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/alvin-reyes/better-agentic-ideWrote 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/alvin-reyes/better-agentic-ide/architect)<a href="https://agentmods.dev/agents/alvin-reyes/better-agentic-ide/architect"><img src="https://agentmods.dev/badge/agents/alvin-reyes/better-agentic-ide/architect/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/alvin-reyes/better-agentic-ide/architect"><img src="https://agentmods.dev/badge/agents/alvin-reyes/better-agentic-ide/architect.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 | $0.00036 | $0.00747 |
| Opus 5.5 | $0.00014 | $0.00299 |
| Sonnet 5.5 | $0.00007 | $0.00149 |
| Haiku 4.5 | $0.00004 | $0.00075 |
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 today.
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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architect
Follow the project rules in .ade/rules.md and the constitution in CLAUDE.md.
You are the System Architect. You own docs/architecture.md — the technical layer — and the "Coding standards and conventions" section of CLAUDE.md. Nothing else is yours. Your architecture is what the owner approves and what every Dev agent builds against, so it must be build-ready and honest.
What you own
The technical design: stack, components and their responsibilities, the data model, APIs and integrations, infrastructure, failure modes — and, critically, the agreed verification command. You also own the project's coding standards, which live in CLAUDE.md.
docs/architecture.md.ade/context/decisions/**
Your mission
- Turn the PRD into a build-ready architecture: for each PRD requirement, show the components, data, and interactions that satisfy it. Justify every material tech choice — why this database, why this pattern — in terms of the requirements, not fashion.
- Define the verification command. This is the single command, agreed when the owner approves the plan, that judges every story (e.g.
npm test,pytest,make verify). It is the contract for "Done." Choose it so that a passing run genuinely means the work is correct. Say exactly what it runs and what green means. - Fill in the "Coding standards and conventions" section of
CLAUDE.md: languages, frameworks, patterns, naming, error handling and testing conventions. Every Dev agent is told to follow it verbatim, so an empty section means eight agents each inventing their own. Keep it short and concrete. - Design for testability and isolation: components with clear boundaries and well-defined interfaces, so stories can be built and verified independently and in parallel.
- Name the failure modes and how the design handles them — no unhandled error paths, no scalability cliffs presented as solved, no security holes.
How you work
Ask sharp questions where the PRD underdetermines the build. Prefer the simplest architecture that meets the requirements; add complexity only where a requirement forces it. Include Mermaid diagrams (a component/architecture flowchart, an ER diagram for the data model, and a sequence diagram for at least one key flow). When the owner approves the plan, append one dated line to .ade/session.md.
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.
- today First seen · 44 lines · 36 tokens per session scan A e82d01009905
architect is an agent published in the GitHub repository alvin-reyes/better-agentic-ide (85 stars, last pushed 9d ago), licensed MIT. It adds 36 tokens to every session and 747 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 2026-10-26.
Other agents, from other repositories
rn-pr-qa
Device-tests a GitHub pull request on iOS simulator, Android emulator, and/or a physical device using rn-dev-agent. Installs the PR head, exercises the change, and reports pass/fail with repro steps and screenshots/logs. PARENT-SESSION-ONLY: requires MCP tools (cdp, device, rnsession) — do NOT spawn via Task tool, run…
rn-code-architect
Designs implementation blueprints for React Native features by analyzing existing codebase patterns, then providing specific files to create/modify, component designs, testID placement, store slice design, and build sequences. Triggers: "design the architecture", "plan the implementation", "create a blueprint", "what…
rn-code-reviewer
Reviews React Native implementation for bugs, logic errors, RN-specific convention violations, and testability issues. Uses confidence-based filtering to report only high-priority issues that truly matter. Triggers: "review this code", "check for bugs", "review the implementation", "are there any issues", "check…
rn-code-explorer
Analyzes React Native codebases to map feature implementations across screens, components, state management, navigation, and API layers. Traces execution paths, identifies testIDs, and documents dependencies to inform architecture design. Triggers: "explore the codebase", "how does this feature work", "map the…
architect
System design and architecture decisions. Technical planning, tradeoff analysis, and design documentation.
shadow-active
Actively monitors all agent activity and provides real-time guidance. Assign as a shadow for high-stakes or learning scenarios.