Initial commit: AI conversation impact methodology and toolkit

CC0-licensed methodology for estimating the environmental and social
costs of AI conversations (20+ categories), plus a reusable toolkit
for automated impact tracking in Claude Code sessions.

plans/usage-guidelines.md

@@ -0,0 +1,46 @@
+# Plan: Define when to use (and not use) this tool
+
+**Target sub-goals**: 1 (estimate before acting), 3 (value per token),
+12 (honest arithmetic)
+
+## Problem
+
+Not every task justifies the cost of an LLM conversation. A grep command
+costs ~0 Wh. A Claude Code session costs ~6-250 Wh. Many tasks that people
+bring to AI assistants could be done with simpler tools at a fraction of
+the cost. Without explicit guidelines, the default is to use the most
+powerful tool available, not the most appropriate one.
+
+## Actions
+
+1. **Create a decision framework.** A simple flowchart or checklist:
+   - Can this be done with a shell command, a search engine query, or
+     reading documentation? If yes, do that instead.
+   - Does this task require generating or transforming text/code that a
+     human would take significantly longer to produce? If yes, an LLM
+     may be justified.
+   - Will the output reach many people or prevent significant harm? If
+     yes, the cost is more likely justified.
+   - Is this exploratory/speculative, or targeted with clear success
+     criteria? Prefer targeted tasks.
+
+2. **Integrate into CLAUDE.md.** Add the framework as a quick-reference
+   so it's loaded into every conversation.
+
+3. **Track adherence.** When a conversation ends, note whether the task
+   could have been done with a simpler tool. Feed this back into the
+   impact log.
+
+## Success criteria
+
+- The user (and I) have a shared understanding of when the cost is
+  justified.
+- Measurable reduction in conversations spent on tasks that don't need
+  an LLM.
+
+## Honest assessment
+
+High value but requires discipline from both sides. The framework itself
+is cheap to create. The hard part is actually following it — especially
+when the LLM is convenient even for tasks that don't need it. This plan
+is more about establishing a norm than building a tool.