RRepoGEO

REPOGEO REPORT · LITE

builderz-labs/mission-control

Default branch main · commit 85215c57 · scanned 5/17/2026, 8:21:15 PM

GitHub: 4,849 stars · 848 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
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 builderz-labs/mission-control, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening statement to clarify AI agent orchestration focus

    Why:

    CURRENT
    **Open-source dashboard for AI agent orchestration.** Manage AI agent fleets, dispatch tasks, track costs, and coordinate multi-agent workflows — self-hosted, zero external dependencies, powered by SQLite.
    COPY-PASTE FIX
    **Open-source dashboard for AI agent orchestration.** Mission Control provides a dedicated, self-hosted platform to manage and govern your AI agent fleets. It enables dispatching tasks, coordinating multi-agent workflows, and monitoring operational costs, offering a specialized solution beyond general MLOps or workflow tools.
  • mediumtopics#2
    Add more specific AI agent management topics

    Why:

    CURRENT
    agent-orchestration, ai-agents, ai-automation, ai-dashboard, claude, dashboard, developer-tools, llm, mcp, nextjs, open-source, openclaw, self-hosted, sqlite, task-management, typescript
    COPY-PASTE FIX
    agent-orchestration, ai-agents, ai-automation, ai-dashboard, ai-agent-management, agent-governance, agent-workflow, claude, llm, mcp, nextjs, openclaw, self-hosted, sqlite, task-management, typescript
  • lowreadme#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section titled 'Comparison with MLOps and Workflow Tools' to the README, explicitly outlining how Mission Control's focus on AI agent orchestration differs from general MLOps platforms (like MLflow, Kubeflow) and workflow orchestrators (like Apache Airflow).

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 builderz-labs/mission-control
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
mlflow/mlflow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. mlflow/mlflow · recommended 2×
  2. kubeflow/kubeflow · recommended 1×
  3. apache/airflow · recommended 1×
  4. Netflix/metaflow · recommended 1×
  5. Azure Machine Learning · recommended 1×
  • CATEGORY QUERY
    How can I orchestrate multiple AI agents and manage their workflows from a central dashboard?
    you: not recommended
    AI recommended (in order):
    1. Kubeflow (kubeflow/kubeflow)
    2. MLflow (mlflow/mlflow)
    3. Apache Airflow (apache/airflow)
    4. Metaflow (Netflix/metaflow)
    5. Azure Machine Learning
    6. Google Cloud Vertex AI
    7. AWS Step Functions

    AI recommended 7 alternatives but never named builderz-labs/mission-control. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source self-hosted platform helps monitor AI agent costs and task execution?
    you: not recommended
    AI recommended (in order):
    1. Langfuse (langfuse/langfuse)
    2. OpenTelemetry
    3. Jaeger (jaegertracing/jaeger)
    4. Grafana Tempo (grafana/tempo)
    5. Prometheus (prometheus/prometheus)
    6. Grafana (grafana/grafana)
    7. MLflow (mlflow/mlflow)
    8. Weights & Biases (wandb/wandb)
    9. Elasticsearch (elastic/elasticsearch)
    10. Logstash (elastic/logstash)
    11. Kibana (elastic/kibana)

    AI recommended 11 alternatives but never named builderz-labs/mission-control. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 builderz-labs/mission-control?
    pass
    AI did not name builderz-labs/mission-control — likely talking about a different project

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

  • If a team adopts builderz-labs/mission-control in production, what risks or prerequisites should they evaluate first?
    pass
    AI named builderz-labs/mission-control 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 builderz-labs/mission-control solve, and who is the primary audience?
    pass
    AI named builderz-labs/mission-control explicitly

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

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builderz-labs/mission-control — RepoGEO report