tommy0103/obelisk - Open Source PR Review Scorecard

Every past session, subagent, and workflow -- queryable by your agent, browsable by you

C-Rank Grade: A (Welcoming) - 64/100

External PR Merge Rate: 47%

Response Time: 9h

First Timer Success: 33%

Frequently Asked Questions

Is tommy0103/obelisk welcoming to first-time open-source contributors?

tommy0103/obelisk has a recorded first-timer success rate of 33.3%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in tommy0103/obelisk respond to incoming external pull requests in approximately 8.5 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 64.3 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 64.3 places tommy0103/obelisk in the A tier.

What is the external contributor pull request merge rate for tommy0103/obelisk?

The external contributor pull request merge rate for tommy0103/obelisk is 46.9%, based on public PR activity from non-core contributors.

Are there Good First Issues available in tommy0103/obelisk?

tommy0103/obelisk currently has 2 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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tommy0103/obelisk

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Every past session, subagent, and workflow -- queryable by your agent, browsable by you

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.7/10
Patience Score
8.2/10
Nitpick Rate
30%

Collaborative maintainer environment in tommy0103/obelisk. Reviews community pull requests with focus on project quality.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
8 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
46.9%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
33.3%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
11 core
Highly collaborative maintainer core
Diagnostic Health HUD
46.9%
Merge Gauge
33.3%
1st-Timer
Community Vibe52/100

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GetMerged C-Rank badge for tommy0103/obelisk
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Active Good First Issues (3)

View on GitHub

Proposal Add a minimax provider adapter that indexes MiniMax Code (mcode) session history alongside the existing claude / codex / deepseek / kimi / pi providers. Full design spec: docs/minimax-provider-adapter-spec.md (currently in the working tree; will accompany the implementation PR). Source format mcode has two runtime generations on disk; v1 (event-sourced ledger.jsonl) is retired, v2 is current: Data root ~/.minimax (legacy ~/.mavis); sessions under v2/sessions/YYYY/MM/DD/<sessionDir>/ — grouped by creation date, not by project. messages.jsonl: the canonical LLM history, one envelope per line (message_id, turn_id, Pi-format message body, optional turn_config, optional history_artifact at position 0). Session metadata (title, workspaceDir, parent links) lives only in v2/sqlite/runtime-state.sqlite. Compaction rewrites messages.jsonl wholesale: the pre-compaction history is first published to an immutable snapshots/gNNNN--<compactionId>.jsonl, then the file restarts from a compa

📅 Opened Sep 19, 2026💬 0 comments
Quality: 90/100Contribute

Evaluation: Obelisk on real coding tasks This report evaluates whether access to prior coding-agent history improves real software-engineering work. It covers three complementary settings: Cross-task archive: 81 SWE-bench tasks over four repositories, with history produced by other agents on earlier issues. Own-failure retry: 34 frozen SWE-bench failures, with the agent's failed attempt available as history for a second attempt. Longitudinal work: one fixed sequence of six real jazzband/tablib issues, where the same agent configuration accumulates its own prior sessions across tasks. The first two panels use official SWE-bench test grading. The longitudinal panel uses the CL-Bench codebase_adaptation grader. All effective runs use deepseek-v4-flash through Pi. Executive result Other agents' cross-task history: the official Obelisk skill produced exactly the same result as no memory on the content-clean primary panel: 34/68 vs 34/68, paired difference 0.0 pp (95% bootstrap CI -5.9 to

📅 Opened Aug 9, 2026💬 2 comments
Quality: 55/100Contribute

TL;DR Replaying a Kimi context.undo event leaves injection messages in the index that Kimi itself removed from the context. Low impact today — the leftovers are reminder-class records — but the divergence should be closed before undone content is ever surfaced rather than dropped. Priority: low. No user-visible symptom has been observed. This is a fidelity gap found by reading both implementations side by side, not a reported bug. Problem Kimi's context.undo is a tail truncation at a user-turn boundary: it removes the last N real user prompts and everything that followed them. The Kimi adapter replays that event to keep the index consistent with what Kimi actually has in context. The two implementations disagree on one class of record. Kimi counts injection messages as non-undoable when deciding where to cut, but still removes them when applying the cut. The adapter treats "skip while counting" as "skip while removing", so injections inside the undone range survive into the index

📅 Opened Aug 3, 2026💬 0 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for tommy0103/obelisk

When evaluating whether to contribute to tommy0103/obelisk, 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 tommy0103/obelisk acknowledge new external contributions in approximately 8 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 46.9% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to tommy0103/obelisk

01

Is tommy0103/obelisk welcoming to first-time open-source contributors?

tommy0103/obelisk has a recorded first-timer success rate of 33.3%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~8 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 64.3 C-Rank™ score represent?

The C-Rank™ 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 64.3 places tommy0103/obelisk in the Welcoming tier.

04

What is the external contributor pull request merge rate for tommy0103/obelisk?

The external pull request merge rate is 46.9%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in tommy0103/obelisk?

Yes, tommy0103/obelisk currently has 2 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for tommy0103/obelisk 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.