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Product Discovery
by
Alireza Rezvani
· GitHub ↗
· v2.1.1
· MIT-0
296
Downloads
0
Stars
4
Active Installs
2
Versions
Install in OpenClaw
/install product-discovery
Description
Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resour...
Usage Guidance
This skill appears to do exactly what it claims: a small local Python CLI to prioritize assumptions and suggest tests. Before installing: ensure you have Python 3 available (SKILL.md calls `python3` but the metadata doesn't declare it). Review the included script (scripts/assumption_mapper.py) — it only reads CSV/CLI input and prints results, and makes no network calls or secret access. When using untrusted CSVs, be cautious about CSV-injection (if you open the output in Excel/Sheets, cells that begin with '=' or similar may be treated as formulas). If you plan to let the agent invoke skills autonomously, note this skill itself has no external access, but always verify future updates or added files for network/credential usage.
Capability Analysis
Type: OpenClaw Skill
Name: product-discovery
Version: 2.1.1
The skill bundle provides a legitimate framework and utility for product discovery and assumption mapping. The Python script `scripts/assumption_mapper.py` performs basic data processing on CSV or inline inputs to prioritize risks, and it contains no network calls, shell execution, or unauthorized file access. All instructions in `SKILL.md` and documentation in `references/discovery-frameworks.md` are consistent with standard product management practices.
Capability Assessment
Purpose & Capability
The name/description (product discovery, assumption mapping) match the provided files and behavior. Minor mismatch: SKILL.md instructs running `python3 scripts/assumption_mapper.py` but the skill metadata does not declare a required binary; the script requires a Python 3 runtime to be present.
Instruction Scope
SKILL.md stays on-topic (OST, assumption mapping, tests, discovery sprints) and only instructs running the included assumption_mapper.py or performing interviews/experiments. The instructions do not request unrelated files, credentials, or external endpoints.
Install Mechanism
There is no install specification (instruction-only), and the repo includes a small Python script. No downloads, external packages, or extraction steps are present. Runtime depends on a local Python 3 interpreter which is not declared in required binaries.
Credentials
The skill requests no environment variables, credentials, or config paths. The included script reads only user-supplied CSV files or inline arguments and prints a prioritized plan to stdout.
Persistence & Privilege
always is false and the skill is user-invocable. It does not request persistent presence or modify other skills or system-wide settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install product-discovery - After installation, invoke the skill by name or use
/product-discovery - Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.1.1
v2.1.1: optimization, reference splits
v1.0.0
Initial publish
Metadata
Frequently Asked Questions
What is Product Discovery?
Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resour... It is an AI Agent Skill for Claude Code / OpenClaw, with 296 downloads so far.
How do I install Product Discovery?
Run "/install product-discovery" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Product Discovery free?
Yes, Product Discovery is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Product Discovery support?
Product Discovery is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Product Discovery?
It is built and maintained by Alireza Rezvani (@alirezarezvani); the current version is v2.1.1.
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