# pstack (ChatGPT Plugin) > Engineering agent workflows - Type: plugin - Publisher: FetchUpstream - Categories: Development, AI & ML - Website: https://chatgpt.com/plugins/plugins_6a85a87df50c8191bd7f010bb7b17794 - Open in ChatGPT: https://chatgpt.com/plugins/plugins_6a85a87df50c8191bd7f010bb7b17794 - Version: 0.2.0 - Listed: 2026-10-15 ## About An unofficial ChatGPT port of pstack, providing rigorous reusable workflows for engineering, reasoning, review, and writing. ## Install 1. **Add it in ChatGPT** Open Plugins in the ChatGPT sidebar (web or desktop), search for “pstack” and select +. You'll be asked to sign in to any connected service on first use. Then type @ in a chat to call it. ## Skills - **architect**: Design types, interfaces, module boundaries, data flow, and ownership before implementation. Use for 'architect this', 'design this', API or domain modeling, refactors, new subsystems, or non-trivial changes where choosing the wrong shape would make the implementation harder. - **blast-radius**: Find what a code change could break outside the diff by tracing callers, contracts, shared data, external integrations, lifecycle behavior, and downstream consumers. Use for 'blast radius of X', 'what could this break', risky PR reviews, regression analysis, and checking whether a small change is actually isolated. - **bro**: Restate the last message in plain human language, with no jargon. - **how**: Explain how a codebase, subsystem, feature, API, or technical artifact works by inspecting the available source. Use for 'how does X work', code walkthroughs, runtime flows, architecture questions, ownership questions, and 'where should this live'. - **principle-boundary-discipline**: Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions. - **principle-build-the-lever**: Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun. - **principle-encode-lessons-in-structure**: Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text. - **principle-exhaust-the-design-space**: Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing. - **principle-experience-first**: Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones. - **principle-fix-root-causes**: Apply when debugging. Trace each symptom to its root cause and fix it there; reproduce first, ask why until you reach it, resist nil-check guards that silence crashes. - **principle-foundational-thinking**: Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious. - **principle-make-operations-idempotent**: Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs. - **principle-migrate-callers-then-delete-legacy-apis**: Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers. - **principle-minimize-reader-load**: Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope. - **principle-model-the-domain**: Apply when writing stateful logic, or when code branches a lot or repeats a shape assumption across files. Encode the domain in a structure instead of scattered conditionals. ## Example prompts - "Explain how this subsystem works. Trace the code flow and flag the parts most likely to confuse developers." - "Review this PR for blast radius. Find what could break outside the diff and what still needs verification." - "Rewrite this to sound human. Keep the meaning and tone, but remove AI tells, filler, and generic phrasing." ## Related - [Superpowers](https://chatgptplugins.directory/plugins/superpowers.md): Plan, develop, and debug code - [Codex Security](https://chatgptplugins.directory/plugins/codex-security.md): Security scanning for your codebase - [Build Web Apps](https://chatgptplugins.directory/plugins/build-web-apps.md): Build frontend-focused web apps with generated assets, browser testing, payments, and... - [GitHub](https://chatgptplugins.directory/plugins/github.md): Triage PRs, issues, CI, and publish flows - [Figma](https://chatgptplugins.directory/plugins/figma.md): Figma design-to-code workflows - [Shopify](https://chatgptplugins.directory/plugins/shopify.md): Build and manage your store --- Source: https://chatgptplugins.directory/plugins/pstack · Index: https://chatgptplugins.directory/llms.txt · Independent and community-run. Not affiliated with or endorsed by OpenAI. ChatGPT is a trademark of OpenAI.