Local, git-versioned memory for AI coding agents. No RAG, no Docker, no external service. Capture, compile, recall over a local LLM wiki with on-device embeddings and an MCP server.
C-Rank Grade: D (Risky) - 0/100
External PR Merge Rate: -
Response Time: -
First Timer Success: -
This repository currently has no indexed public pull request reviews or activity on GitHub. Some large projects conduct code reviews via external tooling (e.g. Gerrit, Phabricator) or internal monorepos. As soon as public PR review activity is recorded, scores are computed automatically.
No public review history has been recorded on GitHub for this project yet. Check the project CONTRIBUTING guide or explore active, welcoming alternatives in the same language ecosystem.
No public pull request merge data is recorded on GitHub for ctxr-dev/llm-wiki-memory. Review workflows may be hosted externally or restricted to core teams.
Review speed is currently unmeasured due to no public GitHub PR activity. Refer to the repository's contributing guidelines for team workflow norms.
ctxr-dev/llm-wiki-memory does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Local, git-versioned memory for AI coding agents. No RAG, no Docker, no external service. Capture, compile, recall over a local LLM wiki with on-device embeddings and an MCP server.
We score this repo live from GitHub's public pull-request history - usually in under 30 seconds. Results are cached for 24 hours and refreshed when new commits land.
This repository has no indexed public pull request reviews or activity on GitHub yet. Some large projects conduct code reviews via external tooling or private repositories. As soon as public PR review activity is recorded, C-Rankâ„¢ computes scores automatically.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
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No cached good first issues currently tracked for ctxr-dev/llm-wiki-memory.
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When evaluating whether to contribute to ctxr-dev/llm-wiki-memory, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of ctxr-dev/llm-wiki-memory acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.
ctxr-dev/llm-wiki-memory has a recorded first-timer success rate of 0.0%. Repositories ranked Risky typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rankâ„¢ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 0.0 places ctxr-dev/llm-wiki-memory in the Risky tier.
The external pull request merge rate is 0.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
ctxr-dev/llm-wiki-memory does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for ctxr-dev/llm-wiki-memory are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.