thinkhaven: Command for Claude Code

.claude/commands/bmadPMF/tasks/analyze-sales-call.md

analyze-sales-call is a command for Claude Code from hollandkevint/thinkhaven. It costs 0 tokens per session (1,402 once invoked), scanned A, original, Apache-2.0.

A command that reviews a recorded or documented sales call to identify customer interest, objections, engagement, and useful changes to a case study.

In plain words
What is it for?
Use it to document prospect context, locate moments of strong or weak engagement, compare case-study versions, and identify demand patterns or follow-up opportunities.
Why use it?
It turns individual sales conversations into organized feedback instead of relying only on memory or intuition.

Command for Claude Code

Written for Claude Code: installed under .claude/.

This is hollandkevint/thinkhaven's own configuration. It tells Claude Code how to work on thinkhaven itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything thinkhaven configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/hollandkevint/thinkhaven/main/.claude/commands/bmadPMF/tasks/analyze-sales-call.md
Clone the repo
git clone --depth 1 https://github.com/hollandkevint/thinkhaven

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,402 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 $0.00000 $0.01402
Opus 5 $0.00000 $0.00701
Sonnet 5 $0.00000 $0.00280
Haiku 4.5 $0.00000 $0.00140

Measured 10d ago against content hash 841b92f40db5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

analyze-sales-call 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 10d 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.

.claude/commands/bmadPMF/tasks/analyze-sales-call.md · 223 lines

How it starts

The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/analyze-sales-call Task

When this command is used, execute the following task:

Analyze Sales Call Task

Purpose

To systematically extract insights from sales conversations that reveal demand patterns, friction points, and opportunities for case study refinement. Every call is data that brings you closer to product-market fit.

Inputs

  • Recording or detailed notes from recent sales call
  • Current case study version used in the call
  • Prospect information (role, company, context)
  • Call outcome (next steps, objections, interest level)
  • Your gut feeling about what went well/poorly

Key Activities & Instructions

1. Call Setup Documentation

Record the context for proper analysis:

  • Prospect Profile: Role, company size, industry
  • How They Found You: Inbound/outbound, referral source
  • Pre-Call Research: What you knew going in
  • Their Stated Interest: Why they took the meeting
  • Case Study Version: Which variation you presented

2. Energy and Engagement Mapping

Track engagement throughout the call:

2.1 High Energy Moments
  • When did they lean in or get excited?
  • What specific words/phrases sparked interest?
  • Which slides/sections generated questions?
  • When did they start selling themselves?
2.2 Energy Drops
  • Where did enthusiasm wane?
  • Which sections felt like pushing uphill?
  • When did they disengage or multitask?
  • What triggered skepticism or doubt?

<critical_rule>Map energy shifts to specific case study sections</critical_rule>

3. Question Analysis

Document and interpret every question asked:

Question Asked Underlying Concern What This Reveals
"How long does implementation take?" Risk/effort concern Need clearer "How" section
"Who else uses this?" Social proof needed Add customer examples
"Can it integrate with X?" Technical feasibility Address in options

Read the full file on GitHub · 223 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. 10d ago First seen · 223 lines · 0 tokens per session scan A 841b92f40db5

Subscribe to this mod's changes

analyze-sales-call is a command published in the GitHub repository hollandkevint/thinkhaven (5 stars, last pushed 11d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,402 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 2026-08-31.