strategy-doc

strategy-doc is a skill for Claude Code from matteotitta/genesys-skills. It costs 154 tokens per session (2,112 once invoked), scanned A, original, MIT.

A guided product strategy document based on the Good Strategy Bad Strategy framework. It defines the problem, chosen approach, target user, success measures, and a small set of work tracks.

In plain words
What is it for?
Use it to set or refresh product direction, choose a primary audience, define meaningful metrics, and organise major work areas.
Why use it?
It gives a product team a shared direction and separates strategic choices from a feature specification, which describes what to build.

Skill for Claude Code

Written for Claude Code: effort in frontmatter.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is This skill is the anchor of the **PM closed loop** (P3 in `.claude/discovery/0526-every-ai-pm-guide-steal-analysis.md`). See [.claude/rules/pm-loop.md](../../...

Good fit Use it to set or refresh product direction, choose a primary audience, define meaningful metrics, and organise major work areas.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/matteotitta/genesys-skills
agentmods
npx agentmods add skills/matteotitta/genesys-skills/strategy-doc

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 154 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,112 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00154 $0.02112
Opus 5 $0.00077 $0.01056
Sonnet 5 $0.00031 $0.00422
Haiku 4.5 $0.00015 $0.00211

Measured 9d ago against content hash 08cc436679e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

strategy-doc scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/primitives/product-management/strategy/strategy-doc/SKILL.md · 181 lines

How it starts

The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product strategy doc — 5-part GSBS structure

Produce a locked product strategy document that anchors the agent-native PM operating loop. Adapted from /ce-strategy in EveryInc/compound-engineering-plugin v3.5.0 (MIT). Based on Marcus Moretti's AI PM Guide (Every.to) and Richard Rumelt's Good Strategy Bad Strategy.

This is not a spec or PRD. Strategy describes the guiding policy (what we'll do and why); requirements describe the artifacts (what we'll build). Keep them separate.

When to run

Invoke when the user says:

  • "Run product strategy for [Genesys ship / client product]"
  • "What's our strategy for [product]?"
  • "Time for the quarterly strategy refresh"
  • "Run the strategy interview"

Do NOT invoke when:

  • User wants positioning / category framing → /positioning (PMM-side, different artifact)
  • User wants a feature spec / PRD → external product-management:write-spec plugin
  • User wants the daily product pulse → /product-pulse (downstream of this skill)
  • User wants post-ship learnings → /ship-learnings

Workflow sequences:

  • New product: company-context → icp-research → positioning → strategy-doc → product-pulse → ship-learnings
  • Refresh: ship-learnings (last cycle) + product-pulse (last cycle) → strategy-doc (refreshed)

Inputs

Required:

  • Product name + 1-line description
  • Stakeholder for review (founder / PM / ops lead)

Recommended (improve quality):

  • company-context — firmographics, traction, qualification context
  • icp-research / icp-behavioural — sharpens the "who-for" section
  • positioning — gives anchors and differentiators (the "approach")
  • win-loss-analysis — what users actually pay for vs. ignore
  • Latest product-pulse and ship-learnings from prior cycle (for refresh runs)

If inputs missing: Run a 5-section guided interview anyway. Flag data gaps. Recommend running upstream skills before lock.

The 5 parts (GSBS structure)

Read the full file on GitHub · 181 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 181 lines · 154 tokens per session scan A 08cc436679e8

Subscribe to this mod's changes

strategy-doc is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 154 tokens to every session and 2,112 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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