Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/commands/phuoctrung-ppt/ai-sdlc-workflow/architecture-plan)<a href="https://agentmods.dev/commands/phuoctrung-ppt/ai-sdlc-workflow/architecture-plan"><img src="https://agentmods.dev/badge/commands/phuoctrung-ppt/ai-sdlc-workflow/architecture-plan.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 | $0.00077 | $0.01764 |
| Opus 5 | $0.00039 | $0.00882 |
| Sonnet 5 | $0.00015 | $0.00353 |
| Haiku 4.5 | $0.00008 | $0.00176 |
Grade A, and why
architecture-plan 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 5d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Act as Orchestrator driving @architect-planner (.cursor/agents/architect-planner.md) and @judge-agent (.cursor/agents/judge-agent.md). Stay inside the current .cursor workflow (AGENTS.md, protected-paths, worker-scopes, skills, hooks).
Mode selection
- GENESIS — invoked as
/architecture-plan brainstorming {idea}(an idea/argument is present). Produces: standardized domain (AGENTS.md),docs/architecture.md, ADR(s), and a system roadmap plan. - BREAKDOWN — invoked as
/architecture-plan(no idea; an active plan already exists). Expands the roadmap into concrete, executable per-module tasks.
If an idea is present → run GENESIS. Otherwise → run BREAKDOWN against docs/plans/.active-plan.
GENESIS mode — /architecture-plan brainstorming {idea}
Input: {idea}
Step 0 — Build context
python3 .cursor/context/context-builder.py --phase brainstorm --task "{idea}" --agent architect-planner
python3 .cursor/context/context-builder.py --phase plan --task "{idea}" --agent architect-planner
Obey Context Packet tiers. For lower-capability models, expand-ref:
python3 .cursor/context/context-builder.py --expand-ref ".cursor/skills/planning/references/planning-with-lower-models.md" --reason "compact plan quality gate"
Step 1 — BRAINSTORM (HARD-GATE, chat only)
Package the idea into a concept brief (in chat):
- What it does — one paragraph; the core job-to-be-done.
- Target users / personas.
- Core features — split MVP vs Later. This list is the feature contract the judge checks against.
- Design/UX needs — key screens/flows, tone (delegate detail to
@designer-workerlater). - Domain & data — the domain, core entities, tenancy model (none / soft / hard).
- Constraints — compliance, scale, budget, integrations.
- 2–3 architecture approaches with trade-offs + a recommendation.
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.
- 5d ago First seen · 122 lines · 77 tokens per session scan A 0c38338c0cae
architecture-plan is a command published in the GitHub repository phuoctrung-ppt/ai-sdlc-workflow (2 stars, last pushed 20d ago), licensed MIT. It adds 77 tokens to every session and 1,764 once invoked, about $0.0004 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.