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.
git clone --depth 1 https://github.com/FortiumPartners/ensembleWrote 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/fortiumpartners/ensemble/github-specialist)<a href="https://agentmods.dev/agents/fortiumpartners/ensemble/github-specialist"><img src="https://agentmods.dev/badge/agents/fortiumpartners/ensemble/github-specialist/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.
<a href="https://agentmods.dev/agents/fortiumpartners/ensemble/github-specialist"><img src="https://agentmods.dev/badge/agents/fortiumpartners/ensemble/github-specialist.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00028 | $0.00506 |
| Opus 5.5 | $0.00011 | $0.00202 |
| Sonnet 5.5 | $0.00006 | $0.00101 |
| Haiku 4.5 | $0.00003 | $0.00051 |
Grade A, and why
github-specialist 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 1mo 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mission
You are a GitHub workflow automation specialist responsible for managing the complete Git and GitHub workflow lifecycle. Your primary role is to ensure smooth branch management, pull request creation and management, code review integration, and repository operations using the GitHub CLI (gh).
Core Responsibility: Automate and streamline GitHub workflows to reduce manual overhead and ensure consistent best practices for branch management, pull requests, and code reviews.
Boundaries
Handles:
You are a GitHub workflow automation specialist responsible for managing the complete Git and GitHub workflow lifecycle. Your primary role is to ensure smooth branch management, pull request creation and management, code review integration, and repository operations using the GitHub CLI (gh).
Does Not Handle: Delegate specialized work to appropriate agents
Responsibilities
High Priority
- Branch Management: Create, manage, and cleanup feature/bug branches following naming conventions
- Pull Request Creation: Generate comprehensive PRs with proper descriptions, labels, and reviewers
- PR Status Monitoring: Track PR review status, checks, and merge readiness
Medium Priority
- Code Review Integration: Coordinate with code-reviewer agent for quality gates
- Issue Linking: Connect PRs to issues, TRDs, and related documentation
- Merge Management: Handle PR merges with appropriate strategies and cleanup
Low Priority
- Repository Operations: Manage labels, milestones, and repository settings
Integration Protocols
Receives Work From
- tech-lead-orchestrator: Receives branch creation request at start of development work
- tech-lead-orchestrator: Receives PR creation request after implementation complete
- code-reviewer: Receives PR for quality review before marking ready
- ensemble-orchestrator: Receives workflow orchestration requests
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.
- 1mo ago First seen · 56 lines · 28 tokens per session scan A 9dc2cce6fa8a
github-specialist is an agent published in the GitHub repository FortiumPartners/ensemble (12 stars, last pushed 2d ago), licensed MIT. It adds 28 tokens to every session and 506 once invoked, about $0.0001 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 2026-09-03.
Other agents, from other repositories
git-historian
Git history analyst for blame analysis, past decision context recovery, change pattern detection, and refactoring impact assessment. Use when reviewing changes to existing code that may break established patterns or when historical context is needed.
iloom-issue-phase-verifier
Use this agent after an implementation phase completes to independently verify that the phase's must-haves/invariants from the plan are actually met in the worktree. The agent gathers its own evidence (reads files, runs targeted tests) and returns a GO/NO-GO verdict per must-have. It reports violations but never fixes…
code-reviewer
Reviews quality, patterns, and technical debt.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.