product-strategy

product-strategy is a skill for Codex from TIKAZI/TIKAZ-AI-Skills. It costs 44 tokens per session (265 once invoked), scanned A, original, MIT.

A decision-making guide for understanding users and markets, comparing product choices, planning launches, and measuring product results.

In plain words
What is it for?
Use it for positioning, prioritization, go-to-market planning, product analytics, market research, and experiments with measurable success criteria.
Why use it?
It separates evidence from assumptions and makes tradeoffs, risks, and next steps explicit when deciding what to build or pursue.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it for positioning, prioritization, go-to-market planning, product analytics, market research, and experiments with measurable success criteria.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tikazi/tikaz-ai-skills/product-strategy
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add TIKAZI/TIKAZ-AI-Skills --skill product-strategy
Clone the repo
git clone --depth 1 https://github.com/TIKAZI/TIKAZ-AI-Skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for product-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/product-strategy/github.svg)](https://agentmods.dev/skills/tikazi/tikaz-ai-skills/product-strategy)
Your own site
<a href="https://agentmods.dev/skills/tikazi/tikaz-ai-skills/product-strategy"><img src="https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/product-strategy/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for product-strategy

Your own site · 80×15
<a href="https://agentmods.dev/skills/tikazi/tikaz-ai-skills/product-strategy"><img src="https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/product-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 265 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.
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 $0.00044 $0.00265
Opus 5 $0.00022 $0.00133
Sonnet 5 $0.00009 $0.00053
Haiku 4.5 $0.00004 $0.00026

Measured 12d ago against content hash 8e6e0ee15708, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

product-strategy 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 12d 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.

suites/knowledge-research/product-strategy/SKILL.md · 29 lines

What it actually says

Product Strategy

This clean-room TIKAZ Edition is designed, integrated, independently refactored, and continuously maintained by TIKAZ.

Inputs and workflow

Accept the target user, problem, desired outcome, constraints, alternatives, available evidence, business model, time horizon, and decision metric. Separate facts from assumptions, compare a small set of viable directions, test positioning and risks, and recommend one direction with measurable next experiments.

Output contract

Return the problem framing, evidence and assumptions, alternatives, recommendation, tradeoffs, prioritization, success metrics, experiment plan, and decision risks.

Validation and fallback

Trace important market claims to dated sources or label them assumptions. If customer or usage evidence is missing, recommend a validation experiment rather than presenting a forecast as fact.

Example and limits

Use product-strategy to compare these three product directions and recommend one based on user value, evidence, effort, differentiation, and measurable validation.

This Skill supports decisions; it does not guarantee adoption, revenue, or market fit.

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 29 lines · 44 tokens per session scan A 8e6e0ee15708

Subscribe to this mod's changes

product-strategy is a skill published in the GitHub repository TIKAZI/TIKAZ-AI-Skills (6 stars, last pushed 10d ago), licensed MIT. It adds 44 tokens to every session and 265 once invoked, about $0.0002 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 2026-08-31.

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