markus-global/markus - Open Source PR Review Scorecard

The all-in-one AI workforce platform, to build AI agent teams. You are the boss.

C-Rank Grade: A (Welcoming) - 57/100

External PR Merge Rate: 84%

Response Time: 3d

First Timer Success: -

Frequently Asked Questions

Is markus-global/markus welcoming to first-time open-source contributors?

markus-global/markus has a recorded first-timer success rate of 0.0%. 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 markus-global/markus respond to incoming external pull requests in approximately 63.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 57.0 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 57.0 places markus-global/markus in the A tier.

What is the external contributor pull request merge rate for markus-global/markus?

The external contributor pull request merge rate for markus-global/markus is 84.2%, based on public PR activity from non-core contributors.

Are there Good First Issues available in markus-global/markus?

markus-global/markus currently has 4 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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markus-global/markus

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Active (30d)A•Welcoming(57/100)TypeScript

The all-in-one AI workforce platform, to build AI agent teams. You are the boss.

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AI Maintainer Review Guidelines

Review Persona

Strict Architecture Gatekeeper

Warmth Score
6.4/10
Patience Score
7.4/10
Nitpick Rate
45%

Strict review standards in markus-global/markus. Ensure PR scope matches issue requirements closely before requesting review.

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
2 days+
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
84.2%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
0.0%
No first-timer merges recorded in window

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
1 core
Single maintainer review bottleneck
Diagnostic Health HUD
84.2%
Merge Gauge
0.0%
1st-Timer
Community Vibe34/100

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Active Good First Issues (5)

View on GitHub

Why We have no repeatable way to answer "did this change make agents slower?" Until now, performance and stability work has relied on ad-hoc measurement (reading logs, watching a single run). Several P0 issues we fixed recently — heartbeat storms, lock granularity, tool timeouts, stream handling — were all things a throughput/latency harness would have surfaced earlier, or at least would now guard against regressing. Scope A benchmark harness, runnable from the repo, that measures agent throughput and latency on a fixed synthetic workload. Requirements Fixed workload — a small set of scripted task scenarios (e.g. N agents each running a multi-step task with a mix of tool calls), stored as fixtures. Same input every run. Deterministic where it can be, honest where it can't — LLM latency is not deterministic, so the harness must record the provider/model, and separate platform overhead (scheduling, routing, persistence, streaming) from provider latency as far as the instrumentat

📅 Opened Aug 16, 2026💬 0 comments
Quality: 50/100Contribute

Goal Markus ships 25 role templates (templates/roles/): researcher, developer, reviewer, ops, finance, HR, SRE... Add a role we don't yet have, following the same structure. Candidate roles (pick one or propose your own with a clear job description) security-auditor (review code/arch for vulnerabilities) data-analyst (SQL/reporting agent) seo-specialist (web visibility) sales-engineer (demo + technical sales) localization-manager (i18n coordination) How Study templates/roles/sre/ROLE.md and templates/roles/secretary/ROLE.md — note the structure: Identity & Expertise, Core Responsibilities, Workflow, Guardrails, metrics Create templates/roles/NEW-ROLE/ROLE.md with: Identity section (who the agent is, core expertise) Core Responsibilities (tables of duties, triggers, outputs) Workflow steps Guardrails / escalation rules Concrete success metrics Add the role to the README package table if roles are listed there Validate: the role directory is discoverable by the agent system (see

📅 Opened Aug 16, 2026💬 0 comments
Quality: 50/100Contribute

Goal Windows users currently must install via npm or the Electron desktop package. Add a PowerShell installer (iwr -UseBasicParsing ... | iex) that mirrors scripts/install.sh: detect architecture, download the right binary bundle, verify checksum, and print next steps. Reference files scripts/install.sh (existing bash installer — mirror its logic) scripts/build-binary.sh (what artifacts exist for Windows) markus.global/install.sh endpoint (where the script is served) Acceptance criteria install.ps1 works on PowerShell 5.1+ and 7+ (x64 + arm64) Downloads and verifies checksum, installs to %LOCALAPPDATA%\Markus (or similar), adds to PATH Documented in README Quick Start (Windows line) No secrets; respects standard security (RemoteSigned / execution policy guidance) Size: M · Skill needed: PowerShell, release engineering · Comment before starting to coordinate with release automation.

📅 Opened Aug 16, 2026💬 0 comments
Quality: 50/100Contribute

Where we actually are (v0.11.0) Since this issue was filed, the skill codec has grown a real multi-format front end: packages/core/src/skills/codec/ (detect.ts, parse.ts, render.ts, import-export.ts, frontmatter.ts). Formats the detector already handles (priority order in detectSkillPackageFormat): markus → mcp-server → soul → openclaw → claude (bare SKILL.md) → skillhub → agentscope. Registries wired up: our own Hub, SkillHub, and skills.sh (/api/skills/registry, /skillhub, /skillssh). So "support additional import formats beyond current adapters" is largely done — what's left is narrower and better specified. This issue is being rewritten to match. Gap No adapter for: A2A agent definitions — agent card / capability manifest → canonical skill. Cursor Rules (.cursor/rules/*.mdc) — closest field mapping to what we already model. n8n workflow nodes — widest reach, but needs the node graph modelled; heavier. Optional, lower priority: Claude Code subagent definition

📅 Opened Aug 16, 2026💬 1 comment
Quality: 50/100Contribute

Goal Add a Discord messaging adapter to packages/comms so teams can drive Markus from Discord. This also enables the planned Discord community channel. How Follow the existing adapter pattern — each adapter lives in packages/comms/src/NAME/ with adapter.ts + client.ts and is wired in packages/comms/src/router.ts: Study packages/comms/src/telegram/ (which is similar in shape) and packages/comms/src/slack/ Implement a minimal Discord client (discord.js or raw REST) supporting: receive messages, send messages, connect/disconnect Register the adapter in packages/comms/src/index.ts + router.ts Add unit tests mirroring packages/comms/test/telegram-adapter.test.ts Reference files packages/comms/src/telegram/, slack/, router.ts, index.ts packages/comms/test/telegram-adapter.test.ts Acceptance criteria discord.js (or equivalent) is a peerDependency, not bundled into core Adapter connects, receives, and sends with graceful error handling (token invalid, network down) Unit tests pass; pnpm

📅 Opened Aug 16, 2026💬 3 comments
Quality: 50/100Contribute
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Contributor Compatibility & Review Speed Analysis for markus-global/markus

When evaluating whether to contribute to markus-global/markus, 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 markus-global/markus acknowledge new external contributions in approximately 2 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 84.2% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to markus-global/markus

01

Is markus-global/markus welcoming to first-time open-source contributors?

markus-global/markus has a recorded first-timer success rate of 0.0%. 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 ~2 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 57.0 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 57.0 places markus-global/markus in the Welcoming tier.

04

What is the external contributor pull request merge rate for markus-global/markus?

The external pull request merge rate is 84.2%. 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 markus-global/markus?

Yes, markus-global/markus currently has 4 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 markus-global/markus 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.