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Health Score

Community
davekilleen
health-score

Use when reviewing customer-account health with a configured scoring rubric and dated inputs, or when reporting why a portfolio cannot yet be scored. Not for finding expansion opportunities; use expansion-opportunities.

Overview

Publisherdavekilleen
RepositoryDex
Skill namehealth-score
Stars
481
Forks
130
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Health Score 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.
  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/davekilleen/Dex.git /tmp/Dex
mkdir -p .claude/skills
cp -r /tmp/Dex/packages/dex-agent-plugin/skills/_available/customer-success/health-score .claude/skills/health-score
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Health Score 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 Health Score 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 Health Score 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.

When to use

Use for a named account segment or portfolio health review when the user supplies, or the account system contains, a configured scoring rubric and dated inputs. If the rubric or required inputs are absent, still use this skill to return not scored and a review of signals only.

Do not use this skill to infer churn from silence, replace customer-success judgment, assign a health rating without its rubric, update CRM records, or contact a customer. Not for expansion qualification, renewal pricing, or commercial commitments.

Inputs and source discipline

  1. Identify the account scope and as-of date. Require a configured scoring rubric with a named version/effective date, factors, weights, thresholds, freshness window, and missing-data rule; record its source, source date, date checked, and confidence. If it is missing, ambiguous, or stale, the result is not scored.
  2. For each factor, capture a dated input, source, source date, date checked, unit if relevant, and freshness relative to the rubric. Prefer system records, dated customer outcomes, support events, and explicit account notes over assumptions. Preserve unknown, stale, and contradictory inputs rather than filling them from silence.
  3. Treat no recent contact as an absence of evidence, not evidence of churn or risk. A silence signal may be listed for human review only when its date and source are clear.

Method

  1. Work read-only. Validate the rubric before reading scores: confirm factors, weights, thresholds, effective date, and missing-data behavior are complete and internally consistent.
  2. Match each required factor to a dated input within the configured freshness window. Apply a partial-data rule only when the configured rubric explicitly permits it. Otherwise any required unknown, stale, or contradictory factor makes that account not scored; unknown is never red or green and must not be coerced to a favorable or unfavorable value.
  3. When all required inputs are valid, calculate the score exactly as configured and preserve the rubric version with the result. Do not substitute an intuitive threshold or infer a score from engagement, silence, sentiment, renewal date, or a single event.
  4. Produce a portfolio distribution only over accounts with valid scores and a stated denominator. Keep unscored accounts and their review signals in a separate list; recommendations remain for human review.

Truth and uncertainty rules

Use observed for a dated input directly supported by a source, inferred for a review interpretation, unknown for missing or insufficient data, stale for data outside the rubric's freshness, and contradictory when sources disagree. State confidence and the rubric basis. Never infer churn from silence. Never invent dates, metrics, owners, intent, money, percentages, causes, status, or evidence. Recommendations are not human decisions.

Output contract

Return a review containing:

  • account scope, rubric source/version/effective date, as-of date, freshness rule, and sources;
  • not scored at portfolio or account level whenever the rubric or required inputs are absent;
  • scores and red/yellow/green labels only when the configured rubric and dated inputs support them;
  • for each account, factor inputs with source/date, freshness, confidence, unknowns, stale data, contradictions, and the reason for any unscored result;
  • a distribution with an explicit eligible-account denominator, or no distribution when unscored; and
  • review signals and non-binding outreach recommendations clearly separate from score evidence.

Safety and write boundaries

Remain read-only by default. Do not update health fields, CRM, account notes, tasks, or customer communications. If a write, export, shared artifact, outreach, or other action is requested, preview the exact target, content, audience, and side effects; redact secrets or unapproved personal/confidential content; wait for explicit confirm from the authorized human owner; then perform only that approved action. A score or recommendation is not human authorization.

Verification and recovery

Read back the rubric, every scored input, formula, and output label. Recalculate each score, reconcile scored-account counts and distribution totals to the eligible denominator, and check source dates, freshness, units, and as-of scope; fail closed on any mismatch. If rubric or data retrieval fails, preserve the review, return not scored, record the failure and affected signals, and rerun after refresh. Never silently turn unknown into red or green.

Frequently asked questions

What does the Health Score AI skill do?

Use when reviewing customer-account health with a configured scoring rubric and dated inputs, or when reporting why a portfolio cannot yet be scored. Not for finding expansion opportunities; use expansion-opportunities.

Why use Health Score on TypingMind?

Because you install it once and use it with any model. Health Score 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 Health Score in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/davekilleen/Dex/tree/main/packages/dex-agent-plugin/skills/_available/customer-success/health-score. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Health Score?

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 Health Score?

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

Is the Health Score AI skill free?

It is published on GitHub by davekilleen. 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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