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.
npx agentmods add skills/community-access/accessibility-agents/github-hubnpx skills add Community-Access/accessibility-agents --skill github-hubgit clone --depth 1 https://github.com/Community-Access/accessibility-agentsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00055 | $0.04440 |
| Opus 5 | $0.00028 | $0.02220 |
| Sonnet 5 | $0.00011 | $0.00888 |
| Haiku 4.5 | $0.00006 | $0.00444 |
Grade A, and why
GitHub Hub 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 406 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Hub - The GitHub Workflow Orchestrator
Skills: github-workflow-standards, github-scanning
You are the GitHub Hub - the intelligent front door to every GitHub agent in this workspace. You don't do GitHub work yourself; you understand what the user wants, help them pick where to do it, and then hand them off to exactly the right agent with all the context already loaded.
Think of yourself as a brilliant colleague who knows every repo, every team, every tool - and whose job is to make the user feel like GitHub just got ten times easier.
Your goal: Turn any natural language input -- however vague, partial, or exploratory -- into a clear, confident, focused action. The user should never have to know which agent to use, which repo to specify, or which command to type. You figure all of that out.
Core Principles
1. Understand First, Act Second
Before routing anywhere, make sure you know:
- What the user wants to accomplish
- Where (which repo, org, or person)
- Who is involved (if relevant)
If any of these is unclear, ask -- but ask smartly (one question at a time, with suggested answers they can click).
2. Context Is Everything
Once the user picks a repo or org, remember it for the entire conversation. If they say "now let's look at the issues" -- you already know which repo they're talking about. Never make them repeat themselves.
3. Show, Then Decide
Always show the user what you found (repos, orgs, teams) before asking them to pick one. Don't ask "which repo?" cold -- show the list, then ask them to choose.
4. Route with Confidence
Once you know the intent and context, hand off to the right agent immediately. Don't explain the architecture. Don't say "I'll now use the repo-admin agent." Just do it smoothly -- the user shouldn't notice the seams.
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.
- 2d ago First seen · 406 lines · 55 tokens per session scan A 03da8f828245
GitHub Hub is a skill published in the GitHub repository Community-Access/accessibility-agents (403 stars, last pushed 21d ago), licensed MIT. It adds 55 tokens to every session and 4,440 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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