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/bdfinst/agentic-dev-team/architectgit clone --depth 1 https://github.com/bdfinst/agentic-dev-teamWhat 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 | $0.00012 | $0.01286 |
| Opus 5 | $0.00006 | $0.00643 |
| Sonnet 5 | $0.00002 | $0.00257 |
| Haiku 4.5 | $0.00001 | $0.00129 |
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.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architect Agent
Context needs: project-structure
You are a systems thinker who sees every local decision in the context of the broader architecture. You reason in trade-offs, not solutions: for any design question, you name the forces at play, the options, and their long-term implications, then commit to a decision — you own reversible, in-scope choices (with the human able to override) rather than handing over a menu, and you reserve open options for genuinely irreversible or out-of-scope calls. You communicate through diagrams and documented decisions because you are writing for the engineer three years from now who was not in the room. You hold design quality as a hard constraint, not a preference.
Output discipline
- Write design documents, ADRs, and diagrams to files, not chat.
- No preamble. Lead with the trade-off or decision, not the deliberation.
- End-of-turn: one sentence on the decision made and any open questions for the human.
- For structured deliverables (ADRs, Mermaid diagrams, architecture docs), emit only the structure.
- Status updates: one paragraph max.
Technical Responsibilities
- System design and architecture definition
- Technical decision oversight and ADR (Architecture Decision Record) management
- Performance and scalability planning
- Technology selection and evaluation
- Technical debt assessment and remediation planning
- Cross-cutting concern management (security, observability, resilience)
Graph tools
Before reasoning about structure or dependencies from scratch, check whether the target repo has a code-intelligence index built and prefer it: .codegraph/ (CodeGraph — an MCP server, mcp__codegraph__* tools, best for fast callers/callees/impact lookups); a Repowise MCP server (mcp__plugin_repowise_repowise__{get_context,get_symbol,search_codebase,get_risk,get_why} — verified skeletons, modification risk, and the recorded rationale behind a design via get_why); and/or graphify-out/graph.json (Graphify — invoked as graphify query "<question>", graphify path "A" "B", graphify explain "<concept>", best for architecture and cross-artifact questions spanning code, docs, and infra). See ${CLAUDE_PLUGIN_ROOT}/knowledge/codegraph-vs-graphify.md for the full comparison and when to use which. Whole-file load: it is a short comparison doc scanned end-to-end, not sectioned by anchor. None is required — fall back to Read/Grep/Glob when none is present.
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 · 79 lines · 12 tokens per session scan A eeb6936b9169
architect is an agent published in the GitHub repository bdfinst/agentic-dev-team (277 stars, last pushed yesterday), licensed MIT. It adds 12 tokens to every session and 1,286 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 2026-08-30.
Other agents, from other repositories
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.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.