agent-tty

Terminal and TUI automation CLI for AI agents. Use when the user needs to create a terminal session, run a command in a terminal, automate an interactive CLI or TUI, wait for terminal output, capture a TUI screenshot, export a terminal recording, or test a CLI workflow with reviewable artifacts.

Terminal and TUI automation CLI for AI agents. Use when the user needs to create a terminal session, run a command in a terminal, automate an interactive CLI or TUI, wait for terminal output, capture a TUI screenshot, export a terminal recording, or test a CLI workflow with reviewable artifacts.

Terminal and TUI automation CLI for AI agents. Use when the user needs to create a terminal session, run a command in a terminal, automate an interactive CLI or TUI, wait for terminal output, capture a TUI screenshot, export a terminal recording, or test a CLI workflow with reviewable artifacts.

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

Structured TUI dogfooding and QA workflow using agent-tty. Use for exploratory testing, bug hunting, release-readiness validation, and UX review of terminal applications.

Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.

Guide for running statistically meaningful agent-tty evals with trials, parallelism, and A/B comparison. Covers non-determinism baseline, recommended sample sizes, and result interpretation.

Interview the user relentlessly about a plan or design. Use when the user wants to stress-test a plan before building, or uses any 'grill' trigger phrases.

A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

Internal maintainer SOP for version bumps, release PRs, tagging, publishing, and post-publish verification in this repository.

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

Break a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices.

Turn the current conversation into a PRD and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.

Move issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.