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 skills/backnotprop/pstack/architectnpx skills add backnotprop/pstack --skill architectgit clone --depth 1 https://github.com/backnotprop/pstackWhat 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 | $0.00052 | $0.01233 |
| Opus 5 | $0.00026 | $0.00616 |
| Sonnet 5 | $0.00010 | $0.00247 |
| Haiku 4.5 | $0.00005 | $0.00123 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architect
Design before implementing. Sketch types, function signatures, class shapes, and module boundaries with not implemented bodies and pseudocode. Synthesize across multiple model perspectives, then fill in code against the chosen sketch. If implementation proves the sketch wrong, throw it out and redesign.
Start
Open a todolist with one entry per phase before starting. Autonomous mode without checkpoints needs the list to show phase position and keep phases from silently disappearing.
- Ground
- Sketch
- Agree
- Implement
- Scrap
Phase A: Ground the problem
Build a real mental model of every system the new code touches. Run the how skill over the relevant subsystems. Critique mode if existing structure is the constraint or the design must push back on it.
Naming a file isn't grounding. Produce the traced model how prescribes. If the design redefines ownership or layering, also run the why skill on the existing shape so the rationale becomes a constraint, not a guess.
Skip Phase A only when the work is genuinely greenfield with no surrounding system to integrate.
Phase B: Sketch
Run the arena skill with the design-sketch task and the Phase A grounding artifacts. Pass references/runner-prompt.md as each runner's prompt. Each candidate produces a design package shaped per references/rationale-template.md: the caller's usage written first, then the type sketch, function signatures, module map, and prose rationale derived from it.
Use your configured architect runners (defaults claude-fable-5-thinking-max, gpt-5.6-sol-max, grok-4.6-fast-xhigh, claude-opus-5-thinking-xhigh).
Design it twice. Require at least two structurally distinct candidates before synthesis, even when the first looks sufficient. This is the exhaust-the-design-space principle skill made concrete. Whole-shape alternatives, not point fixes inside one shape.
Screen every candidate against references/design-red-flags.md before synthesis. Reject or revise shallow modules, information leakage, temporal decomposition, and pass-through methods.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 84 lines · 52 tokens per session scan A 585d7a9e03c0
architect is a skill published in the GitHub repository backnotprop/pstack (165 stars, last pushed 12d ago), licensed MIT. It adds 52 tokens to every session and 1,233 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…