FSL-1.1-ALv2.

Things to check

  • Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
1/5
Versatility
3/5
Reliability
4/5
Security
3/5
Overall score2.55 / 5.00 UsableEvaluatedJul 2026
Scored from trust signals (evidence-eval-v1): 155 GitHub stars; 7 contributors; last commit 8d ago; license FSL-1.1-ALv2.

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