CodeJury
Terminal-first, knowledge-grounded multi-agent software delivery pipeline: scope requirements, implement changes, run tests, and gate pull requests with deterministic QA and ensemble code review.
Supply asset profile
Coding and developer agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Agent fit
Claude Code + OpenAI Agents + CLI
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add krishagarwal314/CodeJury
Maintenance
fresh
20d since push
Risk
Needs review
Dependency or permission surface needs review
GitHub quality
137
94/100 Quality · 79/100 Trust
Coverage tags
Review notes
Dependency or permission surface needs review · Permission surface may require sandboxing
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
137 GitHub stars
Repo activity
137 stars, 23 forks
Maintenance
20d since push
License
MIT
Install
npx skills add krishagarwal314/CodeJury
Install safety
standard package or runtime install path
Permission surface
secrets or environment access, shell or command execution
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Review before production
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 137 stars, 23 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- GitHub automation workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Inspect repository metadata
Suited agents
Install decision
- Command
- npx skills add krishagarwal314/CodeJury
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 71/100
- Audit
- 87/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add krishagarwal314/CodeJuryDo not use when
- teams that need a vendor-supported SLA
- high-compliance environments without internal security review
- No major risk signals from current metadata
- High-risk permission hints: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Agent safety v2
47/100 · Avoid automatic install
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Shell or command execution
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
high
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- High-risk permission hints: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install krishagarwal314-codejuryAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20CodeJury%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20CodeJury%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/krishagarwal314-codejury/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use CodeJury in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20CodeJury%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/krishagarwal314-codejury/install
Install command: npx skills add krishagarwal314/CodeJury
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/krishagarwal314-codejury/install
LLM text format
/api/skills/krishagarwal314-codejury/install?format=text
Find alternatives
/api/skills/search?q=CodeJury&limit=3
Agent prompt
Use CodeJury for this task. Review https://www.openagentskill.com/api/skills/krishagarwal314-codejury/install, then install with: npx skills add krishagarwal314/CodeJuryRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/krishagarwal314-codejury
LLM text
/api/registry/manifest/krishagarwal314-codejury?format=text
Install alias
/api/registry/install/krishagarwal314-codejury
Recommend
/api/registry/recommend?task=Use%20CodeJury%20in%20an%20agent%20workflow&limit=3
Agent fit
GitHub automation
Use-case tags
Platforms
Python, Claude Code, OpenAI Agents
Audit report
Needs review · 87/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Primary pick for GitHub automation
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
GitHub automation
Trust label
Production-ready
Install path
Command ready
Use when
- GitHub automation workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 94/100 quality profile
- 1 OpenAgentSkill engagement events
review first
- No major risk signals from current metadata
Implementation path
- 1Install it in a sandbox agent and run one GitHub automation task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Sandbox only
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO137 GitHub stars
Stars/forks activity
CHECK137 stars, 23 forks; issue activity unavailable in current metadata
Recent maintenance
PASS20d since push
License clarity
PASSMIT
Good signals
- Manually verified listing
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 137 stars, 23 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Excellent candidate for agent workflows
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Use this skill in these scenarios
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Add it to a complete workflow
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Compare before you install
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Overview
<div align="center">
<img src="docs/screenshots/cli-session.gif" alt="CodeJury in the terminal: which model owns each stage, an indexed repository, a request as tickets, the Planner's verified plan, and a four-judge jury with each juror's verdict" width="900">
<sub>One unbroken session against <a href="https://github.com/go-gitea/gitea">go-gitea/gitea</a> — Go, TypeScript and templates, 120,521 symbols indexed. Which model owns each of the six stages, the request that started it, the ticket it became, the Planner's plan pinned to real symbols, then the jury: four judges on four different providers, each with its own verdict, one of them dissenting. Every screen is real state from a delivery that actually ran; nothing here is a mockup.</sub>
<br>
### A terminal-first coding agent that is reviewed by a **jury**, not by a judge.
**One LLM grading another LLM's code is not a review — it is a coin flip with a confident voice.** So CodeJury sends every change to a panel of independent, differently-modelled judges and a foreperson who synthesizes one verdict. And because a panel costs tokens, the agent earns them back: it navigates your repository through a **persistent code graph plus semantic search over graph nodes**, so it *looks up* where a change goes instead of burning context rediscovering it.
**And nothing about it is fixed.** Six stages — *knowledge, PM, planner, dev, QA, review* — and you choose the provider and model for every one of them, live, from the terminal. Claude plans, Codex writes, GPT reviews. The jury itself is a roster you seat, re-model and re-brief yourself. All of it runs on the coding CLIs you're already logged into, so **you may not need an API key at all**.
<br>
`pip install` · one command to run · no API key required · **macOS · Linux · Windows**
[](https://github.com/krishagarwal314/CodeJury/actions/workflows/ci.yml) ](https://www.openagentskill.com/skills/krishagarwal314-codejury)
[](https://www.openagentskill.com/skills/krishagarwal314-codejury)
[](https://www.openagentskill.com/skills/krishagarwal314-codejury/audit)
[](https://www.openagentskill.com/skills/krishagarwal314-codejury)Author
krishagarwal314✓
@krishagarwal314
Platform fit
Health signals
- GitHub stars
- 137
- Quality score
- 58/100
- Last GitHub push
- Aug 3, 2026
- Framework hints
- 1
- OpenAgentSkill views
- 1
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Sandbox only
- GitHub adoption137 GitHub starsINFO
- Stars/forks activity137 stars, 23 forks; issue activity unavailable in current metadataCHECK
- Recent maintenance20d since pushPASS
- License clarityMITPASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime riskcommand execution surface, credential or environment accessFIX
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