Agent skill

Writing Relayflows

by AgentWorkforce in AgentWorkforce/relay

A skill your agent uses when authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk, the journal-based v2 engine — the CLI is flows, package versions 2.0.x) in TypeScript or YAML/JSON.

Apache-2.0Auto-check passed

Install Writing Relayflows

skills CLI
$ npx skills add AgentWorkforce/relay --skill writing-relayflows -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install AgentWorkforce/relay writing-relayflows --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/AgentWorkforce/relay.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/writing-relayflows .claude/skills/writing-relayflows && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
writing-relayflows
GitHub stars
865
Token cost
~3.3k tokens
SKILL.md length
824 words
Files
1
Skills in repo
14
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk, the journal-based v2 engine — the CLI is flows, package versions 2.0.x) in TypeScript or YAML/JSON.

  • Works in 3 steps: run / deterministic — a shell command.… → llm / llm — a bare model call. Prompt… → agent / agent — a harnessed coding agent…
  • Authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • The journal-based v2 engine — the CLI is flows

What it does

Writing Relayflows is an agent skill from AgentWorkforce/relay. Use when authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk, the journal-based v2 engine — the CLI is flows, package versions 2.0.x) in TypeScript or YAML/JSON. Covers the three-rung ladder (run/llm/agent), the resident verbs (human/dispatch/done), verification gates, TypeScript vs YAML authoring, per-step cli/model selection and its resolution order, flows.json, and flows check/run/resume with their real refusal shapes and exit codes. Not for the older, unrelated @relayflows/core WorkflowBuilder…

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with TypeScript. The repository describes itself as: Infrastructure for coding agents. The licence is Apache-2.0.

When your agent uses it

  • Authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk
  • The journal-based v2 engine — the CLI is flows
  • Package versions 2.0.x) in TypeScript

Example prompts

  • “/writing-relayflows”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. run / deterministic — a shell command. No model. Implicit gate is exit_code == 0.
  2. llm / llm — a bare model call. Prompt in, verified output out. No workspace, no tool use.
  3. agent / agent — a harnessed coding agent in a workspace. Returns { summary, artifacts }, not raw text.

What it can do on your machine

Read from SKILL.md and the folder at commit 734600d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript, yaml and json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com
    • agentrelay.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Writing Relayflows loads about 3.3k tokens when it runs. Until then it costs about 183 tokens; SKILL.md has 824 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~183
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AgentWorkforce/relay at commit 734600d, republished under its Apache-2.0 licence (© AgentWorkforce). 824 words, ~3,312 tokens.

Download SKILL.mdSave it as .claude/skills/writing-relayflows/SKILL.md (or your agent's skills folder).
name
writing-relayflows
description
Use when authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk, the journal-based v2 engine — the CLI is `flows`, package versions 2.0.x) in TypeScript or YAML/JSON. Covers the three-rung ladder (run/llm/agent), the resident verbs (human/dispatch/done), verification gates, TypeScript vs YAML authoring, per-step cli/model selection and its resolution order, flows.json, and `flows check`/`run`/`resume` with their real refusal shapes and exit codes. Not for the older, unrelated `@relayflows/core` WorkflowBuilder engine (`.pattern('dag')`/.agent()/.step() chains) that `writing-agent-relay-workflows` and `migrating-persona-to-relayflow` cover — that's a different product despite the similar name.
Overview

Relayflows turns a coding-agent task into steps a journal can inspect, verify, and resume. A flow is data (YAML/JSON) or code (TypeScript) that compiles to the same journal-backed kernel spec. Every effect is journaled before it's treated as real — a journal write that fails fails the step, with no silent fallback.

Name collision warning. This repo also has skills for an older, unrelated engine that is also casually called "Relayflow" (singular) — @relayflows/core's WorkflowBuilder, a chained builder (workflow('name').pattern('dag').agent(...).step(...).run()). That's writing-agent-relay-workflows and migrating-persona-to-relayflow's territory. This skill is the v2 engine: @relayflows/surface's flow() function and the YAML/JSON dialect compiled by @relayflows/sdk. If you see .pattern(, .agent( as a chained builder call, or ctx.workflow.run(), you're in the other engine — stop and use one of those skills instead.

When to use this skill
  • Writing a new .flow.ts or .flow.yaml/.flow.json for the flows CLI (package @relayflows/sdk, binary name flows).
  • Deciding whether a step needs run (shell), llm (bare model call), or agent (harnessed coding agent in a workspace).
  • Wiring up cli/model for an agent or llm step, in either language.
  • Debugging a REFUSED [...] message from flows check or flows run.
  • Choosing between TypeScript and YAML for a given flow.
The ladder

Three step verbs, one per rung — never more (packages/sdk/src/spec.ts, export type StepType = 'deterministic' | 'llm' | 'agent';):

  1. run / deterministic — a shell command. No model. Implicit gate is exit_code == 0.
  2. llm / llm — a bare model call. Prompt in, verified output out. No workspace, no tool use.
  3. agent / agent — a harnessed coding agent in a workspace. Returns { summary, artifacts }, not raw text.

Plus four resident verbs that aren't ladder rungs: human (durable approval), dispatch (hand off to a child flow), done (typed finish), and in YAML, on/triggers (event entry points — out of scope for this skill).

Most flows only need run and llm. Climb to agent once a step needs hands on a real workspace.

Two ways to author the same thing
TypeScript
ts
import { flow } from '@relayflows/surface';

export default flow('hello', async (f) => {
  const greeting = await f.run('echo "Hello from Relayflows"');
  console.log(greeting.trim());

  const answer = await f.agent('greeter', {
    task: 'Reply with one short hello sentence. Do not use tools or modify files.',
    cli: 'claude',
    model: 'claude-sonnet-4-6',
  });
  console.log(answer.summary);

  f.done('success');
});
YAML
yaml
version: '0.1.0'
name: hello
steps:
  - id: greeting
    type: deterministic
    command: 'echo "Hello from Relayflows"'
  - id: greeter
    type: agent
    dependsOn: [greeting]
    instruction: 'Reply with one short hello sentence. Do not use tools or modify files.'
    cli: claude
    model: claude-sonnet-4-6
The real Ctx contract (TypeScript)
packages/surface/src/context.ts, current as of origin/main@86a2ec2:
ts
export interface AgentResult {
  summary: string;
  artifacts: string[];
}

export interface AgentOptions {
  task: string;
  workspace?: string;
  cli?: string;
  model?: string;
}

export interface Ctx {
  run(command: string): Step<string>;
  llm(strings: TemplateStringsArray, ...values: unknown[]): Step<string>;
  llm(
    prompt: string,
    options: { output: Record<string, unknown>; cli?: string; model?: string }
  ): Step<unknown>;
  agent(name: string, options: AgentOptions): Step<AgentResult>;
  human(question: string, options: { to: string }): Promise<boolean>;
  dispatch<T>(flow: string, input: unknown): Promise<T>;
  done(reason: RunCompletionReason): void;
  cloud: CloudHelper;
  slack: SlackHelper;
}
The real step shapes (YAML/JSON, packages/sdk/src/spec.ts)
```ts
ts
interface DeterministicStepSpec {
  type: 'deterministic';
  id: string;
  command: string;
  dependsOn?: string[];
  timeoutMs?: number;
  verification?: VerificationSpec; // omit for implicit exit_code
}

interface LlmStepSpec {
  type: 'llm';
  id: string;
  prompt: string;
  dependsOn?: string[];
  verification?: OutputVerificationSpec;
  model?: string;
  cli?: string;
}

interface AgentStepSpec {
  type: 'agent';
  id: string;
  instruction: string;
  dependsOn?: string[];
  verification?: OutputVerificationSpec;
  agent?: string; // selects a named FlowSpec.agents entry
  cli?: string;
  model?: string;
  surfaces?: { workspace?: { surface: string }[]; streams?: { stream: string }[]; external?: string[] };
  recoveryMode?: 'reset' | 'inspect' | 'manual'; // default 'reset'
  permissions?: {
    fileGlobs?: string[];
    networkAllowlist?: string[];
    accessPreset?: 'readonly' | 'readwrite';
  };
}

interface FlowSpec {
  version: string; // required, e.g. '0.1.0' — not optional
  name?: string;
  cli?: string; // flow-level CLI default
  agents?: Record<string, { cli: string; model: string }>; // both fields required
  steps: StepSpec[];
  budget?: { maxTokensIn?: number; maxTokensOut?: number; maxDollars?: string };
}
Verification gates
Verification is control flow, not decoration — a gate decides whether a step actually completed, not just whether the process exited cleanly (packages/sdk/src/spec.ts, VerificationGateType):
yaml
- id: classify
  type: llm
  prompt: 'Classify this ticket as bug, feature, or question: "the export button does nothing"'
  cli: claude
  model: claude-sonnet-4-6
  verification:
    type: output_contains
    value: bug
cli / model: what a step actually runs on
Both YAML and TypeScript agent/llm steps can set cli and model directly (TypeScript since flows#310, AgentOptions.cli?/.model?). Resolution order for cli — checked once per step by preflight.ts's resolveCli (packages/sdk/src/preflight.ts:265-282), identical regardless of authoring language because both compile to the same StepSpec:
$ flows check hello.flow.yaml   # agent step, no cli anywhere
REFUSED [cli_unresolved] Step "greeter" has no CLI at step, flow, or project level. No flows.json was found from "..." to the filesystem root.
flows.json
json
{ "cli": "claude", "executors": ["cron"], "models": ["claude-sonnet-4-6"] }
Human approval and dispatch (TypeScript resident verbs)
```ts
ts
import { flow } from '@relayflows/surface';

export default flow('ship-feature', async (f) => {
  const plan = await f.agent('planner', {
    task: 'Research and plan: add OAuth2 support',
    workspace: 'acme/api: readonly', // compiles to relayauth path scopes
  });

  const ok = await f.human(`Ship this?\n${plan.summary}`, { to: 'khaliq' });
  if (!ok) return f.done('canceled');

  const pr = await f.dispatch('garden/implement', plan); // hands off to a child flow
  f.done('success');
});
Running it: flows check / run / resume
Real usage (packages/sdk/src/cli.ts):
flows check [--json] <flow.yaml|spec.json>
flows run [--json] [--no-spawn] [--no-observer-link] [--data-dir <dir>] [--local-agent] <flow.yaml|spec.json>
flows run [--json] [--no-spawn] [--no-observer-link] [--data-dir <dir>] [--local-agent] <flow.ts> --input <inline-json-or-file>
flows resume [--json] [--no-spawn] [--no-observer-link] [--data-dir <dir>] <run-id>
Common mistakes
  • Forgetting version in a YAML/JSON FlowSpec. It's required, not optional — flows check refuses a spec without it.
  • Adding agents: to a TypeScript flow() header. FlowHeader has no such field; it throws TypeError: flow header has unknown fields: agents at authoring time. Named-agent maps + agent: selector are YAML/JSON-only (flows#300 tracks TypeScript composition via use:, not yet shipped).
  • Assuming flows.json's models sets a default model. It only validates models already declared elsewhere; it never selects one.
  • Not awaiting a step, or manually .then()-chaining one. Both are refused (unawaited_step / unsupported_verb) rather than silently ignored — the executor closes every root operation's lifecycle explicitly.
  • Running a .flow.ts without --input. Required even for flows that don't use their input argument.
  • Expecting a fifth done() reason. The set is closed: success | step_failed | canceled | budget_exceeded. Don't invent partial or skipped.
Show full SKILL.md (263 more words)Show less
What this skill does NOT cover
  • Named-agent maps in TypeScript (agents: { reviewer: { cli, model } } + reuse across steps by name) — YAML/JSON only today. Tracked for TS composition via use: at flows#300.
  • recoveryMode, permissions, surfaces, budget, memory on agent steps — real YAML/JSON fields with no TypeScript equivalent. Author that step in YAML and reach it from TypeScript with f.dispatch if you need them.
  • Cloud execution (flows run --cloud), triggers/webhooks, memory retrieval, and the f.mcp/f.slack helper namespaces — each is its own surface with its own gotchas; see the Relayflows product docs for what's shipped versus designed-but-not-yet-implemented.
  • The older @relayflows/core WorkflowBuilder engine — see writing-agent-relay-workflows and migrating-persona-to-relayflow in this repo.
Quick reference
Verb / fieldLanguageNotes
f.run(command) / type: deterministicbothshell command, implicit exit_code gate
f.llm(...) / type: llmbothbare model call, no workspace
f.agent(name, opts) / type: agentbothharnessed coding agent, returns {summary, artifacts}
f.human(question, {to})TS onlydurable approval; YAML has no equivalent yet
f.dispatch(flow, input)TS onlyhand off to a named child flow
f.done(reason) / —TS / kernelone of success | step_failed | canceled | budget_exceeded
options.cli / step.clibothper-call/step CLI override (TS: flows#310)
options.model / step.modelbothper-call/step model; no flow/project default
agent: <name> + agents: {...}YAML/JSON onlynamed cli/model pair, reused by selector
flows check <file>CLIpure validate + preflight, no daemon
flows run <file> [--input ...]CLIactually executes; .flow.ts needs --input
flows resume <run-id>CLIresume a parked/crashed run
Verified against
AgentWorkforce/flows@86a2ec2 (origin/main). Built packages/surface and packages/sdk from source in a clean worktree (published npm @relayflows/surface@2.0.8 is stale — it predates flows#310 and lacks cli/model on AgentOptions; local build was symlinked in instead), then ran the real CLI:
$ flows check hello.flow.yaml         # this skill's YAML example, cli/model added, flows.json models allowlist set
CHECK PASSED hello.flow.yaml            # exit 0

$ flows check hello.flow.ts            # this skill's TypeScript example
CHECK PASSED hello.flow.ts              # exit 0

$ flows check extract.flow.yaml        # this skill's output_contains example
CHECK PASSED extract.flow.yaml          # exit 0

$ flows check hello.flow.yaml           # same YAML, no flows.json anywhere
REFUSED [cli_unresolved] Step "greeter" has no CLI at step, flow, or project level. ...   # exit 2

$ flows check hello.flow.yaml           # step model not in flows.json's models[]
REFUSED [model_unknown] Step "greeter" declares model "claude-sonnet-4-6" ... not listed in project model registry ...   # exit 2

© AgentWorkforce, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/writing-relayflows of AgentWorkforce/relay.

Open the folder on GitHubat commit 734600d

Compare with similar skills

Writing Relayflows next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
MCP Server BuildershareAI-lab/learn-claude-code78k5 repos~1.2kAutomated safety check: PassMIT

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Works with

Questions about Writing Relayflows

What does Writing Relayflows do?

A skill your agent uses when authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk, the journal-based v2 engine — the CLI is flows, package versions 2.0.x) in TypeScript or YAML/JSON. Writing Relayflows is an agent skill from AgentWorkforce/relay.x) in TypeScript or YAML/JSON.

When should I use Writing Relayflows?

Writing Relayflows fits situations like: authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk; the journal-based v2 engine — the CLI is flows; package versions 2.0.x) in TypeScript.

How do I install Writing Relayflows in Claude Code?

Run `npx skills add AgentWorkforce/relay --skill writing-relayflows -a claude-code`. Or copy the skill folder (.agents/skills/writing-relayflows in AgentWorkforce/relay) into .claude/skills/writing-relayflows in your project. Claude Code loads it when a task matches its description.

How do I install Writing Relayflows in Codex?

Run `npx skills add AgentWorkforce/relay --skill writing-relayflows -a codex`. Or copy the skill folder (.agents/skills/writing-relayflows in AgentWorkforce/relay) into .agents/skills/writing-relayflows in your project. Codex loads it when a task matches its description.

Can I use Writing Relayflows in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AgentWorkforce/relay --skill writing-relayflows -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/writing-relayflows, .gemini/skills/writing-relayflows, .github/skills/writing-relayflows and .opencode/skills/writing-relayflows in your project.

What does Writing Relayflows need to run?

SKILL.md names no scripts, command-line tools or credentials: Writing Relayflows is instructions for the agent only.

Does Writing Relayflows access the network?

SKILL.md names 2 domains. As links in the text: github.com and agentrelay.com. This is read from the text; nothing was executed.

Is Writing Relayflows safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Writing Relayflows use?

Writing Relayflows is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Writing Relayflows use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Writing Relayflows?

Skills that share tags, products or a category with Writing Relayflows: MCP Server Builder (anthropics/skills, 180k stars), Web Artifacts Builder (anthropics/skills, 180k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Writing Relayflows?

AgentWorkforce (a GitHub organization) maintains it in AgentWorkforce/relay, which has 865 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 7, 2026.

Source: AgentWorkforce/relay on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.