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Pestel Delta Monitor

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deanpeters
pestel-delta-monitor

Quarterly re-scan of a prior PESTEL analysis. Use when checking which macro factors moved, which assumptions broke, and what's new — turning PESTEL from a workshop artifact into a radar.

Overview

Publisherdeanpeters
RepositoryProduct-Manager-Skills
Skill namepestel-delta-monitor
Stars
7K
Forks
831
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 deanpeters on GitHub. Read the source before you install it.

Installation

Install the Pestel Delta Monitor 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/deanpeters/Product-Manager-Skills.git /tmp/Product-Manager-Skills
mkdir -p .claude/skills
cp -r /tmp/Product-Manager-Skills/skills/pestel-delta-monitor .claude/skills/pestel-delta-monitor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pestel Delta Monitor 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 Pestel Delta Monitor 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 Pestel Delta Monitor 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.

PESTEL Delta Monitor

Purpose

Refresh a PESTEL analysis by diffing each factor — Political, Economic, Social, Technological, Environmental, Legal — against the prior run and reporting material movement only: search plan → factor-by-factor diff → broken assumptions → new entrants to the frame → next-step options. Macro factors move slowly, which is exactly why teams stop looking; the value of a cadence is catching the two factors that moved, not re-debating the twenty that didn't. Diffing also reveals which baseline entries were live assumptions versus furniture — broken assumptions are the real output.

Input

Works best with: the prior PESTEL analysis (pasted or attached) and the product/market scope it covered — this skill requires a baseline to diff against. Also useful: any events since the last run you already suspect matter — they get checked first.

Input supplied inline with the invocation — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it against the question budget; don't re-ask.

Arriving empty-handed? This is the one investigation skill with a hard prerequisite: with no baseline, it recommends running pestel-analysis first and stops — there is nothing to diff. (That referral is the empty-handed path: you leave knowing exactly what to do first.)

Example invocation: PESTEL delta against the attached Q1 analysis — scope is our EU payments product; I suspect the new AI liability directive matters.

Key Concepts

  • Governing protocol: honors the autonomous-investigation contract — question budget of 2, search-plan gate, Fact/Inference/Assumption labels, Just Enough Mode, stable schema, 4-option Final Step. Disciplines: GEOINT/DEMOINT statistics plus FININT regulatory sources (see intelligence-collection-disciplines); this is the annual/quarterly layer of the fusion cadence.
  • Materiality for macro factors: regulation passed or credibly proposed, macro indicators crossing thresholds your baseline named, technology maturation with adoption evidence, social signals with data behind them. "No material movement" per factor is a valid and common result — a quiet quarter reported honestly keeps the radar trusted.
  • Broken assumptions are the headline. A baseline entry now contradicted by evidence outranks ten new observations, because strategy was built on it. The diff exists to find these.
  • Assumptions vs. furniture. Entries that never move and touch no decision were furniture — flag them for retirement at the next baseline refresh rather than re-scanning them forever.
  • Scope changes break diffs. New market, pivot, fundamentally different business context → redo the full PESTEL; never diff across a scope change.
  • Do-not-invent list: regulations, statistics, dates, events. Real URLs and dates on everything — invented regulation is this domain's signature fabrication risk.

Application

  1. Check the prerequisite. No prior PESTEL → recommend pestel-analysis and stop. Scope changed since the baseline → recommend a fresh full analysis and stop.
  2. Credit inline context, then ask only the unanswered questions (max 2):
    1. Prior PESTEL to paste?
    2. Any events since then you already suspect matter?
  3. Read the prior analysis fully; diff factor by factor — the baseline document is the diff target, not your general knowledge of the macro environment.
  4. Show the 3-bullet search plan — which factor categories get active searching this cycle (suspected events first), source types (government and regulatory sources, central-bank and statistical data, credible news, industry bodies, standards organizations), fact/inference separation. Continue unless revised.
  5. Emit the schema below exactly.

Output schema (do not reorder)

markdown
# PESTEL Delta Report

## 1. Run Header
**Scope (from prior analysis):** | **Prior analysis date:** | **This run date:**

## 2. Factor-by-Factor Delta
For each of P / E / S / T / E / L:
### [Factor]: [moved / no material movement]
- **What moved:** [1-2 bullets, labeled, cited — only if moved]
- **Prior assumption affected:** [which entry from the baseline]
- **Reading:** [Inference — implication for the product scope]

Keep "no material movement" factors to a single line each.

## 3. Broken Assumptions
- [Baseline entries now contradicted by evidence — the run's most important section; cited]

## 4. New to the Frame
- [Factors absent from the baseline that now warrant a slot]

## 5. So What?
- **3** implications for strategy or roadmap
- **2** factors to watch closely next cycle
- **3** assumptions to validate
Each bullet: label, confidence, URL where relevant.

A copy/paste fill-in version of this schema, with quality checks, lives in template.md.

Final Step (offer exactly 4 options)

  1. Update the baseline PESTEL with these deltas (new baseline)
  2. Deep-dive the most consequential moved factor
  3. Trace the broken assumptions into roadmap or OKR impact
  4. Set next cycle's watch priorities

Accept 1, 2, 3, 4, 1 and 2, Verbose Mode, or a custom path.

Examples

A factor that moved, traced to its assumption (fictional):

Legal: moved

  • What moved: the data-residency provision cleared committee with an 18-month compliance window — Fact ([legislature record, URL, date])
  • Prior assumption affected: baseline entry L2 assumed "no residency mandate before 2028," which justified deferring the regional storage architecture
  • Reading: the deferral logic is dead — Inference: the architecture decision moves from someday to next two roadmap quarters, and compliance becomes a sales asset in regulated verticals before it's a legal obligation.

A quiet quarter reported honestly: five factors show "no material movement" at one line each; one Economic entry moved (a rate-path shift crossing the baseline's stated budget-gate threshold). The report is half a page. That brevity is the radar working — the reader spends two minutes and knows the strategy's macro floor held except where it didn't.

See examples/sample.md for a complete worked delta run (fictional trades-software scope) with two broken assumptions traced to their baseline entries and furniture flagged for retirement. examples/sample-industrial.md runs the industrial scope, where the hot factors swap — tariffs, energy, disclosure rules — and threshold crossings are distinguished from broken assumptions.

Common Pitfalls

  • Re-debating the unmoved. Rewriting all six factors every quarter turns the radar back into the workshop it was meant to replace. One line per quiet factor — the discipline is the product.
  • Materiality inflation. Promoting think-pieces and proposals-going-nowhere into "movement." The bar is passed/credibly-proposed regulation, crossed thresholds, adoption evidence — not discourse.
  • Burying broken assumptions. Listing deltas without connecting them to the baseline entries they contradict. The "prior assumption affected" line is what makes a delta actionable.
  • Diffing across a pivot. The business entered a new market and the monitor keeps diffing the old scope's factors. Scope change = new baseline, always.
  • Invented specificity. A regulation name, effective date, or statistic that doesn't check out. In this domain a fabricated citation isn't just wrong, it's a compliance risk for the reader — the do-not-invent list is load-bearing.

References

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 Pestel Delta Monitor AI skill do?

Quarterly re-scan of a prior PESTEL analysis. Use when checking which macro factors moved, which assumptions broke, and what's new — turning PESTEL from a workshop artifact into a radar.

Why use Pestel Delta Monitor on TypingMind?

Because you install it once and use it with any model. Pestel Delta Monitor 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 Pestel Delta Monitor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/deanpeters/Product-Manager-Skills/tree/main/skills/pestel-delta-monitor. 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 Pestel Delta Monitor?

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 Pestel Delta Monitor?

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

Is the Pestel Delta Monitor AI skill free?

It is published on GitHub by deanpeters. 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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