Pyproj

STRONG · 88
Community indexed

Python interface to PROJ (cartographic projections and coordinate transformations library)

Downloads0
Stars1.2K
Version1.0.0
Quality100/100 · Excellent
Trust88/100 · Review then install
Audit94/100 · Safe to try

Supply asset profile

Coding and developer agents

Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.

Browse track

Scenario

GitHub automation

I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add pyproj4/pyproj

Maintenance

fresh

17d since push

Risk

Safe to try

No major risk signals from available metadata

GitHub quality

1.2K

100/100 quality · 91/100 trust

Coverage tags

CodingGitHub automationgeo-sciencegeospatialanalysis

Review notes

No major risk signals from available metadata

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

Excellent
100

High-confidence pick with strong adoption and healthy maintenance signals.

Trust

Review then install
88

Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.

Audit

Safe to try
94

Install readiness, security metadata, maintenance, and adoption risk.

Trust Score v5

Agent install candidate

Use as the primary candidate after human or sandbox review.

PythonGeospatialCodexClaude CodeCursor

Stars

1.2K GitHub stars

Repo activity

1.2K stars, 234 forks

Maintenance

17d since push

License

MIT

Install

npx skills add pyproj4/pyproj

Install safety

standard package or runtime install path

Permission surface

filesystem or document access

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Low metadata risk

  • No major trust warnings detected from available metadata

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.

Open JSON

Suited tasks

  • GitHub automation workflows
  • Claude Code teams
  • teams that value GitHub adoption signals
  • Inspect repository metadata

Suited agents

PythonGeospatialCodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add pyproj4/pyproj
Policy
allow
Human review
no

Trust and risk

Trust
88/100
Audit
94/100
Risk level
Safe to try

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add pyproj4/pyproj

Do not use when

  • teams that need a vendor-supported SLA
  • high-compliance environments without internal security review
  • No OpenAgentSkill engagement data yet
  • No major trust warnings detected from available metadata
  • Production credentials, payments, or irreversible account changes without explicit human review

Agent safety v2

86/100 · Safe to install with normal review

Verifiedallow

Strong metadata, audit, install, and review signals. Suitable for agent shortlists after normal workspace review.

Allow agent install in a sandbox or low-risk workspace, then promote after one successful narrow task.

Resolve via API

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.

Install targets

Install this skill in your agent workflow

Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.

skill install

OpenAgentSkill CLI

Use the registry command when your workflow supports the OpenAgentSkill installer.

$ npx skills add pyproj4/pyproj

Agent 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 text plan

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 Pyproj in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Pyproj%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/pyproj4-pyproj/install
Install command: npx skills add pyproj4/pyproj
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.

Open install API

Agent prompt

Use Pyproj for this task. Review https://www.openagentskill.com/api/skills/pyproj4-pyproj/install, then install with: npx skills add pyproj4/pyproj

Registry 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.

Open manifest

Agent fit

100/100

GitHub automation

Platforms

Python, Geospatial, Claude Code

Audit report

Safe to try · 94/100

Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.

View audit reportView eval report

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.

100
Readiness
Adopt
Stage

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
  • teams that value GitHub adoption signals

Evidence

  • 1,214 GitHub stars
  • recent repository activity
  • install command or GitHub repo available
  • 100/100 quality profile

Review first

  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one GitHub automation task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Review then install

Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.

88
Trust score

GitHub adoption

PASS

1.2K GitHub stars

Stars/forks activity

INFO

1.2K stars, 234 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

17d since push

License clarity

PASS

MIT

Good signals

  • Manually verified listing
  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Meaningful GitHub adoption signal
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Use as the primary candidate after human or sandbox review.

Quality profile

Excellent candidate for agent workflows

High-confidence pick with strong adoption and healthy maintenance signals.

100
GitHub stars
1.2K
Freshness
17d ago
Install ready
Yes
License
MIT

Workflow fit

Use this skill in these scenarios

Stack fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills in this category, ranked with the same readiness and quality signals.

Compare all

Overview

Python interface to PROJ (cartographic projections and coordinate transformations library)

Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.

Platform Compatibility

pythonFULL
geospatialFULL

Technical Details

Version
1.0.0
License
MIT
Last Updated
6/21/2026
Published
6/21/2026

Frameworks & Tools

PythonGeospatial

Decision snapshot

Primary pick

100
Ready
Adopt
Stage

1,214 GitHub stars

Audit snapshot

Install review

Install and adoption review

94
Safe to try
Security
89/100
Maintenance
100/100
Install
92/100
Open full auditOpen eval report

Agent-proven evidence

Agent Proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Install

Add to agent workflow

Free and open source. Review the audit before production use.

Growth loop

Share kit

X

Scenario-led draft for Pyproj, ready for a manual X post.

Curator note
Most coding agents don't fail from lack of model power. They fail when repo context disappears.

Pyproj gives coding agents a repeatable way to plan, patch, review, or ship.

1.2K stars

https://www.openagentskill.com/skills/pyproj4-pyproj?ref=x
#AIAgents
Open X draft
Optional reply with install command
Listing + install path for Pyproj:
https://www.openagentskill.com/skills/pyproj4-pyproj?ref=x

Install: npx skills add pyproj4/pyproj

Listing source

Community indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
pyproj4
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This community indexed listing is attributed to pyproj4 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

README badge

Add this badge to your GitHub README to show the listing, trust score, and install handoff.

[![OpenAgentSkill](https://www.openagentskill.com/api/badge/pyproj4-pyproj)](https://www.openagentskill.com/skills/pyproj4-pyproj)

Author

P

pyproj4

@pyproj4

Platform Fit

Health Signals

GitHub stars
1.2K
Quality score
63/100
Last GitHub push
Jun 15, 2026
Framework hints
2
OpenAgentSkill views
0
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

Review then install

88
  • GitHub adoption1.2K GitHub starsPASS
  • Stars/forks activity1.2K stars, 234 forks; issue activity unavailable in current metadataINFO
  • Recent maintenance17d since pushPASS
  • License clarityMITPASS
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskno major dependency risk hints in public metadataPASS