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 commands/ayoubben18/ab-method/update-architecturegit clone --depth 1 https://github.com/ayoubben18/ab-methodWhat 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 | $0.00000 | $0.00394 |
| Opus 5 | $0.00000 | $0.00197 |
| Sonnet 5 | $0.00000 | $0.00079 |
| Haiku 4.5 | $0.00000 | $0.00039 |
Grade A, and why
update-architecture 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 3d 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.
What it actually says
Update Architecture
Description
Update and maintain architecture documentation to keep technical documentation current with project changes.
Usage
/update-architecture
Behavior
Loads and executes the update-architecture workflow from .ab-method/core/update-architecture.md
This workflow will:
- Identify what shipped (from the latest
progress-tracker.mdsummaries,git diff, or user description) - Refresh the architecture docs that the change touches:
- APIs/endpoints in
tech-stack.md(Entry Points) — checked every run, even if the user didn't mention APIs - Patterns in
frontend-patterns.md/backend-patterns.md - Stack / external services / constraints / testing in
tech-stack.md - Domain terms in
UBIQUITOUS_LANGUAGE.md/CONTEXT.md
- APIs/endpoints in
- Invoke the
improve-codebase-architectureskill scoped to the changed files — surfaces deepening opportunities the change just created or revealed, drops into a grilling loop on the candidate the user picks - Defer hard-to-reverse / domain-reshape decisions to
/domain-model(which captures ADRs properly)
Workflow Details
- Always checks APIs — Entry Points drift is the most common stale-doc issue
- Always runs
improve-codebase-architecturescoped to the change — docs catch the what; the skill catches the architectural debt the change just introduced - Incremental — adds new content; deprecates with
[DEPRECATED <date>]instead of deleting
Examples
/update-architecture
# Reviews and updates architecture documentation
# Ensures technical docs reflect current project state
# Maintains consistency for accurate task planning
Alternative Usage
You can also use the traditional AB Method master controller:
/ab-master update-architecture
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.
- 3d ago First seen · 41 lines · 0 tokens per session scan A 32698592cc4f
update-architecture is a command published in the GitHub repository ayoubben18/ab-method (187 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 394 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.
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clarify
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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.
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.