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.
npx agentmods add commands/rlancemartin/claude-diary/diarygit clone --depth 1 https://github.com/rlancemartin/claude-diaryWrote 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/rlancemartin/claude-diary/diary)<a href="https://agentmods.dev/commands/rlancemartin/claude-diary/diary"><img src="https://agentmods.dev/badge/commands/rlancemartin/claude-diary/diary.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 | $0.00010 | $0.01598 |
| Opus 5 | $0.00005 | $0.00799 |
| Sonnet 5 | $0.00002 | $0.00320 |
| Haiku 4.5 | $0.00001 | $0.00160 |
Grade A, and why
diary 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 5d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Diary Entry from Current Session
You are going to create a structured diary entry that documents what happened in the current Claude Code session. This entry will be used later for reflection and pattern identification.
Approach: Context-First Strategy
Primary Method (use this first): Reflect on the conversation history loaded in this session. You have access to:
- All user messages and requests
- Your responses and tool invocations
- Files you read, edited, or wrote
- Errors encountered and solutions applied
- Design decisions discussed
- User preferences expressed
When to use JSONL fallback (rare):
- Session was compacted and context is incomplete
- You need precise statistics (exact tool counts, timestamps)
- User specifically requests detailed session analysis
Steps to Follow
1. Create Diary Entry from Context (Primary Method)
Review the current conversation and create a diary entry based on what happened. No tool invocations needed for typical sessions.
Skip to Step 4 to write the diary entry.
2. Fallback: Locate Session Transcript (Only if context insufficient)
If you determine context is insufficient, run this command to find the transcript:
# Find the most recent session file for this project
# NOTE: Path format includes leading dash: -Users-name-Code-app
SESSION_FILE=$(ls -t ~/.claude/projects/-$(echo "{{ cwd }}" | sed 's/\//‐/g')/*.jsonl 2>/dev/null | head -1) && \
if [ -z "$SESSION_FILE" ]; then \
echo "ERROR: No session file found" && \
echo "Looking in: ~/.claude/projects/-$(echo "{{ cwd }}" | sed 's/\//‐/g')/" && \
ls -la ~/.claude/projects/ | head -20; \
else \
echo "FOUND: $SESSION_FILE" && \
ls -lh "$SESSION_FILE"; \
fi
What this does:
- Converts current directory to project hash format (e.g.,
/Users/name/Code/app→-Users-name-Code-app) - Note the LEADING DASH in the path format
- Finds the most recent
.jsonlfile in that project's directory
3. Fallback: Extract Key Metadata (Only if needed)
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.
- 5d ago First seen · 203 lines · 10 tokens per session scan A d65af7a652dd
diary is a command published in the GitHub repository rlancemartin/claude-diary (379 stars, last pushed 8mo ago), licensed MIT. It adds 10 tokens to every session and 1,598 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 2026-08-30.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.