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Conversation state human handoff

Skill gaelic-ghost/socket/plugins/messaging-collaboration-skills/skills/conversation-state-human-handoff

The Source for macOS Agent Workflows

Install
npx -y skills add gaelic-ghost/socket --skill conversation-state-human-handoff

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Plan conversation identity, state, consent, escalation, transcript, and human-handoff behavior for bots and business messaging agents.

SKILL.md

1.6 KB, 268 tokens by cl100k_base, as published. Nobody here has run it

Conversation State And Human Handoff

Purpose

Design a narrow, explainable conversation boundary. Platforms identify people, installations, channels, and conversations differently, so normalize only the application facts needed for the product; do not erase platform identity or policy distinctions.

Workflow

  1. Identify the platform-native sender, conversation, installation or tenant, message, and consent identifiers.
  2. State which identifiers are durable, which can change, and which are sensitive.
  3. Define the minimal state required for the user experience: task progress, user preference, handoff status, and delivery context.
  4. Specify an explicit escalation path: trigger, acknowledgement, operator queue or destination, visible transition, return-to-automation rule, and unavailable-hours behavior.
  5. Apply platform and product consent/retention rules before storing transcripts, media, model inputs, or contact data.
  6. Test interruption, duplicate delivery, human takeover, failed escalation, opt-out, deletion, and resumed conversation behavior.

Guards

  • Do not map identities across platforms as though they represent the same authenticated person without an explicit account-linking flow.
  • Do not let an AI response conceal that a human has joined or left when the platform has a representative-state mechanism.
  • Do not introduce repositories, managers, or state mirrors into an app without a concrete ownership need.

Gives 0 of the 12 instructions most agent orchestration skills give in 268 tokens

Counted across 742 of the 995 authors here whose files we hold, read 2026-08-06

  • run the full test suite after integrating changesin 53 of 742, across 20 files
  • reference existing artifacts by path or URLin 52 of 742, across 22 files
  • dispatch one agent per independent problem domainin 50 of 742, across 17 files
  • verify fixes do not conflictin 45 of 742, across 13 files
  • include a suggested skills section in the documentin 45 of 742, across 15 files
  • redact sensitive informationin 41 of 742, across 11 files
  • save to the temporary directory of the operating systemin 39 of 742, across 9 files
  • tailor the document to user-provided focus argumentsin 39 of 742, across 9 files
  • spot check agent changes for systematic errorsin 34 of 742, across 7 files
  • write a handoff document summarising the current conversationin 31 of 742, across 6 files
  • assign each agent a specific scopein 23 of 742, across 8 files
  • provide specific scope and clear goalin 23 of 742, across 5 files

Said here and by no other author read

  • Identify platform-native sender and conversation identifiers
  • State which identifiers are durable, changeable, or sensitive
  • Define minimal state required for the user experience
  • Specify an explicit escalation path
  • Apply consent and retention rules before storing data
  • Test interruption and duplicate delivery behavior

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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