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Contact Consent Review

Organization
runxhq
contact-consent-review

Decide and record conservative contact-consent transitions from bounded engagement, bounce, and consent evidence before any send.

Overview

Publisherrunxhq
Repositoryrunx
Skill namecontact-consent-review
Stars
105
Forks
109
Bundled files
5
LicenseApache-2.0
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.

  • 5 bundled files

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

  • Open source

    Published by runxhq on GitHub. Read the source before you install it.

Installation

Install the Contact Consent Review 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/runxhq/runx/tree/main/skills/contact-consent-review
  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/runxhq/runx.git /tmp/runx
mkdir -p .claude/skills
cp -r /tmp/runx/skills/contact-consent-review .claude/skills/contact-consent-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Contact Consent Review 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 Contact Consent Review 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 Contact Consent Review 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.

Contact Consent Review

Use this skill after collecting current contact evidence and before preparing a campaign. It decides whether a contact remains eligible, needs re-permission, must be suppressed, or needs human review. When policy justifies a state transition, it records that decision in the operator's consent ledger with optimistic concurrency and verifies the exact event through a second read.

This skill never sends a message and never mutates a mailing provider. A later message-send run must read the current consent state again at delivery time. The ledger records the operator's policy decision; it does not replace provider unsubscribe or bounce data.

Operating model

The caller supplies one bounded engagement observation, the current consent observation, and the policy threshold that applies to the contact. The evidence must be marked read and versioned to the same ledger head that the runner reads through the store's projection.read. Missing, stale, ambiguous, or conflicting evidence produces human_review without a write.

The deterministic decision order is conservative:

  1. An unsubscribe marker stops automation.
  2. An existing suppression is preserved; age alone can never relax it.
  3. Verified hard-bounce evidence suppresses when policy permits that automatic action, otherwise it stops for review.
  4. A subscribed contact whose last engagement exceeds the decay threshold is moved to re_permission.
  5. A clean, recent subscribed contact returns verify without writing.

Only re_permission and suppress can create transitions. The append uses the observed ledger version and the caller's stable idempotency key. Readback must match the append status, source identity, new version, event reference, event digest, and projection digest before the result reports a recorded transition. No-write decisions also perform a second read and require the projection to remain unchanged.

Authority and finality

The runner requests runx:data:read and, only for an admitted transition, runx:data:append. These scopes authorize a bounded consent-ledger operation; they do not authorize delivery or changes to a CRM or mailing provider. The data-source binding owns storage and credentials.

A sealed result proves the ledger reads and any exact recorded transition. It does not prove provider state, re-subscription, campaign approval, or delivery. Every result therefore keeps downstream_send.status at not_run and names message-send as the separate delivery boundary.

Decisions and recovery

  • verify: current evidence supports no transition. Nothing is appended.
  • re_permission: engagement has decayed past policy and a subscribed contact must regain permission before sending. The transition is recorded once.
  • suppress: hard-bounce evidence requires suppression, or an existing suppression is preserved. A write occurs only when state actually changes.
  • human_review: evidence or policy cannot safely support automation. Nothing is appended.

If the ledger version changes before the decision, run again with a fresh read and fresh evidence. Reuse an idempotency key only for the identical transition. The runner deliberately makes no claim that a post-commit retry can recover from the old expected version; inspect the receipt and current ledger before deciding whether another operation is needed.

Inputs and result

Provide the logical data source, consent-ledger resource, contact aggregate, observed version, stable transition key, bounded engagement counts and recency, bounce policy, and current consent evidence. Counts must be non-negative and the policy threshold must be between 1 and 3,650 days.

The result preserves the decision and reason, the observed consent state, the readback-bound transition identity when one was written, a human escalation only when review is required, and the untouched downstream send boundary.

Agent rules

  • Never invent engagement, bounce, consent, or version evidence.
  • Never relax suppression from contact age alone.
  • Never re-permission an unsubscribed contact automatically.
  • Never describe an internal ledger append as a provider update.
  • Never dispatch, send, or claim delivery from this result.

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 Contact Consent Review AI skill do?

Decide and record conservative contact-consent transitions from bounded engagement, bounce, and consent evidence before any send.

Why use Contact Consent Review on TypingMind?

Because you install it once and use it with any model. Contact Consent Review 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 Contact Consent Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/runxhq/runx/tree/main/skills/contact-consent-review. 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 Contact Consent Review?

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 Contact Consent Review?

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

Is the Contact Consent Review AI skill free?

Yes. It is published on GitHub by runxhq under the Apache-2.0 license. 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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