RRepoGEO

REPOGEO REPORT · LITE

jingkaihe/matchlock

Default branch main · commit e18e585b · scanned 6/11/2026, 2:36:56 AM

GitHub: 589 stars · 32 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface jingkaihe/matchlock, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 to clearly state the project's category

    Why:

    CURRENT
    # Matchlock

> **Experimental:** This project is still in active development and subject to breaking changes.

Matchlock is a CLI tool for running AI agents in ephemeral microVMs - with network allowlisting, secret injection via MITM proxy, and VM-level isolation. Your secrets never enter the VM.
    COPY-PASTE FIX
    # Matchlock: A Secure MicroVM Sandbox for AI Agents

> **Experimental:** This project is still in active development and subject to breaking changes.

Matchlock is a CLI tool for running AI agents in ephemeral microVMs - with network allowlisting, secret injection via MITM proxy, and VM-level isolation. Your secrets never enter the VM.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/jingkaihe/matchlock

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface jingkaihe/matchlock
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
kubernetes/kubernetes
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. kubernetes/kubernetes · recommended 2×
  2. kata-containers/kata-containers · recommended 2×
  3. GCP Confidential Computing · recommended 1×
  4. Azure Confidential Computing · recommended 1×
  5. AWS Nitro Enclaves · recommended 1×
  • CATEGORY QUERY
    How to safely execute AI agent code with strong isolation and secret protection?
    you: not recommended
    AI recommended (in order):
    1. GCP Confidential Computing
    2. Azure Confidential Computing
    3. AWS Nitro Enclaves
    4. Docker (moby/moby)
    5. Kubernetes (kubernetes/kubernetes)
    6. Open Enclave SDK (openenclave/openenclave)
    7. Intel SGX SDK
    8. Kata Containers (kata-containers/kata-containers)

    AI recommended 8 alternatives but never named jingkaihe/matchlock. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools for sandboxing AI agents in ephemeral, isolated Linux environments?
    you: not recommended
    AI recommended (in order):
    1. Docker
    2. Kubernetes (kubernetes/kubernetes)
    3. Firecracker (firecracker-microvm/firecracker)
    4. Kata Containers (kata-containers/kata-containers)
    5. gVisor (google/gvisor)
    6. LXC (lxc/lxc)

    AI recommended 6 alternatives but never named jingkaihe/matchlock. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of jingkaihe/matchlock?
    pass
    AI named jingkaihe/matchlock explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts jingkaihe/matchlock in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jingkaihe/matchlock explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo jingkaihe/matchlock solve, and who is the primary audience?
    pass
    AI named jingkaihe/matchlock explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of jingkaihe/matchlock. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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jingkaihe/matchlock — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
jingkaihe/matchlock — RepoGEO report