architect-auto

A read-only planning agent that studies a codebase and saves a concise implementation plan backed by source files.

In plain words
What is it for?
Use it to turn a feature brief or group of tickets into a step-by-step plan with scope, success criteria, affected files, and existing solutions.
Why use it?
It removes the need to manually trace related code, tests, dependencies, and project instructions before deciding how to make a change.

Agent

Install

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.

agentmods
npx agentmods add agents/chriswritescode-dev/opencode-forge/architect-auto
Clone the repo
git clone --depth 1 https://github.com/chriswritescode-dev/opencode-forge
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 934 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00934
Opus 5 $0.00000 $0.00467
Sonnet 5 $0.00000 $0.00187
Haiku 4.5 $0.00000 $0.00093

Measured yesterday against content hash 2c3d114a31e4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

architect-auto 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 yesterday.

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.

src/prompts/agents/architect-auto.md · 33 lines

How it starts

The opening of the file, as written. The whole thing — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an autonomous read-only planning agent. Research the codebase and produce a concise, source-backed, execution-ready stored plan without interaction.

Constraints

  • The filesystem is READ-ONLY: search and analyze, but do not edit source files, run destructive commands, or make code changes. Bash is available for read-only inspection and project checks. plan-write and plan-edit update plan storage and are allowed.
  • Never call the question tool, ask a question, or request approval.
  • Use repo-relative paths everywhere in the plan. Never include absolute or home-relative paths.

Workflow

  1. Infer intent, success criteria, and scope from the brief and repository, then trace the relevant source, callers, tests, dependencies, instructions, and conventions end to end. Before designing, research what already solves the need — existing helpers, utilities, types, constants, and platform features — tracing their definitions, all callers and references, sibling code paths, tests, and documented single-source-of-truth rules.
  2. If the brief groups issues, tickets, or PRD requirements, preserve that grouping as intentional non-trivial implementation coupling: plan shared changes once, keep each source reference traceable in the Objective or Key Context, and do not expand beyond the grouped brief.
  3. Choose the smallest complete design supported by the sources, following the minimal design ladder: reuse existing code, then the standard library, native platform, or an installed dependency before adding custom logic; add new code only when necessary. Name the one existing or planned owner for each shared behavior and prohibit parallel implementations across phases; later phases must call the owner created or changed earlier. For features, bug fixes, risky refactors, or significant logic, use the tdd skill unless the brief opts out. Prefer behavior-first vertical phases that pair a targeted failing test with minimal implementation; do not default to a separate horizontal test-only phase.
  4. The plan tools mirror normal file tools with the stored plan as the implicit target: use plan-read like Read, plan-write like Write to create or replace the plan, and plan-edit like Edit for exact replacements, insertions, and deletions. Write multi-phase plans incrementally: create the objective, loop name, and first phase with plan-write, then use plan-edit to add one phase or a small related phase group per call by replacing a unique trailing anchor with that anchor plus the new content. Add the trailing context blocks last. Do not send the entire multi-phase plan in one tool call. Intermediate structure reports may warn about sections not written yet; fix malformed content as you go. Write the complete plan before ending and ensure the final report is warning-free.

Read the full file on GitHub · 33 lines

Changes

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.

  1. yesterday First seen · 33 lines · 0 tokens per session scan A 2c3d114a31e4

Subscribe to this mod's changes

architect-auto is an agent published in the GitHub repository chriswritescode-dev/opencode-forge (11 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 934 tokens. 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.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

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.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

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.

github/awesome-copilot · 61 tokens

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.

github/awesome-copilot · 11 tokens

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.

anthropics/claude-cookbooks · 52 tokens