structured-log
Skill9 starsChanged 6 months agoMITView on GitHub
Write structured entries to daily memory log with facts, concepts, and files — use after any meaningful work, research, or decision
1 other project uses a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- Layneformalized225/ai-cofounderedited, first seen Mar 22, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
- Layneformalized225/ai-cofounder★ 184% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 2 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 8
Write structured entries to memory/YYYY-MM-DD.md instead of free-form text.
- Distinctive: line 12
After any meaningful action:
- Very specific: line 48
Concepts are for search: Write keywords you'd use to find this entry later via memory_search.
- Distinctive: line 50
One entry = one topic: Don't mix a decision + tool finding in one entry.
≈ “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
Structured Log
Write structured entries to memory/YYYY-MM-DD.md instead of free-form text. This improves recall via memory_search.
When to Use
After any meaningful action:
- Made a decision or received a decision from the founder
- Discovered a new fact (via Exa, PostHog, web, conversation)
- Found an insight or pattern
- Completed a task with a result
- Updated a hypothesis
Entry Format
### HH:MM — [TYPE] Title
What happened (1-2 sentences).
**Facts:**
- concrete fact 1
- concrete fact 2
**Concepts:** keyword1, keyword2, keyword3
**Files:** path/to/file (if changed)Types (TYPE)
| Type | When |
| DECISION | Decision made (by whom, why, what changes) |
| FACT | New confirmed fact (source required) |
| INSIGHT | Pattern, connection, conclusion from data |
| TOOL | Finding from tool usage (PostHog, Exa, web) |
| TASK | Completed task with result |
| HYPOTHESIS | Created/updated/killed a hypothesis |
Rules
- Facts must be verifiable. "Signups = 0 for 7 days" (ok). "Seems low" (no).
- Concepts are for search. Write keywords you'd use to find this entry later via
memory_search. Include: names, products, metrics, topics. - Files — only if changed. List only files that were created or modified.
- One entry = one topic. Don't mix a decision + tool finding in one entry.
- Narrative < 50 words. Context goes in facts, not prose.
Promotion to MEMORY.md
A fact deserves promotion to MEMORY.md if:
- It changes understanding of wedge, ICP, constraint
- It's confirmed 2+ times from different sources
- It affects current strategy or hypothesis
On promotion — add to the appropriate MEMORY.md section and remove outdated info.
Example
### 14:30 — [TOOL] PostHog: 41% activation step failures
PostHog query revealed a high percentage of errors during the key activation step.
**Facts:**
- 41% of `primary_resource_action` events have `processingStatus=failed` (30d)
- Main errors: timeout on large inputs (above the documented size limit)
- Affects the `first_primary_resource_added -> primary_resource_processed` funnel stage
**Concepts:** activation-blocker, funnel-drop, PostHog, TTFV
**Files:** —Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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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.

