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.
git clone --depth 1 https://github.com/tjboudreaux/cc-plugin-product-strategistWrote 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.
[](https://agentmods.dev/commands/tjboudreaux/cc-plugin-product-strategist/product)<a href="https://agentmods.dev/commands/tjboudreaux/cc-plugin-product-strategist/product"><img src="https://agentmods.dev/badge/commands/tjboudreaux/cc-plugin-product-strategist/product/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.
<a href="https://agentmods.dev/commands/tjboudreaux/cc-plugin-product-strategist/product"><img src="https://agentmods.dev/badge/commands/tjboudreaux/cc-plugin-product-strategist/product.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.00650 |
| Opus 5 | $0.00008 | $0.00325 |
| Sonnet 5 | $0.00003 | $0.00130 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
product 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Analysis
Analyze: $ARGUMENTS
Instructions
Parse the arguments to determine analysis type and subject, then apply appropriate product skills.
Analysis Types
1. Opportunity Analysis
Trigger: "opportunity", "market", "find opportunities"
/product opportunity <market or segment>
- Apply
product-opportunity-mappingfor signal harvesting - Apply
thinking-first-principlesto challenge assumptions - Output: Opportunity brief with scoring
2. Value Proposition
Trigger: "value-prop", "positioning", "why users"
/product value-prop <product or feature>
- Apply
product-value-propositionfor proposition design - Apply
product-behavior-signalsfor user insights - Output: Positioning statement with validation plan
3. Growth Strategy
Trigger: "growth", "scale", "loops", "retention"
/product growth <product>
- Apply
product-growth-loopsfor loop design - Apply
product-monetizationfor revenue alignment - Apply
thinking-second-orderfor consequence analysis - Output: Growth model with experiments
4. Launch Planning
Trigger: "launch", "gtm", "go-to-market"
/product launch <feature or product>
- Apply
product-launch-opsfor staged rollout - Apply
thinking-pre-mortemfor risk identification - Apply
eng-user-impactfor success metrics - Output: Launch playbook with guardrails
5. Product Review
Trigger: "review", "critique", "evaluate"
/product review <product or feature>
- Apply all product skills for comprehensive review
- Apply
thinking-inversionfor failure analysis - Output: Structured critique with recommendations
Output Format
## Product Analysis: [Subject]
**Type**: [Analysis Type]
### Summary
[Key findings in 2-3 sentences]
### Analysis
[Detailed analysis using appropriate framework]
### Evidence
| Signal | Source | Strength |
|--------|--------|----------|
### Recommendations
1. [Actionable recommendation]
2. [Actionable recommendation]
### Next Steps
- [ ] [Experiment or validation to run]
- [ ] [Research to conduct]
### Risks
| Risk | Likelihood | Mitigation |
|------|------------|------------|
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.
- 11d ago First seen · 106 lines · 0 tokens per session scan A 60429bc2823e
product is a command published in the GitHub repository tjboudreaux/cc-plugin-product-strategist (2 stars, last pushed 7mo ago), licensed MIT. It adds 16 tokens to every session and 650 once invoked, about $0.0001 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.