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Get Started Free →Use when working with the Runtype TypeScript or Python SDK, FlowBuilder, BatchBuilder, EvalBuilder, CLI commands, Marathon long-running agent tasks, playbooks, model fallback, built-in CLI tools, sandboxes, code-first stored/upsert/virtual agents or flows, local tools, hidden parameters, or source-controlled Runtype workflows.
.claude/skills/hashgraph-online-runtype-sdk-marathon/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | -34% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -17% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -24% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -17% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 4% | 0% |
Use this skill for code-first Runtype workflows, the CLI, and Marathon. Use runtype-build-product when the user is designing hosted product resources through MCP.
Fetch live docs when available:
get_platform_documentation(topic="sdk-reference")get_platform_documentation(topic="types-flow-steps")get_platform_documentation(topic="types-entities")get_platform_documentation(topic="flow-step-types")Code-first modes:
Default to stored or upsert for production workflows because dashboard inspection, logs, evals, and versioning are easier. Use virtual for tests, one-offs, privacy constraints, or temporary generated flows.
Use local tools when execution must happen in the user's browser or server. Use hidden parameters when auth context, tenant ids, or sensitive request data must not appear in the model-visible tool schema.
Install or run directly:
bashnpm install -g @runtypelabs/cli npx @runtypelabs/cli@latest <command>
Authenticate:
bashruntype auth login runtype auth whoami
Export a key for stdio MCP or CI only when needed:
bashexport RUNTYPE_API_KEY=$(runtype auth export-key)
Common commands include runtype agents list, runtype dispatch, runtype flows create, runtype records create, runtype schedules, runtype models, runtype batch, runtype eval, runtype persona, runtype products init, and runtype validate-product.
For command flags not listed here, run runtype --help or runtype marathon --help instead of expanding this skill with CLI reference text.
Marathon is the CLI harness for long-running research, code editing, and build tasks. It streams progress, can run multiple sessions, manages continuation context, supports playbooks, and can use sandboxes.
Examples:
bashruntype marathon researcher \ --goal "Research recent AI announcements and summarize them" \ --tools firecrawl \ --max-sessions 2 runtype marathon "Code Editor" \ --goal "Refactor the auth module and run tests" runtype marathon calculator \ --goal "Build a calculator in 3D and deploy it publicly" \ --sandbox daytona
Built-in CLI tools exposed by --tools include exa, firecrawl, and dalle. The CLI validates requested tool ids and model compatibility at startup.
Playbooks live in .runtype/marathons/playbooks/ in the current repo or the user's home directory. Use them for repeatable workflows with milestones, models, fallback models, completion criteria, and rules.
Use playbooks when the task has durable phases such as research, build, verify, and polish. Keep rules explicit about file scope, verification, and deployment expectations.
If the umbrella runtype skill is installed alongside this focused skill, its durable references provide deeper working-mode guidance. This skill must still work when installed by itself; prefer live MCP docs over local sibling files.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-05 | fail→pass | 28,760 | 3,591 | -88% | 1 | 1 | 0% | 1,951 | 1,297 | -34% | 0 | 0 | — |
case-01 | fail→fail | 21,865 | 17,385 | -20% | 1 | 1 | 0% | 3,034 | 2,954 | -3% | 0 | 0 | — |
case-02 | fail→pass | 16,218 | 4,172 | -74% | 1 | 1 | 0% | 1,859 | 1,542 | -17% | 0 | 0 | — |
case-03 | fail→pass | 21,333 | 8,048 | -62% | 1 | 1 | 0% | 2,889 | 2,184 | -24% | 0 | 0 | — |
case-04 | fail→pass | 12,811 | 4,732 | -63% | 1 | 1 | 0% | 1,975 | 1,640 | -17% | 0 | 0 | — |
case-06 | fail→pass | 15,268 | 3,390 | -78% | 1 | 1 | 0% | 1,370 | 1,419 | +4% | 0 | 0 | — |
case-07 | fail→fail | 15,555 | 3,403 | -78% | 1 | 1 | 0% | 1,585 | 1,379 | -13% | 0 | 0 | — |
case-08 | fail→fail | 14,918 | 2,828 | -81% | 1 | 1 | 0% | 1,670 | 1,277 | -24% | 0 | 0 | — |
case-09 | fail→pass | 17,510 | 3,741 | -79% | 1 | 1 | 0% | 1,703 | 1,279 | -25% | 0 | 0 | — |
case-10 | pass→pass | 24,548 | 22,537 | -8% | 1 | 1 | 0% | 3,242 | 2,845 | -12% | 0 | 0 | — |
case-11 | pass→pass | 19,767 | 18,874 | -5% | 1 | 1 | 0% | 2,504 | 2,516 | +0% | 0 | 0 | — |
case-12 | fail→pass | 11,692 | 5,183 | -56% | 1 | 1 | 0% | 1,264 | 1,441 | +14% | 0 | 0 | — |
case-13 | fail→pass | 17,051 | 9,052 | -47% | 1 | 1 | 0% | 2,152 | 1,627 | -24% | 0 | 0 | — |
case-14 | fail→pass | 15,533 | 9,831 | -37% | 1 | 1 | 0% | 1,949 | 1,540 | -21% | 0 | 0 | — |
case-15 | fail→pass | 23,069 | 16,892 | -27% | 1 | 1 | 0% | 3,024 | 2,829 | -6% | 0 | 0 | — |
case-16 | fail→pass | 14,638 | 4,135 | -72% | 1 | 1 | 0% | 2,233 | 1,288 | -42% | 0 | 0 | — |
case-17 | pass→pass | 24,926 | 11,709 | -53% | 1 | 1 | 0% | 1,885 | 1,970 | +5% | 0 | 0 | — |
case-18 | fail→pass | 10,710 | 3,473 | -68% | 1 | 1 | 0% | 1,585 | 1,311 | -17% | 0 | 0 | — |
case-19 | fail→pass | 26,492 | 10,452 | -61% | 1 | 1 | 0% | 3,111 | 1,300 | -58% | 0 | 0 | — |
case-20 | fail→pass | 19,767 | 7,867 | -60% | 1 | 1 | 0% | 2,094 | 1,180 | -44% | 0 | 0 | — |
case-21 | fail→pass | 17,642 | 5,414 | -69% | 1 | 1 | 0% | 3,038 | 1,536 | -49% | 0 | 0 | — |
case-22 | pass→pass | 19,514 | 13,596 | -30% | 1 | 1 | 0% | 1,703 | 1,931 | +13% | 0 | 0 | — |
case-23 | pass→pass | 10,849 | 13,952 | +29% | 1 | 1 | 0% | 1,854 | 2,017 | +9% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +65 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.