journal-capture
Skill0 starsChanged 7 months agoMITView on GitHub
Captures decisions, reflections, brainstorms, progress, and teardowns to a structured JSONL journal. Use when user makes a choice, has a realization, brainstorms ideas, ships something, or analyzes a system. Also use when user says "journal this", "log this", "capture this", or signals session end.
In this repository37 other files it gives its agents.
- ablation-study-frameworkSkill
- async-http-websocket-patternsSkill
- brain-dumpSkill
- chaos-controlled-behavior-systemSkill
- daily-digestSkill
- database-reset-and-seedSkill
- duckdb-analytics-layerSkill
- event-driven-backtest-engineSkill
- event-study-full-pipelineSkill
- event-study-stats-suiteSkill
- failure-learning-systemSkill
- fastapi-sse-live-dashboardSkill
- goal-task-decompositionSkill
- high-information-gain-interviewerSkill
- idea-extraction-batch-pipelineSkill
- idea-grouping-taxonomySkill
- interview-belief-extractorSkill
- journal-reviewSkill
- keyword-filter-frameworkSkill
- langgraph-agentic-pipelineSkill
- llm-as-judge-eval-frameworkSkill
- multi-tab-dashboard-rendererSkill
- multi-tier-memory-systemSkill
- parquet-storage-with-walSkill
- project-insightsSkill
- pydantic-typed-config-loaderSkill
- quality-trend-detectionSkill
- research-gap-finderSkill
- safe-commitSkill
- simtom-knowledge-isolationSkill
- statistical-signal-detectionSkill
- streaming-dataset-pipelineSkill
- structured-data-extraction-pipelineSkill
- structured-logging-setupSkill
- system-health-monitoringSkill
- textual-tui-reactiveSkill
- vector-db-ingestionSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 57
Read last 5 lines of your journal file.
- Distinctive: line 126
When user signals wrapping up ("done", "thanks", "that's it"):
- Distinctive: line 129
Write them before responding
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Journal Capture
Automatically captures significant observations to a structured JSONL journal file.
Setup
Set your journal path. Default: data/journal.jsonl in your project root.
When to Capture
Trigger on any of these:
- A choice is made (architecture, approach, prioritization, scope, tools) → decision
- Something is learned or realized → reflection
- Ideas generated (features, strategies, directions) → brainstorm
- Something ships that users can actually interact with → progress
- A real system is studied in depth → teardown
Type Rules
These are the most common mistakes — follow strictly:
- "Decided to write a plan / do research / create docs" → decision (not progress — nobody can use a doc yet)
- "Chose tech stack, architecture, library, approach" → decision always
- "Feature ships / new tab live / deployed" → progress
- "Wrote code or files" → NOT progress unless something real ships
- "Had a realization mid-build" → reflection
- "Strategic conversation about process" → decision (meta-decisions count)
Instructions
Step 1: Determine entry type
Match the observation to a type using the rules above. When in doubt, prefer decision over progress.
Step 2: Identify the project
Tag with the appropriate project slug from your registry. Customize the table below for your projects:
| Slug | Name |
| my-app | My Application |
| tools | Internal Tools |
| research | Research |
Step 3: Dedup check
Read last 5 lines of your journal file. Same type + same project + same topic → replace, don't append.
Step 4: Write the entry
Append one JSON line to your journal file:
{"id": "<8-char-hex>", "type": "<type>", "created_at": "<iso-datetime>", "tags": ["project:<slug>", ...], ...fields}Entry Schemas
decision
{
"decision": "what was decided",
"why": "reasoning",
"expected_outcome": "what should happen",
"might_be_missing": "blind spots"
}reflection
{
"title": "short title",
"context": "situation",
"concept": "key concept",
"what_worked": "positives",
"what_didnt": "negatives",
"explanation": "key insight",
"change": "what to do differently"
}brainstorm
{
"title": "short title",
"content": "full content",
"insights": ["insight1", "insight2"],
"action_items": ["todo1", "todo2"]
}progress
{
"title": "short title",
"what_shipped": "what's live",
"impact": "why it matters",
"next_steps": ["step1", "step2"]
}teardown
{
"system_name": "name",
"source_url": "url",
"problem": "what they solved",
"constraints": "limitations",
"tradeoffs": "design choices",
"what_id_do": "personal take"
}Session End Sweep
When user signals wrapping up ("done", "thanks", "that's it"):
- Scan back through conversation
- Identify any uncaptured decisions, realizations, or strategic priorities
- Write them before responding
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

