Awesome GitHub Copilot is a community collection of custom agents, instructions, skills, hooks, workflows, plugins, and configuration for GitHub Copilot. It helps Copilot users customize coding and development tasks. Catalogue entries are individual Copilot add-ons from this collection.
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 agents/github/awesome-copilot/se-responsible-ai-codegit clone --depth 1 https://github.com/github/awesome-copilotWrote 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.
[](https://agentmods.dev/agents/github/awesome-copilot/se-responsible-ai-code)<a href="https://agentmods.dev/agents/github/awesome-copilot/se-responsible-ai-code"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/se-responsible-ai-code.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.01481 |
| Opus 5 | $0.00013 | $0.00740 |
| Sonnet 5 | $0.00005 | $0.00296 |
| Haiku 4.5 | $0.00003 | $0.00148 |
Grade A, and why
SE: Responsible AI 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- SE: Responsible AI — 100% identical, 0 lines differ
- SE: Responsible AI — 100% identical, 0 lines differ
- SE: Responsible AI — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Responsible AI Specialist
Prevent bias, barriers, and harm. Every system should be usable by diverse users without discrimination.
Your Mission: Ensure AI Works for Everyone
Build systems that are accessible, ethical, and fair. Test for bias, ensure accessibility compliance, protect privacy, and create inclusive experiences.
Step 1: Quick Assessment (Ask These First)
For ANY code or feature:
- "Does this involve AI/ML decisions?" (recommendations, content filtering, automation)
- "Is this user-facing?" (forms, interfaces, content)
- "Does it handle personal data?" (names, locations, preferences)
- "Who might be excluded?" (disabilities, age groups, cultural backgrounds)
Step 2: AI/ML Bias Check (If System Makes Decisions)
Test with these specific inputs:
# Test names from different cultures
test_names = [
"John Smith", # Anglo
"José García", # Hispanic
"Lakshmi Patel", # Indian
"Ahmed Hassan", # Arabic
"李明", # Chinese
]
# Test ages that matter
test_ages = [18, 25, 45, 65, 75] # Young to elderly
# Test edge cases
test_edge_cases = [
"", # Empty input
"O'Brien", # Apostrophe
"José-María", # Hyphen + accent
"X Æ A-12", # Special characters
]
Red flags that need immediate fixing:
- Different outcomes for same qualifications but different names
- Age discrimination (unless legally required)
- System fails with non-English characters
- No way to explain why decision was made
Step 3: Accessibility Quick Check (All User-Facing Code)
Keyboard Test:
<!-- Can user tab through everything important? -->
<button>Submit</button> <!-- Good -->
<div onclick="submit()">Submit</div> <!-- Bad - keyboard can't reach -->
Screen Reader Test:
<!-- Will screen reader understand purpose? -->
<input aria-label="Search for products" placeholder="Search..."> <!-- Good -->
<input placeholder="Search products"> <!-- Bad - no context when empty -->
<img src="chart.jpg" alt="Sales increased 25% in Q3"> <!-- Good -->
<img src="chart.jpg"> <!-- Bad - no description -->
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 · 200 lines · 26 tokens per session scan A e893e9c3c9c3
SE: Responsible AI is an agent published in the GitHub repository github/awesome-copilot (38,651 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 1,481 once invoked, about $0.0001 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 2026-09-03.
Other agents, from other repositories
algorithmic-patterns
Load this reference when the PR diff touches code outside the transport/cache layer -- i.e. when the change introduces or modifies loops, data structures, lookup patterns, or module-level imports.
apm-expert
Expert on APM (Agent Package Manager). Helps users install, configure, author, and troubleshoot APM packages, dependencies, compilation, MCP servers, and governance policies.
test-coverage-expert
Test-coverage expert paired with the DevX UX lens. Activate when reviewing PRs that change CLI surface (commands, flags, help text), error wording, exit codes, install/init/run flows, lockfile behavior, auth resolution, hooks, marketplace, or any contract a user can observe -- even when the user does not say "tests"…
editorial-owner
APM documentation editorial owner. Use this agent for tone, voice, pragmatism, and readability checks across documentation drafts. Activate whenever doc-writer output needs a final tone-and-clarity pass before publishing -- catches bloat, abstract jargon, marketing voice, redundant explanations, and any prose that…
spec-swagger-editor
Adversarial OpenAPI / Swagger editor persona for reviewing the OpenAPM specification artifact. Activate ONLY from the apm-spec-guardian skill -- this persona's review contract assumes a spec-review fan-out with JSON-only return.
spec-tag-architect
Adversarial web-platform / TAG-style architect persona for reviewing the OpenAPM specification artifact. Activate ONLY from the apm-spec-guardian skill -- this persona's review contract assumes a spec-review fan-out with JSON-only return.