This internal module checks whether cli-exercise can use its required build, terminal, and media tools. When a dependency is missing, it identifies a suitable setup path and requires approval before installation, then rechecks readiness. It does not authorize recordings or other actions.
Internal readiness and installation-consent flow for cli-exercise. Requires entry-skill context and does not independently authorize a recording or installation.
Run score Not tested
See how to installThis internal module checks whether the tools needed by cli-exercise are ready. It uses a Go helper to check the Node/Tuistory API and pseudo-terminal, ffmpeg/ffprobe and the requested encoder, font rendering in Go, and any shell or executable needed for the cases. If dependencies are missing, it checks for existing installations and then presents versions, sources, destinations, and commands for a proposed setup. Installation requires approval. After setup, it checks the capabilities again.
Use this module before starting a recording with cli-exercise to see whether the environment is ready. It can check support for MP4 output needed by session videos, as well as GIF output when requested. The results help identify available capabilities, missing dependencies, and whether preparation can proceed.
This module is not called on its own; it is an internal reference used in the context of cli-exercise. Approval is required to install dependencies. That approval does not authorize recording, file changes, GitHub writes, or other actions. The check reports readiness; it does not grant permissions or provide operating-system isolation.
This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.
AI checked the SKILL.md for operations that need care and for setup requirements. The score comes only from actually running the skill (hands-on test).
Not counted in the score. Rated by AI (OpenAI Codex) as of Oct 26, 2026. Treat it as a guide and read the original before installing.
Review the instructions the agent will receive before you install.
Use the package root containing the user-facing cli-exercise/SKILL.md.
This module is bundled with that skill and is loaded as a referenced resource.
If the caller supplies a ready receipt already checked for this task, read and reuse it when its selected tools and probed formats match the case. Do not repeat probes or propose installation just because the receipt was produced elsewhere in the same task. Recheck if its current applicability is uncertain. A receipt does not grant installation or test-resource authority. Normal session delivery, even for one case, needs MP4 chapter intermediates; confirm MP4 capability as well as any requested GIF output.
When a check is needed, first follow the offline-first Go build instructions in the prerequisite reference. Build the helper once for this task, outside the skill and repository, then use that executable:
<helper> --skill-root <package-root> preflight check --output <workspace>/preflight.json
Keep Go toolchain auto-downloads and module downloads disabled on the first build. If a locked dependency is missing from the selected cache, show the packages, sources, destination and build command, then ask before enabling its download. A compile error is not permission to try an online build.
Explicit existing Node module, executable, and font paths can be supplied using the documented overrides. Never embed operator-specific paths in the skill.
Check usable capabilities: the Node/Tuistory API and native PTY, ffmpeg/ffprobe and requested encoders, and actual Go font rasterization. Also identify any case-specific shell, editor, or executable. A command on PATH does not prove that its native bindings or required API work.
When a dependency is missing or incompatible:
Use an appropriate dependency location outside the skill and repository. Do not globally update tools or change project dependency manifests by default. If system installation or authentication is required, state that separately. Never enter an OS password or turn a failed privileged command into success.
If approval is declined, unavailable, or the install/recheck fails, report
blocked with the precise remedy. Preserve diagnostics and any partial-install
facts. Do not silently change recorders, output formats, or supplied cases.
The helper only checks capabilities. Perform approved setup with the appropriate package manager.
Dependency approval does not authorize GitHub writes, filesystem changes outside the workspace, credential changes, purchases, or other effects. Obtain the required case-specific authorization separately and record its actual source.
The resulting receipt identifies tools used by the runtime and renderer. It is readiness evidence, not an OS sandbox or a permission bypass.
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This dispatcher helps with GitHub Agentic Workflows by identifying whether a request is about design, creation, configuration, updates, debugging, or upgrades. It selects the matching workflow prompt or skill file so the agent can follow task-specific guidance.
Exercise a real command-line program with specified cases or a stated goal, then capture and verify the observed behavior. It produces local media evidence such as a session video, helping reviewers see what the command did without treating the recording as proof of general correctness.
Verify CLI exercise expectations against recorded evidence, render requested media, inspect the results, and return local artifacts with case outcomes. The workflow keeps failures visible and does not publish evidence by default.
Use this skill to execute supplied CLI test cases without changing their commands, inputs, ordering, or assertions. It guides preparation, exercise, and validation case by case, then classifies results as passed, failed, blocked, or observed based on actual evidence.
Use this skill to explore a CLI goal by choosing observable checks within an approved scope. It guides the agent through preparation, one exercise, and immediate validation for each case, then helps report what the evidence established and what remained unreachable.
Run and record CLI exercise cases through a shared Go runtime and Tuistory adapter. The skill follows approved setup, exercise, validation, and cleanup phases, captures observed terminal behavior, and preserves execution evidence and chronology.