AgentWorkforce

Use when you are a registered relay agent (a spawned worker, or a lead that called register_agent) coordinating with peers in real time over current Agent Relay MCP tools - messaging, channels, threads, reactions, search, inbox, actions, and worker spawn/release. For role selection and orchestrator startup instructions, use https://agentrelay.com/skill and the orchestrating-agent-relay skill.

Use when building multi-agent workflows with @relayflows/core. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, repairable verification gates, evidence-based completion, mandatory Claude-then-Codex fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Use when building multi-agent workflows with @relayflows/core. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, repairable verification gates, evidence-based completion, mandatory Claude-then-Codex fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Use when you need Codex to coordinate multiple agents through Agent Relay for peer-to-peer messaging, lead/worker handoffs, or shared status tracking across sub-agents and terminals.

This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.

Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.

Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate workflow/YAML examples.

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, mandatory sequential Claude-then-Codex fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when creating, updating, or reviewing a Workforce cloud persona (`persona.ts` + `agent.ts`) for the current deploy/runtime shape. Covers cloud, useSubscription, integrations with scope mounting/enabledByInput gating/adapter config passthrough, inputs, memory, sandbox modes, onEvent, runtime fields, capabilities, defineAgent triggers/schedules/watch/team-dispatcher launch, provider IO via @relayfile/relay-helpers, multi-transport delivery, ctx.relay messaging, and the deploy flow.

Use when you are a registered relay agent (a spawned worker, or a lead that called register_agent) coordinating with peers in real time over current Agent Relay MCP tools - messaging, channels, threads, reactions, search, inbox, actions, and worker spawn/release. For role selection and orchestrator startup instructions, use https://agentrelay.com/skill and the orchestrating-agent-relay skill.

The canonical way to run agent-relay - self-bootstrap the local broker and autonomously spawn, monitor, and coordinate a team of worker agents without human intervention. Covers infrastructure startup, agent spawning, lifecycle monitoring, message-based reading via the relay MCP, and team coordination.

Use when creating, editing, or validating an Agent Relay Factory factory.config.json file, including repo routing, Linear state/team settings, GitHub issue ingestion, live mode, babysitter options, and Relayflows dispatch wiring boundaries.

Use when adding webhook events to make sure integrations properly register the webhook events they carry

Use when an agent or human needs to set up relayfile end-to-end so agents can read and write provider files through a local mount. Covers `relayfile setup`, dynamic integration discovery with `relayfile integration available/search`, Nango and Composio backend selection, Atlassian site selection and metadata, cloud login, OAuth/connect flows, mount verification, `RELAYFILE_LOCAL_DIR` handoff, writeback status and retry commands, and key May 2026 cloud-mount gotchas.

Use when an agent is exploring a relayfile mount for the first time or trying to locate a specific resource (Notion page, Linear issue, Slack channel, GitHub PR). Tells the agent to start with `<mount>/LAYOUT.md` and `<provider>/LAYOUT.md` rather than guessing paths from memory, and to use the `by-title/`, `by-id/`, `by-name/`, `by-edited/<date>/`, `by-state/` alias subtrees instead of recursively grepping. Filename convention is `<identifier>__<uuid>` (ticket number / slug first so listings are scannable). NOT for activity-summary questions, which should use the `activity-summary` skill instead.

Run a fan-out relay pattern for independent subtasks. Use when the same kind of work can be split across files, components, services, or targets with minimal coordination.

Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.

Use when creating, updating, or reviewing a Workforce cloud persona (`persona.json`/`persona.ts` + `agent.ts`) for the current deploy/runtime shape. Covers `cloud`, `useSubscription`, integrations with scope mounting and adapter config passthrough, inputs, memory, sandbox modes, `onEvent`, top-level runtime fields, `defineAgent(...)` triggers/schedules/watch/team-dispatcher launch, provider IO via `@relayfile/relay-helpers`, production-correctness traps, vendored examples, and deploy flow. Use for requests like “create a cloud persona”, “write a deployable workforce persona”, “add integrations to a persona”, “configure GitHub materialization for a persona”, “review a workforce persona”, or “author the agent.ts handler for a workforce persona”.

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, review-depth fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with relay broker-sdk. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, Relayfile-backed human assistance, Slack answer injection, integration subscriptions, waitFor gates, repairable verification, review-depth fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, review-depth fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with relay broker-sdk. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, Relayfile-backed human assistance, Slack answer injection, integration subscriptions, waitFor gates, repairable verification, review-depth fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Create consistent, memorable visual graphics for AgentWorkforce agents in the agents repo. Use when asked to generate, design, refresh, or wire README graphics, avatars, badges, cards, banners, or visual identity assets for folders such as granola, hn-monitor, linear, repo-hygiene, review, spotify-releases, and vendor-monitor.

Use before auto-merging any PR in an autonomous run, and between consecutive merges that touch overlapping code. Covers the per-PR auto-merge bar (live CI verification, substantive review by area, bot-finding stale-vs-actionable triage) and the cross-PR composition discipline (serialize through green main, rebase + re-CI between merges, dormant-safety audit, force-reset over half-merged commits).

Use at the start of every autonomous, multi-PR, cutover-class delegated run. Authors the binding contract between operator and agent — the gates, the flip mechanism, the rollback triggers, the standing constraints, and the explicit escalate-to-human conditions — and surfaces it to the operator for explicit grant of (a) auto-merge authority, (b) flip-the-switch authority, (c) swarm-blockers authority. No autonomous work begins until the contract is acknowledged.

Use when designing or executing a cutover-class change (migration, ingestion path swap, provider relink, flag enablement). Encodes the dark-launch + single-switch flip pattern, the refusal to flip on amber, and the pre-authorized rollback procedure — the canonical way to make irreversible-feeling infra changes reversible-feeling.

Use when a fix has failed two consecutive times for the same symptom. Encodes the discipline that the third action must be a temporary diagnostic (a /_diag endpoint, an enriched structured log, a runtime-captured snapshot) rather than another fix attempt. Also covers the discipline for removing those diagnostics once the real root cause is in.

Use during an autonomous run to (a) dispatch supporting codex-impl + claude-review agent pairs against hard blockers when the orchestrator cannot make progress alone, and (b) maintain the live RED / GREEN gate scoreboard the orchestrator reads to authorize the flip. Encodes the file-based reporting convention that keeps the channel readable.

Use when a single gate would require deep proof across a large set (44 models × 10 providers; 60+ resources; every region; every plan tier). Splits the acceptance into tier-1 (deep proof on high-volume / high-fidelity slice) and tier-2 (smoke proof on low-volume tail), documents the explicit accepted trade-off, and preserves safety through dormant-default + per-item enable + rollback.

Use when inbound Slack content (channel messages, thread replies, or DMs) doesn't read down to local disk, or an integration-event preview says "Message unavailable" though the bytes may be on disk. Covers reading mount sync state, write-only-vs-mirror mounts, the bare-vs-suffixed channel-id drop, the preview two-shape gap, mount wedges, and the relayfile#262 backfill trap.

Use when an outbound Slack writeback (channel post, thread reply, or DM) silently fails to deliver — no error, no dead-letter. Covers the writeback pipeline, the relayfile ops-API getOp recipe to read the persisted lastError, where the Slack error actually surfaces (NOT the consumer logs), the missing_scope/im:write 3-place fix, cf-vs-bridge dispatch, and duplicate/silent-send pitfalls.

Use when verifying Relayfile provider integrations end-to-end against a real workspace, including auth, OAuth connect, sync, file-tree shape, discovery materialization, outbound writeback, inbound webhook checks, evidence capture, and issue filing.

Use when investigating Relayfile cloud, mount daemon, provider sync, discovery, writeback, digest generation, token handling, WorkspaceDO behavior, or architecture during integration verification and debugging.

Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with the relay broker-sdk - covers conversation-shape vs pipeline-shape coordination, repairable/reliable workflow gates, the WorkflowBuilder API, DAG step dependencies, agent definitions, step output chaining via {{steps.X.output}}, verification gates, evidence-based completion, owner decisions, dedicated channels, dynamic channel management (subscribe/unsubscribe/mute/unmute), swarm patterns, chat-native coordination recipes (Q/A, broadcast-ack, peer review, standup, hand-off), error handling, event listeners, step sizing rules, authoring best practices, and the lead+workers team pattern for complex steps

Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with the relay broker-sdk - covers conversation-shape vs pipeline-shape coordination, repairable/reliable workflow gates, the WorkflowBuilder API, DAG step dependencies, agent definitions, step output chaining via {{steps.X.output}}, verification gates, evidence-based completion, owner decisions, dedicated channels, dynamic channel management (subscribe/unsubscribe/mute/unmute), swarm patterns, chat-native coordination recipes (Q/A, broadcast-ack, peer review, standup, hand-off), error handling, event listeners, step sizing rules, authoring best practices, and the lead+workers team pattern for complex steps

Use when coordinating multiple AI agents and need to pick the right orchestration pattern - covers 10 patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) with decision framework and reflection protocol

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with the relay broker-sdk - covers the WorkflowBuilder API, DAG step dependencies, agent definitions, step output chaining via {{steps.X.output}}, verification gates, evidence-based completion, owner decisions, dedicated channels, dynamic channel management (subscribe/unsubscribe/mute/unmute), swarm patterns, error handling, event listeners, step sizing rules, authoring best practices, and the lead+workers team pattern for complex steps

Use when coordinating multiple AI agents and need to pick the right orchestration pattern - covers 10 patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) with decision framework and reflection protocol

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with the relay broker-sdk - covers the WorkflowBuilder API, DAG step dependencies, agent definitions, step output chaining via {{steps.X.output}}, verification gates, evidence-based completion, owner decisions, dedicated channels, dynamic channel management (subscribe/unsubscribe/mute/unmute), swarm patterns, error handling, event listeners, step sizing rules, authoring best practices, and the lead+workers team pattern for complex steps

Use when programmatically creating or managing agent trajectories in TypeScript - provides TrajectoryClient for persistent storage and TrajectoryBuilder for in-memory construction

Best practices for structuring prpm.json package manifests with required fields, tags, organization, multi-package management, enhanced file format, eager/lazy activation, and conversion hints

Use when an agent needs to self-bootstrap agent-relay and autonomously manage a team of workers - covers infrastructure startup, agent spawning, lifecycle monitoring, and team coordination without human intervention

Use when an agent needs to self-bootstrap agent-relay and autonomously manage a team of workers - covers infrastructure startup, agent spawning, lifecycle monitoring, and team coordination without human intervention

Use when an agent needs to self-bootstrap agent-relay and autonomously manage a team of workers - covers infrastructure startup, agent spawning, lifecycle monitoring, and team coordination without human intervention

Use when coordinating multiple AI agents in real-time - provides inter-agent messaging via MCP tools

Use when publishing an MCP server to Smithery and need to maximize the quality score - covers scoring categories, tool metadata requirements, deploy reliability, and known external deployment limitations

Best practices for structuring prpm.json package manifests with required fields, tags, organization, multi-package management, enhanced file format, eager/lazy activation, and conversion hints

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, mandatory sequential Claude-then-Codex fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with relay broker-sdk. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, repairable verification gates, evidence-based completion, mandatory Claude-then-Codex fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.

Use when writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, mandatory sequential Claude-then-Codex fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

Use when building multi-agent workflows with relay broker-sdk. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, repairable verification gates, evidence-based completion, mandatory Claude-then-Codex fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Use when building multi-agent workflows with relay broker-sdk. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, repairable verification gates, evidence-based completion, review-depth fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Use when building multi-agent workflows with relay broker-sdk. Covers conversation vs pipeline coordination, WorkflowBuilder/DAG steps, agents, {{steps.X.output}} chaining, repairable verification gates, evidence-based completion, review-depth fresh-eyes review/fix loops with test hardening, channels, chat-native recipes, error handling, event listeners, step sizing, lead+workers teams, and parallel waves.

Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.

Use when building multi-agent workflows with the relay broker-sdk - covers conversation-shape vs pipeline-shape coordination, the WorkflowBuilder API, DAG step dependencies, agent definitions, step output chaining via {{steps.X.output}}, verification gates, evidence-based completion, owner decisions, dedicated channels, dynamic channel management (subscribe/unsubscribe/mute/unmute), swarm patterns, chat-native coordination recipes (Q/A, broadcast-ack, peer review, standup, hand-off), error handling, event listeners, step sizing rules, authoring best practices, and the lead+workers team pattern for complex steps

Use when building multi-agent workflows with the relay broker-sdk - covers conversation-shape vs pipeline-shape coordination, the WorkflowBuilder API, DAG step dependencies, agent definitions, step output chaining via {{steps.X.output}}, verification gates, evidence-based completion, owner decisions, dedicated channels, dynamic channel management (subscribe/unsubscribe/mute/unmute), swarm patterns, chat-native coordination recipes (Q/A, broadcast-ack, peer review, standup, hand-off), error handling, event listeners, step sizing rules, authoring best practices, and the lead+workers team pattern for complex steps

Use when the assistant has a workspace VFS (via @agent-assistant/harness workspace_* tools) backed by RelayFile. Covers path conventions per provider and the cite-your-source discipline. Provider-specific rows are populated at runtime from /_conventions/*.json written by cataloging agents; hand-written rows below are the fallback.

Strategic content production system — writer context packet, bookmarkability rubric, avoid-slop patterns, and viral postmortem. Load when planning, drafting, scoring, or reviewing any post.

Essay authoring patterns for the Proactive Agents site — Scene scrollytelling, custom SVG figures, Callout/PullQuote/Sidenote usage, embedded media, and a pre-publish voice checklist. Load when writing or editing any MDX essay.

Run the Pear integration mount eval suite. Use when asked to run evals, check writeback coverage, validate variant pass rates, or confirm that prescriptive/full-inject work for claude or opencode CLIs. Applies to pear-sdk-bump/ and relay/packages/evals/.