agent-memory
Skill0 starsChanged 4 months agoMITView on GitHub
Use when setting up or maintaining persistent memory for a long-running agent — the one-fact-per-file structure, what deserves to be written, and the verification habit that keeps failed writes from being reported as successes
38 other projects use a version of this.
Adopted by
Most recently taken up by
- isaacbitran/agent-memorytheir own version, first seen Nov 8, 2026
- msking18/agent-memory-mcptheir own version, first seen Nov 8, 2026
- komluk/scaffoldingtheir own version, first seen Nov 7, 2026
- MemTether/MemTethertheir own version, first seen Nov 1, 2026
- tigerless-labs/agent-memorytheir own version, first seen Oct 22, 2026
- brianschroeder/simple-agent-memorytheir own version, first seen Oct 21, 2026
Used with
Projects with it also use observability, data-analysis and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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Also in 4 projects that use this
shanggqmSkilldata-analysis
数据分析技能,提供结构化的数据查询、统计分析和报告生成工作流。当用户需要查询数据库、进行数据统计分析、生成分析报告时使用。按规范输出原始数据、计算结果、Markdown报告和HTML可视化报告。
Also in 3 projects that use this
Microsoft AzureSkillskill-authoring
Write Agent Skills that comply with the agentskills.io specification. WHEN: "create a skill", "new skill", "write a skill", "skill template", "skill structure", "review skill", "skill PR", "skill compliance", "SKILL.md format", "skill frontmatter", "skill best practices". DO NOT USE FOR: general documentation. INVOKES: vally CLI.
Also in 3 projects that use this
VercelSkilltechnical-writing
Write, edit, review, or audit user-facing documentation for the eve repository. Use for changes under docs/, documentation tied to eve APIs or CLI behavior, docs work based on Slack or support feedback, and requests to make eve docs clearer, more natural, or less AI-patterned while verifying claims against current source, tests, CLI help, public releases, and repository conventions.
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JetBrainsSkillwebapp-testing
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
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AnthropicSkillpdf
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Also in 5 projects that use this
Other versions38 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 38
- tigerless-labs/agent-memory★ 4.3ksame name
- databricks/app-templates★ 218same name
- OpenHands/extensions★ 167same name
- JKHeadley/instar★ 86same name
- nimadorostkar/Claude-Skills-collection★ 33same name
- VoDaiLocz/kilo-kit-mcp★ 28same name
- jayzeng/agentmemory★ 24same name
- komluk/scaffolding★ 16same name
- xChuCx/agent-memory★ 11same name
- t4sh/skills4sh★ 5same name
28 more not listed
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 repository7 other files it gives its agents.
- blast-radiusSkill
- falsifier-designSkill
- orchestrator-judgmentSkill
- ratchet-not-ceilingSkill
- root-cause-disciplineSkill
- standing-instructionsSkill
- verify-before-judgingSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 33 edited versions we read keep these.
4
Distinctive
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 48
Never put content in the index.
- Distinctive: line 78
Write at that moment. A lesson you didn't record does not exist in the next session — and the next session is confident, because it has no …
- Distinctive: line 88
Put principles at the top and current status at the bottom.
- Distinctive: line 116
Delete memories that turn out to be wrong.
“Common” is measured: kept by at least 6 in 10 of the 33 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent memory that survives compaction
Long sessions get summarized. Anything not written to a file is gone, and you will not notice it's gone — you'll just quietly stop applying it.
Structure
One directory. One fact per file. An index that loads every session.
memory/
MEMORY.md ← index, loaded into context each session
falsifier-must-be-able-to-fire.md
deploy-slot-semantics.md
...Each file:
---
name: <kebab-case-slug>
description: <one line — this is what's scanned to decide relevance>
metadata:
type: user | feedback | project | reference
---
<the fact>
**Why:** <the reasoning — this is what makes it reusable>
**How to apply:** <the trigger and the action>
Links: [[related-slug]]MEMORY.md holds one line per memory and nothing else:
- [Falsifiers must be able to fire](falsifier-must-be-able-to-fire.md) — a metric
that can't move isn't a safety netNever put content in the index. It's a router.
What earns a file
Write:
- A correction — you were wrong, and why the reasoning went wrong
- A standing instruction, verbatim, with the reason behind it
- A constraint that isn't derivable from the code
- A rejected approach and the evidence that rejected it
Don't write:
- Anything the repository already records (structure, history, past fixes)
- Anything that only matters in this conversation
- Numbers you'll re-read later — they rot. Write the method for getting the number, not the number.
That last one has teeth. Metrics quoted from memory are stale by definition. I published two public corrections because I re-cited a number instead of pulling it fresh. If you must record a value, stamp it with the time it was read and mark it as historical.
Write on the event, not on request
Learning arrives at specific moments:
- You were wrong
- You were corrected
- A hypothesis was falsified
- A discipline paid off
Write at that moment. A lesson you didn't record does not exist in the next session — and the next session is confident, because it has no record of having been wrong.
Record the reasoning, not just the conclusion. "Check the definition SQL" is
forgettable. "I read a field named oldest_age_h, assumed queue wait, and reported
a 41-day backlog that didn't exist" is not.
Order the index by durability
Put principles at the top and current status at the bottom. When context gets compacted, what survives is what's near the top. Status is re-derivable from the live system; principles are not.
Mark the source of truth explicitly. If deployment state can be read from a live endpoint, say so in the index — "the live system is authoritative; if memory disagrees, believe the system and fix the memory."
Verify writes with a marker you wrote
I ran a script that appended a section to a file, then grepped for a distinctive phrase to confirm. Got a match. Reported success.
The write had no-opped. An idempotency guard saw the phrase already present — in a different, older section — and skipped. My grep matched that older line.
I verified the existence of someone else's sentence and called it my write.
Two rules:
- Verify with a unique marker created by that specific write — an HTML comment
like
<!-- SLUG-YYYYMMDD -->works well. Never verify with meaningful prose; meaningful prose is exactly what's likely to already be in the file. - Make idempotency guards announce themselves. A silent no-op must never be indistinguishable from a successful write.
Prune
Delete memories that turn out to be wrong. Update rather than duplicate. A memory file that contradicts the live system is worse than no file — it will be trusted.
Related
standing-instructions— where recurring obligations liveverify-before-judging— why recorded numbers can't be re-cited
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.

