Borrowing it
Nothing to install: this file belongs to hollandkevint/thinkhaven. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hollandkevint/thinkhaven/main/.claude/commands/bmadPMF/tasks/identify-demand-patterns.mdgit clone --depth 1 https://github.com/hollandkevint/thinkhavenWrote 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/hollandkevint/thinkhaven/identify-demand-patterns)<a href="https://agentmods.dev/commands/hollandkevint/thinkhaven/identify-demand-patterns"><img src="https://agentmods.dev/badge/commands/hollandkevint/thinkhaven/identify-demand-patterns.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.01371 |
| Opus 5 | $0.00000 | $0.00685 |
| Sonnet 5 | $0.00000 | $0.00274 |
| Haiku 4.5 | $0.00000 | $0.00137 |
Grade A, and why
identify-demand-patterns 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 3d 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/identify-demand-patterns Task
When this command is used, execute the following task:
Identify Demand Patterns Task
Purpose
To systematically analyze customer interactions and extract recurring demand patterns that reveal what causes people to buy. Understanding these patterns allows you to focus on customers with the highest demand intensity and refine your case study accordingly.
Inputs
- Notes from 5+ customer conversations
- Sales call recordings or transcripts
- Closed won/lost deal analysis
- Customer support interactions
- Inbound inquiry patterns
- Competitor intelligence
Key Activities & Instructions
1. Collect Demand Data Points
Gather all customer interaction data:
1.1 Direct Demand Signals
- Explicit Statements: "We need to solve X by Y date"
- Budget Mentions: "We have $X allocated for this"
- Timeline Pressure: "This is critical for Q2"
- Team Involvement: Multiple stakeholders engaged
- Process Questions: "How quickly can we implement?"
1.2 Indirect Demand Signals
- Question depth and specificity
- Meeting attendance and punctuality
- Follow-up speed and thoroughness
- Internal champion emergence
- Resource allocation discussions
2. Map Customer Projects
For each customer interaction, identify:
The Core Project:
- What are they trying to accomplish? (in their words)
- What does "done" look like to them?
- Who owns this project internally?
- What's the business impact of completion?
<critical_rule>Use their exact language, not your interpretation</critical_rule>
Example mapping:
Customer A: "Get our sales team ramped faster"
Customer B: "Reduce time to first deal"
Customer C: "Onboard new reps in half the time"
Pattern: Sales team productivity project
3. Analyze Context Patterns
Identify what causes projects to become priorities:
3.1 External Catalysts
- New competitor threat
- Market opportunity window
- Regulatory deadline
- Economic pressure
- Technology shift
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.
- 3d ago First seen · 273 lines · 0 tokens per session scan A c9a23a5473be
identify-demand-patterns is a command published in the GitHub repository hollandkevint/thinkhaven (5 stars, last pushed 8d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,371 tokens. 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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