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/genai-jerry/claude-software-factoryWrote 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/genai-jerry/claude-software-factory/architect)<a href="https://agentmods.dev/commands/genai-jerry/claude-software-factory/architect"><img src="https://agentmods.dev/badge/commands/genai-jerry/claude-software-factory/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/commands/genai-jerry/claude-software-factory/architect"><img src="https://agentmods.dev/badge/commands/genai-jerry/claude-software-factory/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 | $0.00017 | $0.01071 |
| Opus 5 | $0.00009 | $0.00535 |
| Sonnet 5 | $0.00003 | $0.00214 |
| Haiku 4.5 | $0.00002 | $0.00107 |
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 4d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Architect of the Software Factory (see FACTORY.md).
Input: an epic issue number labelled factory:planned: $ARGUMENTS
Mission
Produce a grounded technical design for every affected repo.
Steps
-
Where
.github/factory-testing.jsonturns system tests on (FACTORY.md §4b), the Test Planner has already committedsystem-tests/test-plan.mdandtest-data.mdto the shared design branch. Read them before you design. They say what a human will exercise and what data they will need, and two things in your design answer to that: the seed path or fixtures the plan'sSetup:lines assume must exist, and the preview environment its Environment section names must be deployable. Neither is a reason to change the plan — it is black-box and derived from the approved spec — but a design that makes its cases unrunnable is a design finding. -
Resolve each affected repo's home branch for this epic (FACTORY.md §6/§6a): with
.github/factory-branches.jsonepics: trueit isfactory/epic-<issue-number>in every affected repo — cut it from that repo's default branch if it is not on the remote yet (a no-op if it is) and work there. You run before gate G2, so no task has been dispatched and nothing can be stranded off a branch cut now. Without the policy the home branch is that repo's integration branch (name: the profile'sbranches.stagingwhen it is a non-null string, else the policy'sstaging, else"staging").Find the change folder wherever it actually is: the first of the epic branch, the integration branch and the default branch that carries
openspec/changes/<issue-number>-*/. An epic whose documents merged to the default branch under an older routing still has them there, and reading only the policy's branch would hand you an empty checkout. Then read the change folder (proposal.md,specs/,tasks.md) and the ACTUAL code of every affected repo before deciding anything. -
Reuse first: search each repo for existing modules/patterns to extend. Name the files you will extend. Duplication is a design failure.
-
Write
design.mdin each affected repo's change folder (openspec/changes/<issue>-<slug>/design.md) covering:- API contracts: paths, request/response schemas, status codes, auth.
- Data: the migration plan, using the migration tool named in that repo's
.factory/profile.json. - Per repo: which existing modules to touch, following that repo's profile
conventions(.factory/profile.json) and its CLAUDE.md / AGENTS.md. - Failure modes and edge cases per spec scenario.
- Rollout order and rollback notes.
-
Cross-repo contract: one shared contract snippet, byte-identical in every repo's design.md. Flag any breaking change explicitly.
-
In the epic's repo: commit
design.mdto the existingfactory/<issue-number>-designbranch (the Planner opened its draft PR withtasks.md) and mark that PR ready for review. In each OTHER affected repo: createfactory/<issue-number>-designfrom that repo's home branch for this epic (step 1: itsfactory/epic-<issue-number>branch underepics: true— cut it from the repo's default branch first if it doesn't exist yet — else the branch you found its change folder on) and open one PR with that repo'sdesign.md, based on that same branch. Never base it on the default branch while an integration branch exists (§6). One design PR per repo, all approved at gate G2. On the epic: link the PR(s), removefactory:planned, applyfactory:design-ready, and cc thedesignapprovers from.github/factory-approvers.json— gate G2 is theirs. Where the change folder carriessystem-tests/, say in that comment how many test cases and data sets the PR also carries — the approver is approving the human test plan as well as the design, and gate G2 is the only review it gets.
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.
- 4d ago Changed · +27 lines fdb062dde59d
- 8d ago First seen · 50 lines · 17 tokens per session scan A bd2d9f21dbd4
architect is a command published in the GitHub repository genai-jerry/claude-software-factory (2 stars, last pushed 4d ago), licensed MIT. It adds 17 tokens to every session and 1,071 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 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.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.