PESTLE Analysis  Free · MIT · Base Skill #300

Macro-environment forecast

Read the weather outside your business before you plan the route.

Name a product, a market and the question you face. Your assistant scans six bands of external conditions, rates each factor for impact and likelihood, ranks what matters most and tells you what to watch, adapt to and prepare for.

Original instructions by Pawel Huryn (phuryn/pm-skills), kept byte for byte.

P
PoliticalFood-facility and vehicle permits
MH
E
EconomicOregon minimum-wage increase this year
HH
S
SocialHybrid work makes headcount unpredictable
HH
T
TechnologicalWeb and Slack ordering; 71% of orders in-app
MH
L
LegalCompostable-packaging rule next spring
HH
E
EnvironmentalFood waste from no-shows and leftovers
MH
Readings: impact, then likelihoodH HighM MediumL Low
One factor per band, abridged from a saved run on “Tidewell Desk”, an invented Portland lunch-kit startup. The full run rated 29 factors.
6bands: P, E, S, T, L, E
3–5factors in each band
2readings: impact × likelihood
0API keys or scripts

These counts are rules written in the Skill’s instructions, not performance claims.

What it is

A single instruction file that turns a capable AI assistant into a strategic analyst for the macro environment. It covers government policy, the economy, social trends, technology, law and the natural environment, then forces a choice: which factors are opportunities to use, which are threats to mitigate, and which simply require compliance.

The result does not stop at six lists. It prioritizes by impact × likelihood, names leading indicators to monitor, drafts contingency plans for high-impact factors and lists the assumptions that still need research.

Who it is for

Product managersplanning a launch or a roadmap that depends on regulation or demand shifts
Foundersweighing a new city, region or country
Strategy teamsneeding a structured first draft of external risks
Students and analystslearning to apply PESTLE with ratings, not just lists

Works well for

  • Market-entry checks: is this region viable to enter?
  • Risk reviews: what macro shifts could derail the plan?
  • Regulatory roadmaps: which compliance work must be scheduled?
  • Scenario planning and spotting new external opportunities

Not designed for

  • Legal advice or a final compliance determination
  • Live data: it has no built-in web research and uses what you supply or what your assistant can look up
  • Financial forecasts, valuations or investment decisions
  • Internal capability review: pair it with SWOT for that

What you provide, what you receive

You provide

  • Industry and market context
  • Geographic market or regions
  • Product or business type
  • The strategic challenge or question
  • Any known regulatory or market changes

You receive

  • 3–5 factors per band, each rated High / Medium / Low for impact and likelihood
  • A priority list ranked by impact × likelihood
  • Strategic responses: leverage, mitigate, comply or adapt
  • Leading indicators to monitor
  • Contingency plans for high-impact factors
  • Assumptions and unknowns that need research

Where it runs

Any AI assistant that can read a Skill file, including Claude Code and Codex. Download the free plaintext package from Finch, install it with your assistant’s Skill method, or ask the assistant to read SKILL.md.

No extra API key, script or service. You still need access to an assistant model, which may carry its own subscription or usage cost. The Skill does not browse the web on its own; supply current facts, or use an assistant that has search tools.

Limits and licence

Ratings are structured judgments, only as reliable as the facts supplied. Laws and rules named in an output must be checked against the real text before you act.

MIT licence, Copyright (c) 2026 Pawel Huryn. Source: phuryn/pm-skills at commit 2a12295a7717, path pm-product-strategy/skills/pestle-analysis. The package adds a README, NOTICE, provenance note and a promotional cover; the instructions are unchanged.

How it was checked

One controlled Claude Code run on a fictional company produced all 14 required parts: six bands, 29 rated factors, a ranked priority list, responses, indicators, contingencies and an unknowns list, with 11 assumption or unknown labels. Seven factors used in-between values such as M-H. The package downloaded back from Finch matched the audited files. Native install in each client, repeat runs and real business outcomes were not tested. The Benchmark tab has the full evidence trail.