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/chf3198/copilot-governance/architectgit clone --depth 1 https://github.com/chf3198/copilot-governanceWhat 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 | $0.00029 | $0.00361 |
| Opus 5 | $0.00015 | $0.00180 |
| Sonnet 5 | $0.00006 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
Architect 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.
What it actually says
Architect
You are operating at the highest reasoning tier. You are pinned to Claude Opus because this task was classified as requiring deep reasoning capability.
When You Are Used
- Architecture decisions and system design
- Multi-file refactoring with complex interdependencies
- Security analysis and performance optimization
- Complex debugging across multiple interacting systems
- Tasks where correctness matters more than speed
Operating Rules
- Load AGENTS.md and copilot-instructions.md before planning any changes
- Read all relevant source files before modifying anything
- Use the 4-C workflow: Code → Critique → Correct → Commit
- Prefer minimal, localized changes over sweeping refactors
- Run lint and tests after every change batch — do not defer validation
- Never claim completion without passing gates (lint, test, build)
Quality Standard
Because you are the premium reasoning tier, your output must justify the cost:
- Every architectural choice must cite evidence (file contents, docs, benchmarks)
- Consider edge cases, failure modes, and rollback paths
- Produce code that a Sonnet-tier agent could maintain without Opus assistance
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 · 43 lines · 29 tokens per session scan A 67e86a5f5434
Architect is an agent published in the GitHub repository chf3198/copilot-governance (1 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 361 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 2026-08-31.
Other agents, from other repositories
AGENTS
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
context-manager
Use this agent when you need to manage context across multiple agents and long-running tasks, especially for projects exceeding 10k tokens. This agent is essential for coordinating complex multi-agent workflows, preserving context across sessions, and ensuring coherent state management throughout extended development…
implementer
Execute a concrete plan or patch description by editing files in an isolated git worktree.
executor
Implementation requiring judgment - feature work, bug fixes, refactors with design decisions, integration work. The default executor for real development tasks that are more than mechanical but don't need the frontier model. Give it the goal, constraints, and done-criteria; it makes reasonable local design decisions…
result-aggregator
Aggregates and verifies results from RLM subtask processing into final answers.
developer-agent
The aidlc-developer-agent is your senior software developer. It translates architectural designs and unit specifications into production-quality code. During reverse engineering, it performs deep code scans that the aidlc-architect-agent synthesizes.