Awesome-omni-skills oss-hunter

OSS Hunter \ud83c\udfaf workflow skill. Use this skill when the user needs Automatically hunt for high-impact OSS contribution opportunities in trending repositories and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

install

source · Clone the upstream repo

git clone https://github.com/diegosouzapw/awesome-omni-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/oss-hunter" ~/.claude/skills/diegosouzapw-awesome-omni-skills-oss-hunter && rm -rf "$T"

manifest: skills/oss-hunter/SKILL.md

OSS Hunter 🎯

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/oss-hunter

from

https://github.com/sickn33/antigravity-awesome-skills

into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

plus

ORIGIN.md

as the provenance anchor for review.

OSS Hunter 🎯 A precision skill for agents to find, analyze, and strategize for high-impact Open Source contributions. This skill helps you become a top-tier contributor by identifying the most "mergeable" and influential issues in trending repositories.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

Use when the user asks to find open source issues to work on.
Use when searching for "help wanted" or "good first issue" tasks in specific domains like AI or Web3.
Use to generate a "Contribution Dossier" with ready-to-execute strategies for trending projects.
Use when the request clearly matches the imported source intent: Automatically hunt for high-impact OSS contribution opportunities in trending repositories.
Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
Use when provenance needs to stay visible in the answer, PR, or review packet.

Operating Table

Situation	Start here	Why it matters
First-time use	`metadata.json`	Confirms repository, branch, commit, and imported path before touching the copied workflow
Provenance review	`ORIGIN.md`	Gives reviewers a plain-language audit trail for the imported source
Workflow execution	`bin/hunter.py`	Starts with the smallest copied file that materially changes execution
Supporting context	`bin/hunter.py`	Adds the next most relevant copied source file without loading the entire package
Handoff decision	`## Related Skills`	Helps the operator switch to a stronger native skill when the task drifts

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

Stars > 1000
Recent activity (pushed within 24 hours)
Relevant topics (AI, Agentic, Web3, Tooling)
help-wanted
good-first-issue
bug
v1 / roadmap

Imported Workflow Notes

Imported: Workflow

When hunting for contributions, the agent follows this multi-stage protocol:

Phase 1: Repository Discovery

Use

web_search

gh api

to find trending repositories. Focus on:

Stars > 1000
Recent activity (pushed within 24 hours)
Relevant topics (AI, Agentic, Web3, Tooling)

Phase 2: Issue Extraction

Search for specific labels:

```
help-wanted
```
```
good-first-issue
```
```
bug
```
```
v1
```
/
```
roadmap
```

gh issue list --repo owner/repo --label "help wanted" --limit 10

Phase 3: Feasibility Analysis

Analyze the issue:

Reproducibility: Is there a code snippet to reproduce the bug?
Impact: How many users does this affect?
Mergeability: Check recent PR history. Does the maintainer merge community PRs quickly?
Complexity: Can this be solved by an agent with the current tools?

Phase 4: The Dossier

Generate a structured report for the human:

Project Name & Stars
Issue Link & Description
Root Cause Analysis (based on code inspection)
Proposed Fix Strategy
Confidence Score (1-10)

Imported: Limitations

Accuracy depends on the availability of
```
gh
```
CLI or
```
web_search
```
tools.
Analysis is limited by context window when reading very large repositories.
Cannot guarantee PR acceptance (maintainer discretion).

Examples

Example 1: Ask for the upstream workflow directly

Use @oss-hunter to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @oss-hunter against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @oss-hunter for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @oss-hunter using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Quick Start

Ask your agent:

"Find me some help-wanted issues in trending AI repositories."
"Hunt for bug fixes in langchain-ai/langchain that are suitable for a quick PR."
"Generate a contribution dossier for the most recent trending projects on GitHub."

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
Treat generated examples as scaffolding; adapt them to the concrete task before execution.
Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/oss-hunter

, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open

metadata.json

ORIGIN.md

, and the most relevant copied upstream files. Load only the files that materially change the answer, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

```
@00-andruia-consultant-v2
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.
```
@10-andruia-skill-smith-v2
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.
```
@20-andruia-niche-intelligence-v2
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.
```
@2d-games
```
- Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Resource family	What it gives the reviewer	Example path
`references`	copied reference notes, guides, or background material from upstream	`references/n/a`
`examples`	worked examples or reusable prompts copied from upstream	`examples/n/a`
`scripts`	upstream helper scripts that change execution or validation	`scripts/n/a`
`agents`	routing or delegation notes that are genuinely part of the imported package	`agents/n/a`
`assets`	supporting assets or schemas copied from the source package	`assets/n/a`

hunter.py

Imported Reference Notes

Imported: Contributing to the Matrix

Build a better hunter by adding new heuristics to Phase 3. Submit your improvements to the ClawForge.