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Rote Shell

Organization
modiqo
rote-shell

Use for CLI and shell work through rote: running local commands with `rote exec`, capturing stdout/stderr/files, following logs and background processes, checking dependency manifests, mixing adapters/browser/process steps, and crystallizing CLI work into TypeScript flows. Prefer rote shell primitives over raw shell when the command result should be remembered, queried, replayed, or shared.

Overview

Publishermodiqo
Repositoryskillspec
Skill namerote-shell
Stars
699
Forks
43
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by modiqo on GitHub. Read the source before you install it.

Installation

Install the Rote Shell AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/modiqo/skillspec/tree/main/.claude/skills/rote-shell/source
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/modiqo/skillspec.git /tmp/skillspec
mkdir -p .claude/skills
cp -r /tmp/skillspec/.claude/skills/rote-shell/source .claude/skills/rote-shell
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rote Shell in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Rote Shell on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Rote Shell is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

rote-shell

Use rote for shell and CLI work when the result should become workspace memory: commands, outputs, files, logs, process lifecycle, dependencies, and flow replay. Raw shell is still fine for tiny inspection commands, but work that matters should pass through rote so it can be queried, audited, and crystallized.

Load the shell guidance when you need the complete command model:

bash
rote guidance shell essential

First Decision

Choose the narrowest rote primitive that preserves evidence:

  • one-shot command: rote exec -- <program> [args...]
  • stdin from a file: rote exec --stdin-file input.txt -- <program>
  • declared output file: rote exec --capture-file label:path -- <program>
  • moving file/log: rote stream follow --file logs/server.log --until READY
  • long-running process: rote exec --background --ready-log READY -- <program>
  • process stream: rote stream follow-process proc-1 --stream stdout --until READY
  • terminal-sensitive command: rote pty run -- <program> [args...]
  • dependency preflight: rote deps check deps.toml
  • crystallized replay: rote deno run --allow-all ~/.rote/flows/<name>/main.ts

Do not replace these with ad hoc command > file, tail -f, or ps | grep when the evidence should be durable. Rote already stores typed responses, artifacts, hashes, offsets, process leases, and command-log provenance.

Browser Intent Router

If the user says "browse", "open this site", "attach to my browser", "use the page", "click", "type", "snapshot", "extract from the page", "extract social profiles", "Gmail in browser", or otherwise asks for live web UI state, stop shell routing and invoke /rote-browse.

Do not satisfy browser intent with rote exec, raw Playwright, native web search, WebFetch, open, curl, or a saved non-browser flow unless the user explicitly switches substrate. Native search may help discover a URL only when the user asked for search/discovery or the browser route cannot identify a URL; it is not a substitute for browsing and extracting the page with rote.

Browse intent has precedence over the domain noun. For example, "browse my calendar", "browse Gmail", "browse HubSpot", or "browse Salesforce" means the user wants browser-state access even though those domains may also have APIs. You may still run rote flow search "<intent>" first, but only use an adapter/flow if it is installed, healthy, and completes the request. If the adapter/flow is missing, stale, unauthenticated, or fails setup, do not ask the user to build an adapter before trying the browser route. Hand off to /rote-browse and use an existing headed browser when the task depends on the user's logged-in profile.

For public profile extraction, such as "browse each committer's social profile", use GitHub/CLI/API data to collect candidate URLs and identities, then use /rote-browse to visit and extract the public pages. Do not replace that browse step with native web search summaries.

Default browser decision:

  • Existing login, Gmail, SSO, MFA, extensions, active tabs, or profile state: ask to attach to an existing headed browser.
  • Public read-only page, CI, or replay-like work: ask whether headless new-session is acceptable.
  • The user says "browse" without choosing mode: ask headed vs headless; if headed, ask attach-existing vs new rote-managed headed browser.

For active browser attach, hand off to /rote-browse and use its sequence:

bash
rote browser attach setup --method extension --browser chrome
rote browse <url> --headed --attach-existing --new-tab --no-prompt --no-snapshot
rote browse wait --selector '<ready-selector>' --timeout 30 --quiet-ms 750
rote browse snapshot

For browser plus shell work, keep both in the same workspace. Use /rote-browse for page leases, snapshots, slices, refs, auth state, and readiness. Use /rote-shell only after browser state has been materialized as a saved response, snapshot, slice, or file that a local CLI should process.

Current Capability Map

Use only shipped commands. Do not invent aliases from the roadmap.

NeedShipped commandNotes
One-shot process capturerote exec -- <program> [args...]Direct argv by default.
File stdinrote exec --stdin-file input.txt -- <program>Records stdin provenance.
Declared output filerote exec --capture-file label:path -- <program>Captures file metadata and artifact pointer.
Saved stdout/stderr filesrote exec --stdout-file out.txt --stderr-file err.txt -- <program>Use for durable stream files.
Dependency preflightrote deps check deps.tomlNo install side effects.
Moving file/log streamrote stream follow --file app.log --until READYSupports offsets, chunks, hashes, and pattern stop.
Background startrote exec --background --ready-log READY -- <program>Creates a tracked lease such as proc-1.
Background statusrote exec status proc-1Query lease state before acting.
Background waitrote exec wait proc-1 --timeout-ms 300000 --poll-ms 500Blocks until a tracked finite job exits or times out; records exit plus stdout/stderr observations.
Background stdout/stderr followrote stream follow-process proc-1 --stream stdout --until READYReads from background log artifacts.
Background stop and cleanuprote exec stop proc-1On Unix, stops the process group and records cleanup facts.
One-shot terminal transcriptrote pty run -- <program> [args...]Use when the command must see a terminal.

Deferred or not shipped as commands yet:

  • rote exec attach
  • rote exec log
  • explicit detach
  • persistent PTY sessions: start, send, snapshot, stop, attach
  • non-log readiness probes such as HTTP, TCP, file, or command probes
  • direct OS-pipe stream handles before background output reaches log artifacts
  • non-Unix process-group cleanup guarantees

If a task needs a deferred feature, say so and use the nearest shipped primitive instead. For example, use rote exec wait for finite tracked jobs, use rote stream follow-process ... --until <pattern> for log observation or readiness, and use rote exec status plus rote exec stop instead of raw ps/kill when the process is tracked.

TypeScript SDK Pattern Map

For authored TypeScript flows, use first-class SDK wrappers instead of hand-assembling command arrays. The SDK surface mirrors the shipped shell patterns:

PatternSDK call
Durable one-shotawait rote.exec({ argv: ["git", "status", "--short"], deps: ["git"] })
Declared stdin/output filesawait rote.exec({ argv, stdin: { file }, capture: { stdout: { file }, files: [{ label, path }] } })
Dependency preflightawait rote.depsCheck({ manifest: "deps.toml" })
Tracked background job / detach-like workawait rote.execBackground({ argv, readyLog, readyTimeoutMs, capture })
Long-running job with useful parallel workawait rote.execBackgroundAndJoin(request, async (job) => { ... }, { timeoutMs, pollMs, stopOnWorkError })
Lease statusawait rote.execStatus("proc-1")
Lease waitawait rote.execWait("proc-1", { timeoutMs: 300_000, pollMs: 500 }) or await job.wait(...)
Lease cleanupawait rote.execStop("proc-1")
Moving file streamawait rote.followFile("logs/app.log", { until: "READY" })
Background process streamawait rote.followProcess("proc-1", "stdout", { until: "READY" })
One-shot PTY transcriptawait rote.ptyRun({ argv, cols: 100, rows: 30 })
Authored ordered fan-outawait rote.execMany(requests, { stopOnError: false })

Use rote.shell().<method> when you want the shell namespace explicitly; the top-level rote.<method> forms are convenience aliases for authored flows.

Do not invent SDK methods for deferred roadmap items. There is no rote.detach, persistent PTY send, or direct OS-pipe stream handle yet. The current detach-like pattern is a tracked background lease with stdout/stderr files, execWait, followProcess, execStatus, and execStop.

rote.execMany preserves workspace response ordering by running process requests serially. For true parallel shell fan-out, generate declarative frontmatter steps: with type: process.exec, for_each, and max_concurrency so the DAG runner owns the scheduling and provenance.

For long-running finite jobs in authored TypeScript, prefer execBackgroundAndJoin or job.join when there is useful adapter, browser, process, file, or explicit stream work to do while the lease runs. The callback creates normal semantic DAG evidence; the final exec wait is the join point. Do not generate heartbeat or polling loops as DAG work. rote.execBackground(...) already prints the lease and poll commands to stderr. Do not duplicate that announcement in crystallized flows. Use announce: false only for deliberately quiet flows.

Crystallization Router

When the user asks to turn shell exploration into a reusable flow, choose the flow shape from the work pattern:

Exploration patternCrystallized shape
One finite command whose output is the factrote.exec({ argv, deps, capture })
Command writes files that downstream work readsrote.exec({ capture: { files: [...] } }) plus typed file paths
Existing file or log is the source of truthrote.followFile(path, options)
Long finite job where other useful work can runrote.execBackgroundAndJoin(request, async (job) => { ... }, options)
Long service or daemon with readinessrote.execBackground({ readyLog, capture }), then status/follow/stop
Need to inspect progress from a tracked leasejob.follow(...) or rote.followProcess(...)
Need completion proof from a tracked leasejob.wait(...) or rote.execWait(...)
Terminal behavior is the pointrote.ptyRun({ argv, input, cols, rows })
Many independent commands share one shapedeclarative steps: with process.exec, for_each, and max_concurrency

Crystallize causality, not waiting. Do not encode heartbeat loops, repeated status polling, or sleep/retry scaffolding as business DAG nodes. Those are observation mechanics. The reusable flow should expose semantic actions and joins: start work, observe meaningful artifacts or streams, wait for completion, then summarize.

Before authoring a TypeScript shell flow, read:

bash
rote guidance typescript flow-creation

That guide owns frontmatter, deps.toml, FlowOutput, release QA, and the shell SDK wrapper contract.

Strategy Pattern Library

Map the user's vague request to the smallest shipped pattern that preserves evidence:

SignalPatternUse
Tiny disposable inspectionRaw shell alloweddirect harness shell
Result may be queried, compared, summarized, or replayedDurable one-shotrote exec --
Command reads a known fileDeclared file inputrote exec --stdin-file or a direct argv path
Command creates a file that mattersDeclared file outputrote exec --capture-file
Full stdout/stderr mattersDurable stream files--stdout-file, --stderr-file
Required tools or input files matterDependency gatedeps.toml plus rote deps check
Existing log is movingFile stream watchrote stream follow --file
Start a server or daemon-like processService leaserote exec --background --ready-log
Long finite non-interactive jobTracked background jobrote exec --background --stdout-file --stderr-file
Inspect background outputProcess stream observationrote stream follow-process
Need liveness before actingLease statusrote exec status
Need cleanupLease cleanuprote exec stop
Many independent items share a command shapeFan-out batchsteps: with process.exec, for_each, and max_concurrency
API result feeds CLI or CLI result feeds APIMixed substrate chainadapter/browser primitive plus rote exec
Browser snapshot/file feeds local CLIBrowser-file bridgebrowser snapshot/file plus rote exec
Release, publish, deploy, or global mutationGuarded mutationdeps check, tool-native dry-run, approval, then foreground unless background is approved
Command checks whether stdout is a terminalOne-shot PTY transcriptrote pty run --
Command may prompt interactively and can be scripted safelyOne-shot PTY with bounded inputrote pty run --input or --stdin-file
Command needs ongoing human interactionForeground or deferpersistent PTY attach is not shipped

--dry-run, --resume, --force-resume, and --max-concurrency are DAG runner controls for frontmatter steps: flows. They are not universal rote exec flags. For a single command, use the tool's own dry-run/check mode when available.

Workspace Setup

CLI work must happen inside a rote workspace:

bash
rote init cli-work --seq --force
rote workspace sandbox cli-work off
cd ~/.rote/rote/workspaces/cli-work

Keep commands simple and literal. Avoid shell control operators, command substitution, and long && chains unless the user explicitly needs shell semantics. Prefer direct argv:

bash
rote exec -- rg TODO docs

Use shell parsing only when it is the real subject of the work:

bash
rote exec -- sh -c 'printf "alpha\n" | tr a-z A-Z'

Query After Every Meaningful Step

Treat every @N as the handle for what just happened. The handle is saved evidence, not always the raw business payload. Route by type.

After a command finishes, read @@result first:

  • response_id is the saved evidence handle
  • response_kind tells you how to query the evidence
  • primary_query, primary_stdout_query, primary_stderr_query, or artifact_query are exact typed queries for the saved response
  • @@next remains the immediate next-action guide

For one-shot process output, prefer the typed query fields from @@result:

bash
rote query @1 '.stdout.text' -r
rote query @1 '.stderr.text' -r
rote query @1 '.status.exit' -r
rote query @1 '.files' -r
rote query @2 '.cleanup' -r

Use @proc addresses when inspecting process responses:

bash
rote query @proc.last.stdout '.text' -r
rote query @proc.1.exit '.' -r
rote query @proc.last.transcript '.text' -r

When @@result gives an exact query such as rote query @proc.4.transcript '.text' -r, prefer it over @proc.last if any other command may run before you query. Use rote @N . for full provenance inspection, not as a shortcut for stdout or PTY transcript text.

Do not summarize from terminal scrollback when a structured query exists.

Files And Artifacts

Declare file inputs and outputs instead of relying on memory:

bash
rote exec \
  --stdin-file input.txt \
  --capture-file summary:out/summary.txt \
  -- python3 scripts/summarize.py

This records stdin provenance, file change state, media type, hashes when available, and artifact paths under .rote/artifacts/processes/@N/.

Background Processes

Start servers as leases, not mystery PIDs:

bash
rote exec --background --ready-log "Listening" --ready-timeout-ms 10000 -- npm run dev
rote exec status proc-1
rote stream follow-process proc-1 --stream stdout --until "GET /health"
rote exec stop proc-1
rote query @3 '.cleanup' -r

On Unix, rote starts background commands in a process group and stops the group with TERM followed by KILL if needed. Inspect .cleanup before claiming a process stopped.

Long-Running Finite Jobs

For long-running but finite commands, use a tracked background lease instead of an untracked detach. rote exec detach is not shipped yet. The current detached-like primitive is:

bash
rote exec \
  --background \
  --stdout-file logs/job.stdout.log \
  --stderr-file logs/job.stderr.log \
  -- cargo test --all-targets --all-features

rote exec status proc-1
rote exec wait proc-1 --timeout-ms 600000 --poll-ms 1000
rote stream follow-process proc-1 --stream stdout --from-start --max-bytes 65536
rote stream follow-process proc-1 --stream stderr --from-start --max-bytes 65536

Use this when the command is non-interactive, can safely continue while the agent does other work, and its stdout/stderr are enough to monitor progress. Use exec wait to establish completion and exit status. Use follow-process to inspect output, not as the primary completion detector. Keep the lease id (proc-1) in the task notes and query status before making claims about completion if wait has not finished.

In authored TypeScript, prefer the semantic join helper:

ts
const joined = await rote.execBackgroundAndJoin(
  { argv: ["cargo", "test"], deps: ["cargo"] },
  async (job) => {
    const checks = await rote.exec({ argv: ["gh", "pr", "checks"], deps: ["gh"] });
    const stderr = await job.follow("stderr", { fromStart: true, maxBytes: 65536 });
    return { checks, stderr };
  },
  { timeoutMs: 600_000, pollMs: 1_000, stopOnWorkError: true },
);

The callback's work becomes semantic DAG evidence. The wait remains the completion join. Poll/heartbeat internals do not become graph nodes.

Do not background a command when it may prompt for credentials, OTP, passphrase, license acceptance, or confirmation. rote pty run can capture a bounded one-shot terminal transcript, but it does not provide persistent attach. Ongoing interactive jobs should run foreground or be postponed until the user can drive the prompt.

One-Shot PTY

Use PTY only when terminal behavior is the point: commands that check isatty, render progress differently on terminals, or can be driven with bounded scripted input.

bash
rote pty run --cols 100 --rows 30 -- script-that-checks-tty
rote pty run --input "yes\n" -- interactive-but-scriptable-command
rote query @proc.last.transcript '.text' -r

Do not pass secrets through --input; terminal echo may record them in the transcript. Do not use PTY for persistent REPLs or long human-driven sessions until start/send/snapshot/stop support exists.

Treat release and publish commands as high risk. For examples like cargo release, npm publish, gh release create, or deploy commands:

  1. Run dependency preflight first.
  2. Run the tool's dry-run/check mode first when available.
  3. Show the planned mutation and ask the user for approval before the real run.
  4. Prefer foreground for final irreversible publish steps unless the user explicitly approves tracked background execution.
  5. If background execution is approved, capture stdout/stderr to files, follow process streams, and keep the flow draft until completion evidence is captured.
  6. Do not stop a release/publish process unless the user asks; interruption can leave external state partially mutated.

Decision rule:

  • short and non-interactive: foreground rote exec
  • long and non-interactive: tracked rote exec --background
  • long-running service: tracked rote exec --background --ready-log ...
  • interactive: foreground or wait for PTY/attach support
  • irreversible release/publish: dry-run, user approval, then foreground unless tracked background is explicitly requested

Dependency Manifests

When a task depends on local tools, create or update ~/.rote/flows/<name>/deps.toml before replay. This is not optional for crystallized shell flows: if the flow calls rote.exec({ argv }) for git, gh, cargo, python, node, jq, rg, or any other local executable, the flow directory must include a matching dependency manifest before the flow is marked released.

toml
schema_version = 1

[[tools]]
id = "github-cli"
command = "gh"
required = true
version_command = ["gh", "--version"]

[files]
required = ["input.txt"]

Then run:

bash
cd ~/.rote/flows/<name>
rote deps check deps.toml

Do not auto-install tools into global locations unless the user approved that specific provisioning policy. A crystallized flow should declare dependencies so the target environment can check or provision them before work begins.

If rote deps check deps.toml reports missing required tools, stop and elicit an install decision from the user before continuing. Show the missing tool, why the flow needs it, and the lowest-risk install scope available. Prefer project-local or rote-managed installs over global package manager installs. Only install globally when the user explicitly approves that scope.

Use this shape:

text
The flow needs these missing tools before replay:
- gh: required for GitHub PR and Actions checks

I can install/provision them using one of these scopes:
- rote-managed/project-local: preferred when available; keeps replay isolated
- user/global package manager: broader machine mutation; requires explicit approval

Do you want me to install/provision the missing tools, or should I leave the
flow in draft until you install them?

After any approved install or user-managed install, rerun:

bash
cd ~/.rote/flows/<name>
rote deps check deps.toml

Never mark the flow released while required dependencies are still missing.

Mixed Workflows

For API plus CLI work, use the adapter for typed API calls and rote exec for local CLI facts. Example shape:

bash
rote POST /github '{"method":"GET","path":"/repos/$owner/$repo"}' -t -s
rote exec -- gh repo view "$owner/$repo" --json name,visibility
rote query @1 '.' -r
rote query @2 '.stdout.text' -r

For browser plus CLI work, use rote-browse for page state and rote-shell for local processing of snapshots/artifacts. Do not drop into raw Playwright or raw shell when a rote primitive can preserve the evidence.

Current mixed replay support is intentionally asymmetric:

  • adapter and process.exec actions are first-class steps: DAG actions
  • browser observations are bridged through saved responses, snapshots, and files until first-class browser DAG actions ship

For browser-involved crystallization today, capture the browser state with rote-browse, materialize the snapshot or slice to a file, then consume that file from process.exec.

Crystallization Rule

After a useful CLI workflow works twice, ask whether to crystallize it. The canonical replay command for TypeScript flows is:

bash
rote deno run --allow-all ~/.rote/flows/<name>/main.ts

Use rote flow run only as compatibility syntax. New generated usage should prefer rote deno run --allow-all.

Crystallization Workflow

When the user says yes, do the full release discipline:

  1. Choose the correct scaffold path:

    • Shell-only flow: write ~/.rote/flows/<name>/main.ts manually with @rote-frontmatter. Do not run rote flow pending save, rote flow template create, or rote flow frontmatter; those commands require --adapter in the current implementation and will fail or emit an adapter-shaped flow.
    • Mixed adapter/shell flow: use rote flow frontmatter or rote flow template create so adapter fingerprints and parameters are captured. Then choose one execution shape:
      • Declarative DAG: add top-level steps: when the replay can be expressed as adapter calls plus type: process.exec actions.
      • Authored SDK: write TypeScript with FlowOutput, runPreflight(...), and SDK calls such as rote.exec({ argv }) when custom branching, formatting, help text, or richer TypeScript logic is needed.

    Minimal shell-only frontmatter shape:

    typescript
    /**
     * CSV Sales Report
     *
     * Summarizes a local CSV into JSON and a text report.
     *
     * @rote-frontmatter
     * ---
     * name: csv-sales-report
     * description: "Summarizes a local CSV into JSON and a text report using rote shell primitives."
     * provenance:
     *   tier: local
     *   workspace: csv-json-report-demo
     * metadata:
     *   status: draft
     *   kind: atomic
     *   flow_type: sequential
     *   format: typescript
     *   requires_endpoints: []
     *   requires_sessions: false
     *   parameters:
     *   - name: input
     *     type: string
     *     required: true
     *     description: "Input CSV path"
     *   - name: out_dir
     *     type: string
     *     required: false
     *     default: "out"
     *     description: "Output directory"
     *   tags:
     *   - shell
     *   - process
     *   - typescript
     * ---
     */
  2. Create ~/.rote/flows/<name>/main.ts.

  3. For declarative DAG flows, put the replay graph in frontmatter steps:. For authored SDK flows, use TypeScript SDK shell primitives for process work: rote.exec, rote.execBackground, rote.execStatus, rote.execStop, rote.followFile, rote.followProcess, rote.ptyRun, rote.depsCheck, and rote.execMany. Use adapter handles from runPreflight(...) for adapter work.

  4. Create ~/.rote/flows/<name>/deps.toml for every local tool or required input file. For shell-only flows, prefer a real deps.toml file over frontmatter-only dependency prose so replay can run rote deps check.

  5. Keep frontmatter parameters, usage text, and the flag parser in lockstep. If frontmatter names use underscores, the parser must accept those exact names or documented aliases; do not ship github_repo metadata with only a --github-repo parser unless both forms work.

  6. Start with metadata.status: draft. Do not set released until dependency preflight and replay QA have passed.

  7. Test the draft with at least three distinct inputs:

    bash
    cd ~/.rote/flows/<name>
    rote deps check deps.toml
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts <input-a>
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts <input-b>
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts <input-c>

    If dependency preflight fails, ask the user whether to provision missing required tools, with the install scope and side effects stated plainly. Do not continue release QA until dependency preflight passes or the user says to keep the flow as draft.

  8. Use the right QA gate for the execution shape.

    Declarative steps: DAG flows:

    bash
    rote flow validate ~/.rote/flows/<name>/main.ts
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts --dry-run <params>
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts <params>
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts --resume latest <params>

    rote flow lint checks the authored FlowOutput contract and is not a release gate for pure steps: DAG flows whose TypeScript body is bypassed by the DAG runner.

    Authored SDK flows:

    bash
    rote flow lint <name>
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts --help
    rote deno run --allow-all ~/.rote/flows/<name>/main.ts <known-good-input>

    In both shapes, loop until hardcoded paths, missing dependency declarations, mismatched parameters, raw shell leaks, and output-format issues are fixed.

  9. Mark the flow released only after QA passes. Current practice is to edit the frontmatter status from draft to released, then rebuild and verify the index:

    bash
    rote flow index --rebuild
    rote flow search "<name or relevant keywords>"
  10. If a pending workspace stub was used, discard it after release:

bash
rote flow pending discard <workspace>

Do not claim a shell-derived flow is released from memory. The release claim must point back to rote deps check deps.toml, command output, saved responses, and successful rote deno run --allow-all executions.

Step Reference Rules For Mixed DAGs

In steps: flows, @step{.path} resolves against the step response body, not the persisted @N envelope on disk. For an MCP adapter call, the response body is the JSON-RPC body, so a GitHub adapter text payload usually needs a scalar query such as:

text
@repo_adapter{.result.content[0].text | fromjson | .full_name}

For process steps, the response body is process.exec, so downstream steps can reference fields such as .stdout.text or captured file metadata. Keep process.exec argv, stdin paths, and capture paths scalar after resolution. Do not pass large adapter/browser payloads through argv when a file bridge or a small scalar projection is clearer.

Frequently asked questions

What does the Rote Shell AI skill do?

Use for CLI and shell work through rote: running local commands with `rote exec`, capturing stdout/stderr/files, following logs and background processes, checking dependency manifests, mixing adapters/browser/process steps, and crystallizing CLI work into TypeScript flows. Prefer rote shell primitives over raw shell when the command result should be remembered, queried, replayed, or shared.

Why use Rote Shell on TypingMind?

Because you install it once and use it with any model. Rote Shell is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Rote Shell in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/modiqo/skillspec/tree/main/.claude/skills/rote-shell/source. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Rote Shell?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Rote Shell?

As many as you like. As long as a model supports skills, you can use Rote Shell with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Rote Shell AI skill free?

Yes. It is published on GitHub by modiqo under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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