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Pipeline Health

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davekilleen
pipeline-health

Analyze pipeline coverage and forecast confidence from configured sales definitions

Overview

Publisherdavekilleen
RepositoryDex
Skill namepipeline-health
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 Pipeline Health 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/sales/pipeline-health .claude/skills/pipeline-health
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pipeline Health 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 Pipeline Health 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 Pipeline Health 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.

Purpose

Produce a dated, evidence-backed view of pipeline coverage, velocity, conversion, concentration, and forecast confidence. The skill calculates what the supplied data supports and leaves policy judgments unknown when the team's definitions are absent.

Usage

  • /pipeline-health — review the current confirmed reporting period
  • /pipeline-health [period] — review a named month, quarter, or date range
  • /pipeline-health forecast — focus on explicit forecast categories and gaps

Evidence, authority, and recovery

Set a report as-of timestamp before reading data. Attach field provenance to every target, deal value, stage, probability, forecast category, date, benchmark, and calculated claim: source path or record ID, source event date, and read as-of time. A file modified time is only a discovery clue, never a substitute for a business event date.

  • Use only configured and confirmed stages, targets, probabilities, forecast categories, thresholds, and benchmarks for the requested period. Record the applicable configuration source and effective date. If one is absent, stale, contradictory, or unconfirmed, mark it Unknown; never invent a replacement or import a generic sales convention.
  • Missing differs from zero. A blank, unreadable, absent, or conflicting value is Unknown; zero is valid only when the authoritative source explicitly records zero.
  • A benchmark needs a source and date. Without one, show the factual metric and Assessment: Unknown — no sourced benchmark.
  • Show denominator coverage for every percentage and rate. Verify arithmetic from raw numerators, denominators, stage subtotals, and deal-level contributions.
  • Keep analysis read-only. A recommendation is not human authority. Preview any requested change, require explicit confirmation, then read back the result. If a write or read-back fails, report possible partial state, re-read the authoritative record, and wait for fresh human direction.

Method

1. Confirm scope and policy

Confirm:

  • reporting period, timezone, and as-of time;
  • authoritative deal source and included pipeline;
  • target and currency/units;
  • stage map and stage-entry event;
  • explicit forecast-category definitions;
  • probability source, if weighted pipeline is requested;
  • health, velocity, concentration, and conversion policies, if labels are requested.

Do not calculate across currencies or units without a sourced conversion rule. Do not merge duplicate records until identity has been reconciled.

2. Build the source ledger

For each discovered deal, record:

FieldRequired evidence
Identitystable deal ID and source
Valueamount, currency, source date
Stageconfigured stage and canonical stage-entry date
Forecastexplicit category from the authoritative source
Probabilityconfigured value and effective date
Close datedated source or Unknown
Activitycanonical event date and source

Keep an Unchecked deals section for unreadable, duplicate, or incomplete rows. Do not silently remove them from the apparent pipeline.

3. Normalize without guessing

  • Map a stage only through the confirmed stage configuration.
  • Preserve contradictions side by side; do not choose the convenient value.
  • Exclude unknown values from value totals and disclose the excluded count.
  • Exclude deals with unknown probability from weighted totals.
  • Keep explicitly recorded zero values in the eligible cohort.
  • Use the canonical stage-entry event for velocity. If absent, velocity is unknown for that deal.

4. Calculate supported metrics

  • Coverage ratio: known eligible pipeline value / confirmed target. This is a factual ratio, not a health label. Apply a label only when a configured or cited policy defines one.
  • Weighted pipeline: sum of each known value multiplied by its configured, confirmed probability. Show included and excluded deal counts.
  • Stage conversion: confirmed transitions / eligible prior-stage cohort for the same sourced period. State the cohort and exclusions.
  • Velocity: elapsed time from canonical stage-entry events. Compare against a configured threshold or a clearly described historical distribution; otherwise show age without calling it slow.
  • Concentration: show deal-level shares and the chosen cohort. Label a concentration risk only when a sourced policy defines that judgment.
  • Forecast totals: use explicit source categories such as commit or best case. Never infer a forecast category from stage or probability.

Cross-check total pipeline against stage subtotals, percentage sums against eligible denominators, and every gap sign against target - forecast.

5. Separate facts, judgments, and actions

For each finding, show:

  1. observed metric and source coverage;
  2. configured policy or benchmark used for any judgment;
  3. unknowns and contradictory evidence;
  4. recommended human action and why it follows;
  5. evidence that would change the conclusion.

Never invent causes for a low conversion rate, silence from a buyer, or a likely close. Offer questions to investigate instead.

Output contract

markdown
# Pipeline health

**Period:** [confirmed range and timezone]
**As of:** [timestamp]
**Target:** [value, currency, source/date or Unknown]
**Deals discovered / checked / unchecked:** [N / n / u]

## Forecast
| Category | Amount | Eligible coverage | Definition source |
|---|---:|---:|---|
| Commit | [amount or Unknown] | [n/N] | [source/date] |
| Best case | [amount or Unknown] | [n/N] | [source/date] |
| Weighted pipeline | [amount or Unknown] | [n/N] | [probability source/date] |

## Coverage and flow
| Metric | Result | Numerator / denominator | Assessment policy |
|---|---:|---|---|
| Coverage | [ratio or Unknown] | [raw values] | [source/date or Unknown] |
| Conversion | [rate or Unknown] | [n/N and period] | [benchmark or Unknown] |
| Velocity | [distribution or Unknown] | [eligible n/N] | [policy or Unknown] |

## Risks and unknowns
- [Evidence-backed risk, or Unknown with missing evidence]
- [Contradiction with both sources]
- [Unchecked deal and reason]

## Recommended questions or actions
1. [Action tied to a finding; no write performed]

Every populated value must trace to the source ledger. Placeholders are output shape, not assumptions.

Controlled changes

If the user asks to update a deal, target, probability, or stage configuration:

  1. identify the authoritative target and current bytes/record;
  2. show the exact before/after diff or API payload;
  3. name downstream metrics that will change;
  4. get explicit confirmation from the authorized human;
  5. perform only that confirmed mutation;
  6. read back the saved result and recalculate from the authoritative source.

A timeout, mismatch, or partial response is a failed change, never success.

Frequently asked questions

What does the Pipeline Health AI skill do?

Analyze pipeline coverage and forecast confidence from configured sales definitions

Why use Pipeline Health on TypingMind?

Because you install it once and use it with any model. Pipeline Health 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 Pipeline Health 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/sales/pipeline-health. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pipeline Health?

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 Pipeline Health?

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

Is the Pipeline Health 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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