diary

diary is a command for coding agents from PGHH84/claude-layered-learning. It costs 9 tokens per session (1,050 once invoked), scanned A, original, MIT.

A command that records a structured diary entry about the current coding-agent session. The entry is saved as raw material for a later reflection command to analyse.

In plain words
What is it for?
Use it at the end of a session to document what happened, what was changed, and what problems were solved. It can also capture the project and session context in the diary file path.
Why use it?
It preserves decisions, files changed, errors, and other session details that might otherwise be forgotten. This gives later reviews a consistent record of the work.

Command

Install

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.

agentmods
npx agentmods add commands/pghh84/claude-layered-learning/diary
Clone the repo
git clone --depth 1 https://github.com/PGHH84/claude-layered-learning

Wrote 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.

agentmods badge for diary

README.md
[![agentmods](https://agentmods.dev/badge/commands/pghh84/claude-layered-learning/diary.svg)](https://agentmods.dev/commands/pghh84/claude-layered-learning/diary)
Your own site
<a href="https://agentmods.dev/commands/pghh84/claude-layered-learning/diary"><img src="https://agentmods.dev/badge/commands/pghh84/claude-layered-learning/diary.svg" alt="Measured on agentmods" height="20"></a>
Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,050 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00009 $0.01050
Opus 5 $0.00005 $0.00525
Sonnet 5 $0.00002 $0.00210
Haiku 4.5 $0.00001 $0.00105

Measured 4d ago against content hash bd117a28f22a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 4d 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.

commands/diary.md · 166 lines

How it starts

The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create Diary Entry

Capture a structured diary entry documenting the current Claude Code session. This entry is raw material for /reflect to mine later for cross-session patterns. It is not analyzed or routed here.

Approach: Context-First Strategy

Primary method (use this first): Reflect on the conversation history loaded in this session. You have access to:

  • 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 such as exact tool counts or timestamps
  • the user explicitly requests detailed session analysis

Runtime Paths

  • diary output: ~/.claude/memory/diary/YYYY-MM-DD-<project-slug>-session-N.md
  • project memory that may already exist: ~/.claude/projects/<slug>/memory/MEMORY.md

Path-To-Slug Transform

Use this exact transform so /diary, /reflect, wrap-up, and the PreCompact hook agree on project identity:

  1. If inside a git repository, resolve the canonical project root with git rev-parse --show-toplevel.
  2. If that repo root contains /.worktrees/, strip the /.worktrees/<name> suffix and use the parent repo path as the canonical project root.
  3. Otherwise, if not inside a git repository, use the canonical absolute working directory.
  4. Resolve symlinks before deriving the slug.
  5. Replace every / in the canonical absolute path with -.

Session Number Source of Truth

Use one source of truth for the session number so wrap-up and standalone /diary do not diverge.

  • preferred source of truth: ~/.claude/projects/<slug>/memory/MEMORY.md
  • fallback: scan matching diary files for the same project and date only when MEMORY.md is missing or uninitialized
  • if wrap-up already updated MEMORY.md, reuse that session number instead of incrementing again
  • include a Session ID line only when a runtime session identifier is actually available

Read the full file on GitHub · 166 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. 4d ago First seen · 166 lines · 9 tokens per session scan A bd117a28f22a

Subscribe to this mod's changes

diary is a command published in the GitHub repository PGHH84/claude-layered-learning (2 stars, last pushed 5mo ago), licensed MIT. It adds 9 tokens to every session and 1,050 once invoked, about $0.0000 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.