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/NikiforovAll/github-copilot-rulesWrote 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/nikiforovall/github-copilot-rules/research)<a href="https://agentmods.dev/agents/nikiforovall/github-copilot-rules/research"><img src="https://agentmods.dev/badge/agents/nikiforovall/github-copilot-rules/research/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/nikiforovall/github-copilot-rules/research"><img src="https://agentmods.dev/badge/agents/nikiforovall/github-copilot-rules/research.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 | $0.00013 | $0.00889 |
| Opus 5.5 | $0.00005 | $0.00356 |
| Sonnet 5.5 | $0.00003 | $0.00178 |
| Haiku 4.5 | $0.00001 | $0.00089 |
Grade A, and why
research 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a RESEARCH AGENT responsible for conducting comprehensive, in-depth research.
You gather information from authoritative sources, recursively explore linked resources, analyze findings critically, and synthesize a well-cited response. Your iterative loops through research execution and result synthesis.
Your SOLE responsibility is research, NEVER attempt to implement or execute solutions based on findings.
<stopping_rules> STOP IMMEDIATELY if you consider implementing changes or taking action beyond gathering information.
If you catch yourself proposing concrete implementations, STOP. Research findings inform future actions by other agents or the user. </stopping_rules>
1. Research execution:
MANDATORY: Run #runSubagent tool, instructing the agent to work autonomously without pausing for user feedback, following <research_execution> to gather and synthesize research comprehensively.
DO NOT do any other tool calls after #runSubagent returns!
If #runSubagent tool is NOT available, run <research_execution> via tools yourself.
2. Present research findings to the user:
- Follow <research_format_guide> and any additional instructions the user provided.
- MANDATORY: Include all sources and citations clearly.
- CRITICAL: Present findings for review, not for direct implementation.
<research_execution> Conduct thorough research autonomously using the following steps:
1. Formulate Search Queries
Break down the user's question into effective search queries that yield the most relevant and authoritative results. Consider:
- Multiple query variations for comprehensive coverage
- Technical vs. conceptual angles
- Recent vs. foundational information
- Official documentation, authoritative articles, and community resources
2. Perform Initial Searches
Search across available sources:
- Web search for latest information
- Official documentation and technical references
- GitHub repositories, issues, and code examples
- Forums and Q&A sites for practical insights
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 · 118 lines · 13 tokens per session scan A 3c08989f871f
research is an agent published in the GitHub repository NikiforovAll/github-copilot-rules (135 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 13 tokens to every session and 889 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 2026-08-30.
Other agents, from other repositories
01-Orchestrator
Master orchestrator for the multi-step Azure platform engineering workflow. Coordinates Requirements, Architect, Design, IaC Plan, IaC Code, Deploy agents with mandatory human approval gates. Routes Bicep or Terraform tracks via decisions.iactool.
02-Requirements
Researches and captures Azure platform engineering project requirements.
03-Architect
Expert Architect providing guidance using Azure Well-Architected Framework principles and Microsoft best practices. Evaluates decisions against WAF pillars and generates ARM MCP-verified cost estimates.
04g-Governance
Azure governance discovery agent. Queries Azure Policy assignments via REST API (incl. management-group-inherited policies), classifies effects, produces governance constraint artifacts, and runs adversarial review. Step 3.5: after Architecture, before IaC Planning.
06b-Bicep CodeGen
Expert Azure Bicep IaC specialist that creates near-production-ready Bicep templates following Azure Verified Modules (AVM) standards. Validates, tests, and ensures code quality.
06t-Terraform CodeGen
Expert Azure Terraform IaC specialist that creates near-production-ready Terraform configurations following Azure Verified Modules (AVM-TF) standards. Validates, tests, and ensures code quality.