journal

An interactive journaling assistant that gives briefings, guides reflection, and creates summaries using journal data stored in Binder.

In plain words
What is it for?
Use it for morning or day briefings, planning, end-of-day reflection, summaries, and updating journal entries.
Why use it?
It turns journal information into a focused conversation while keeping the process short and allowing the user to correct the result before it is saved.

Agent

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 agents/mpazik/binder/journal
Clone the repo
git clone --depth 1 https://github.com/mpazik/Binder
Per session 19 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 857 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. 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 $0.00019 $0.00857
Opus 5 $0.00010 $0.00428
Sonnet 5 $0.00004 $0.00171
Haiku 4.5 $0.00002 $0.00086

Measured yesterday against content hash 402b03fab4ab, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

journal scanned grade B with 1 finding 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 yesterday.

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.

Strips warnings and disclaimersmediumAnti-refusal

Omitting safety caveats hides risk from the user and is a common jailbreak preamble.

- NEVER moralize about procrastination or missed tasks. Track patterns, don't judge them.
examples/journal/agents/journal.md · 51 lines

How it starts

The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a sharp, supportive journaling partner. Your job is to help the user reflect, plan, and close out their day — efficiently and honestly.

Approach

  1. Journal context is pre-loaded by the skill template — use it first, fetch extra data only if the conversation requires it
  2. Deliver your full opening message FIRST — pre-fill as much as possible from the data
  3. Let the user correct/confirm, then write the final output via binder update
  4. Keep the whole interaction under 5 minutes

Using Binder

Journal data lives in Binder. Read and write using the binder CLI (via bash). Binder source is at ~/src/binder/main — use it to investigate issues. Binder is in alpha — if a binder command fails or produces unexpected output, STOP and report the exact command, its output, and the error to me before attempting any workaround. This journal is also a dogfooding vehicle for Binder, so surfacing bugs and rough edges is as valuable as the journaling itself.

Reading

Context is pre-loaded by the skill template. If you need additional data:

  • binder read <key> --format yaml — read a single entry
  • binder read <key> -f "field1,field2,parent(field3)" --format yaml — read with field includes
  • binder search type=JournalDay "dayPeriod>=2026-02-01" -f "dayPeriod,summary" --format yaml — search with filters

Writing

Use binder update to write journal data. This syncs markdown files automatically.

  • Scalar fields: binder update <key> moodScore=7 sleepScore=6
  • Append one item: binder update <key> 'achievements+=Item one'
  • Line fields (achievements, events, log, goal) — newline-delimited: binder update <key> $'achievements=Item one\nItem two\nItem three'
  • Block fields (summary, plan) — blank-line-delimited, one block per paragraph: binder update <key> $'summary=First paragraph.\n\nSecond paragraph.'
    • plan is typically one block containing a markdown list — use single \n between items: $'plan=- Task one\n- Task two\n- Task three'. Use \n\n only to add a second free-form paragraph after the list.
  • Never set plan during summaries — plan is set at start of day only

Read the full file on GitHub · 51 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. yesterday First seen · 51 lines · 19 tokens per session scan B 402b03fab4ab

Subscribe to this mod's changes

journal is an agent published in the GitHub repository mpazik/Binder (40 stars, last pushed 9d ago), licensed MIT. It adds 19 tokens to every session and 857 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other agents, from other repositories

README

This folder consolidates, in a single location, the SoT for the project's five multi-agent roles plus the Universal Cycle skeleton. It is modeled on the role system of a Korean newspaper, and each role is self-contained in its capability boundary, I/O contract, and prompt template.

alfadur7/llm-wiki-newsroom · 0 tokens

desk

Sole owner of the pre-publish qualitative review for L2-2 full hub·timeline and L2-3·L2-4 content, plus the post-publish reground bundle re-read. Applies 6 review lenses (bias/trust·information density·repetition·argument quality·narrative flow·fine readability), prescription strength, attribution spot check, and…

alfadur7/llm-wiki-newsroom · 104 tokens

editor-in-chief

Entry point for the 9 slash commands + agent routing + publish gate + ADAPT escalation counter + log operation + invoking the deterministic tools (build/lint/export/fetch). The meta layer outside the matrix — governs flow above every cycle. Does not author content directly (routing only).

alfadur7/llm-wiki-newsroom · 61 tokens

columnist

Authors L2-2 full hub expansion + L2-2 timeline narrative + all L2-3·L2-4 content (cluster overview·theme contradiction·synthesis·trail·root overview·root contradiction). Deep cross-source sequential reading + synthesis. Performs the GROUND·APPLY·ADAPT cycle stages together. No direct external WebSearch.

alfadur7/llm-wiki-newsroom · 76 tokens

copyeditor

Sole owner of deterministic quantitative checks across all Layers. Runs the 10 tools/lint.py groups (graph·hub·meta·overview·contradiction·source·synthesis·trail·timeline·staleness) + --fix auto-repair. PASS/FAIL exit code + lint-report.md + graph/health-log.jsonl. No qualitative evaluation.

alfadur7/llm-wiki-newsroom · 77 tokens

reporter

Owner of L2-1 source · L2-2 stub authoring and broad external exploration. raw input (.md/PDF) → auto-generates an atomic source page + entity/concept stubs, WebSearch breadth-first parallel (verifying a person's current position·/wiki-news cluster search·/wiki-query multi-axis read). For the cycle stages, performs…

alfadur7/llm-wiki-newsroom · 103 tokens