github-trending

github-trending is a skill for Claude Code, Codex from Day1Labs/OpenAva. It costs 39 tokens per session (579 once invoked), scanned A, original, MIT.

A research helper that collects popular GitHub repositories and related signals over a chosen time period, programming language, or topic.

In plain words
What is it for?
Use it to track rising projects, compare tools, review competitors, and support technology choices with evidence and stated risks.
Why use it?
It reduces the time spent finding active projects and judging whether interest in them reflects real growth, adoption, and project health.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to track rising projects, compare tools, review competitors, and support technology choices with evidence and stated risks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/day1labs/openava/github-trending
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Day1Labs/OpenAva --skill github-trending
Clone the repo
git clone --depth 1 https://github.com/Day1Labs/OpenAva

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for github-trending

README.md
[![agentmods](https://agentmods.dev/badge/skills/day1labs/openava/github-trending/github.svg)](https://agentmods.dev/skills/day1labs/openava/github-trending)
Your own site
<a href="https://agentmods.dev/skills/day1labs/openava/github-trending"><img src="https://agentmods.dev/badge/skills/day1labs/openava/github-trending/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for github-trending

Your own site · 80×15
<a href="https://agentmods.dev/skills/day1labs/openava/github-trending"><img src="https://agentmods.dev/badge/skills/day1labs/openava/github-trending.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 579 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.00579
Opus 5.5 $0.00016 $0.00232
Sonnet 5.5 $0.00008 $0.00116
Haiku 4.5 $0.00004 $0.00058

Measured 2mo ago against content hash 0d511b8d70ad, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

github-trending scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

OpenAva/Runtime/Agent/Skills/github-trending/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Core Capabilities

  • Fetch and organize trending repositories and developer signals from GitHub Trending.
  • Perform structured comparisons of projects and deliver conclusions suitable for learning, benchmarking, and technology selection.

Data Source Priority

  1. Primary: GitHub Trending
    • https://github.com/trending
    • https://github.com/trending/{language}
    • https://github.com/trending?since=daily|weekly|monthly
  2. Secondary: GitHub API
    • Used to supplement baseline metrics such as stars, activity, and creation date.
  3. Supplementary: Community Signals
    • Used for cross-validation only, never as a sole basis for conclusions.

Execution Flow

  1. Define scope: time window, language or domain, and goal (tracking, competitive scan, or technology selection).
  2. Fetch candidates: start with Trending, then supplement with verifiable metrics via the API.
  3. Structured evaluation: compare side by side across growth, health, and adoption dimensions.
  4. Deliver results: provide conclusions, evidence, risks, and recommended actions.

Evaluation Framework (Concise)

1) Growth Signals

  • Stars count and recent growth rate
  • Forks and contributors changes

2) Health Signals

  • Recent commit frequency
  • Issue and PR activity and response patterns
  • Documentation and license completeness

3) Adoption Signals

  • Clarity of the problem being solved
  • Onboarding cost and integration complexity
  • Competitive differentiation and cost of switching

Output Requirements

  • Lead with conclusions, then evidence. Avoid stacking metrics without insight.
  • Do not fabricate star growth, commit frequency, or community activity.
  • Mark missing data explicitly as unknown.
  • Label time-sensitive observations as "based on current fetch time".
  • When the user goal is technology selection or production adoption, always include risks and alternatives.

Default Output Template

# GitHub Trending Brief - {date}

## Conclusion
{One-sentence conclusion: the most valuable direction right now and why}

## Top 5 Trending Projects
| Project | Language | Key Metrics | Why Selected | Risk |
|---------|----------|-------------|--------------|------|
| {name} | {lang} | {stars / delta} | {reason} | {risk_or_unknown} |

## Technology Selection Recommendations (optional)
- Recommended: {project}, because {why}
- Alternative: {alternative}, suitable for {scenario}
- Watch out: {risk}

Read the full file on GitHub · 79 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 79 lines · 39 tokens per session scan A 0d511b8d70ad

Subscribe to this mod's changes

github-trending is a skill published in the GitHub repository Day1Labs/OpenAva (11 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 579 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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