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Writing Workspace Signals

Organization
friday-platform
writing-workspace-signals

Authors Friday workspace signals with correct provider configs, payload schemas, and runtime wiring. Use when creating or editing signals in workspace.yml; when a signal needs to accept user input from the Run dialog; or when signal validation or runtime dispatch fails.

Overview

Publisherfriday-platform
Repositoryfriday-studio
Skill namewriting-workspace-signals
Stars
102
Forks
5
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by friday-platform on GitHub. Read the source before you install it.

Installation

Install the Writing Workspace Signals 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/friday-platform/friday-studio/tree/main/packages/system/skills/writing-workspace-signals
  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/friday-platform/friday-studio.git /tmp/friday-studio
mkdir -p .claude/skills
cp -r /tmp/friday-studio/packages/system/skills/writing-workspace-signals .claude/skills/writing-workspace-signals
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Writing Workspace Signals 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 Writing Workspace Signals 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 Writing Workspace Signals 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.

Writing workspace signals

Checklist

  • description present (required)
  • provider matches exact enum: http, schedule, system, fs-watch, slack, telegram, whatsapp, discord, teams
  • Provider config present and valid
  • HTTP signals with params: schema declared with type: object, properties, required
  • HTTP config.path unique across workspace
  • Schedule config.schedule valid cron
  • Signal referenced by at least one job trigger (or dead_signal warning)
  • No id inside inline job fsm: — runtime injects from job name

Two foot-guns

Schemaless signals with payload params

No schema → Run dialog renders no input fields → payload arrives empty. Job gets {} instead of the params it expects.

Wrong:

yaml
signals:
  draft-reply:
    description: "Draft a reply"
    provider: http
    config:
      path: /draft-reply

Right:

yaml
signals:
  draft-reply:
    description: "Draft a reply to an email"
    provider: http
    config:
      path: /draft-reply
    schema:
      type: object
      properties:
        message_id:
          type: string
        instructions:
          type: string
      required:
        - message_id

id inside inline FSM blocks

Runtime auto-injects id from job.name. Adding your own risks mismatch.

Wrong:

yaml
jobs:
  review-inbox:
    fsm:
      id: review-inbox-job   # don't

Right:

yaml
jobs:
  review-inbox:
    fsm:
      initial: idle

Wiring HTTP signals to external systems

A provider: http signal exposes a URL but does NOT tell upstream systems (Bitbucket / GitHub / Jira) to call it. The user still needs to register the webhook on the upstream side. The /hook/raw/{workspaceId}/{signalId} URL pattern, the /status discovery flow, signal-schema requirements, and the tunnel-level error catalog all live in [[wiring-external-webhooks]] — load that skill any time the user asks how to "set up the webhook", "wire Bitbucket/GitHub/Jira", or why /status is unreachable. The HTTP signal in workspace.yml is necessary but not sufficient.

Templates

HTTP trigger, no payload

yaml
signals:
  triage-now:
    description: "Triage unread emails immediately"
    provider: http
    config:
      path: /triage-now

HTTP trigger with payload

yaml
signals:
  draft-reply:
    description: "Draft a reply to a specific email"
    provider: http
    config:
      path: /draft-reply
    schema:
      type: object
      properties:
        message_id:
          type: string
        tone:
          type: string
      required:
        - message_id

Cron trigger

yaml
signals:
  daily-scan:
    description: "Triage inbox every morning at 9am"
    provider: schedule
    config:
      schedule: "0 9 * * *"
      timezone: "America/Los_Angeles"
      # Optional: what to do with firings the daemon was down for.
      # Defaults to manual — surfaces a pending row in /schedules,
      # operator decides. All non-skip policies are bounded by
      # missedWindow (default 24h) so a long outage can't produce
      # an unbounded burst.
      onMissed: manual        # default; other options: skip | coalesce | catchup
      missedWindow: 24h       # optional; default 24h

onMissed policies:

  • manual (default) — surface the missed slot on the /schedules UI as a pending row; do not auto-fire. The operator clicks "Fire now" or "Dismiss". Right for jobs with expensive or visible side effects (paid API calls, email blasts, Slack posts) where you want oversight without auto-replay. Default since 2026-05-03 — silent drops surprised users.
  • skip — drop missed firings entirely. Pick this when missing slots is a non-event because the next scheduled fire will pick up where it left off (e.g., "fetch latest prices" — recency is implicit in the next fire).
  • coalesce — fire once now to represent every missed slot inside missedWindow. Payload carries policy: "coalesce", missedCount, firstMissedAt. Right for "did this happen recently?" jobs (digests, syncs) where one make-up call covers the gap.
  • catchup — fire each missed slot in chronological order, one signal per slot, payload tagged policy: "catchup". Right for "every tick must run" jobs (rate-limit accruals, time-series ingest, slot-numbered exports). Use when missing a slot is incorrect, not just late.

missedWindow (Duration: s/m/h, default 24h) caps the catch-up window for every policy. A daemon down for a week with catchup on an hourly cron only fires the slots inside the window — never all 168.

Missed-schedule events surface on the playground /schedules page under "Missed schedules" and persist in the JetStream WORKSPACE_EVENTS stream for 30 days. manual events that haven't been fired/dismissed show a pending badge + action buttons.

Concurrency policy

concurrency controls what happens when a new envelope for the same (workspace, signal) arrives while a previous cascade is still running. Orthogonal to onMissed (which is the downtime catch-up policy). Lives on every signal provider, not just schedule.

yaml
signals:
  send-alert:
    provider: schedule
    config:
      schedule: "*/5 * * * *"
      concurrency: skip   # default; other options: queue | concurrent | replace

Policies:

  • skip (default) — drop the new envelope if a cascade is in flight for this (workspace, signal). Right for cron jobs where the next tick will run anyway and you don't want pile-up if cascades exceed the schedule.
  • queue — serialize: chain the new envelope after the current one in arrival order. Right when every tick must eventually run; risks unbounded backlog on slow cascades.
  • concurrent — no overlap guard, full parallelism. Right for stateless / idempotent jobs that benefit from parallel runs (independent fetches, fan-out scrapes).
  • replace — abort the in-flight cascade and start the new one. Right for "freshest input wins" workloads (cancel-in-flight semantics for non-chat signals).

For HTTP-trigger correlated callers, skip and replace publish ok=false on the response subject immediately so callers don't wait out their HTTP timeout. queue blocks the caller until the in-flight cascade settles. concurrent returns each cascade's own response.

System trigger

yaml
signals:
  workspace-ready:
    description: "Fired when workspace runtime finishes init"
    provider: system

Validation error decoder

CodeFix
invalid_type on descriptionAdd description field
invalid_type on config.pathHTTP signals need config.path (string, unique)
invalid_type on config.scheduleSchedule signals need config.schedule (valid cron)
http_path_collisionMake each HTTP path unique
cron_parse_failedFix cron; use crontab.guru
dead_signalAdd a job trigger or delete the signal

Runtime anti-patterns

  • Schema not type: object. Run dialog reads properties. Bare string schema or missing properties = no fields rendered, empty payload. Symptom: dialog says "trigger immediately" when it should ask for inputs. Fix: add type: object, properties, required.
  • Payload type mismatch. Schema says string, caller sends number → signal fails with 500, session never starts. Fix: prefer string for IDs even if they look numeric.
  • HTTP path collision. Two signals same config.path → first one wins, second unreachable. Fix: unique paths per workspace.
  • Missing timezone on cron. Defaults UTC. 9am PST becomes 5pm. Fix: explicit timezone.

Order of declaration

Signals last — nothing depends on them. But declare schema before you test the signal. A signal without schema may pass validate_workspace yet fail at runtime when the Run dialog sends {} to a job expecting fields.

Assets

  • assets/minimal-http-signal.yml — trigger, no payload
  • assets/http-signal-with-schema.yml — trigger with typed form fields
  • assets/schedule-signal.yml — cron trigger with timezone

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Writing Workspace Signals AI skill do?

Authors Friday workspace signals with correct provider configs, payload schemas, and runtime wiring. Use when creating or editing signals in workspace.yml; when a signal needs to accept user input from the Run dialog; or when signal validation or runtime dispatch fails.

Why use Writing Workspace Signals on TypingMind?

Because you install it once and use it with any model. Writing Workspace Signals 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 Writing Workspace Signals in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/friday-platform/friday-studio/tree/main/packages/system/skills/writing-workspace-signals. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Writing Workspace Signals?

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 Writing Workspace Signals?

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

Is the Writing Workspace Signals AI skill free?

It is published on GitHub by friday-platform. Check the repository for licensing terms. 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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