structured-log
Skill1 starsChanged 8 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
- CodeAlive-AI/ceo-ai-osedited, first seen May 18, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
- CodeAlive-AI/ceo-ai-os★ 983% 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.
In this repository47 other files it gives its agents.
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- founder-salesSkill
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- hypothesis-trackerSkill
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- launch-marketingSkill
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- metrics-briefingSkill
- ph-launch-timelineSkill
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- posthog-analyticsSkill
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- problem-definitionSkill
- product-hunt-launchSkill
- product-led-salesSkill
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- seo-auditSkill
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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] Analytics: 41% onboarding drop-off
Analytics query revealed a high drop-off rate during onboarding.
**Facts:**
- 41% of users who start onboarding don't complete the key activation step (30d)
- Main cause: timeout on large data imports
- Affects the signup -> activated funnel stage
**Concepts:** onboarding, activation-blocker, funnel-drop, analytics, 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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Your trail
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