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agent-memory

Harga belum dikonfirmasi★ 25,064 Star GitHubDirektori diperbarui · 1 Sep 2026agent-skill

Ringkasan

Use when a project's CLAUDE.md has grown past what anyone reads and you want the agent to learn durable facts from its own sessions instead — or when asking why the agent keeps re-learning the same correction, why a remembered rule is wrong, or where a memory line came from. Implements a four-tier store (L0 transcripts / L1 candidates / L2 project context / L3 stable persona) where promotion is earned by recurrence across sessions and days, never by one confident statement, and nothing reaches a committed file without a human adopting it.

Baca dokumentasi lengkap

Dokumentasi sumber, bukan instruksi untuk situs ini. Periksa izin sebelum menjalankan perintah.

Agent Memory — promotion is earned, not asserted

Portability: stdlib only. No database, no embeddings, no network, no LLM calls.

The problem

A project's CLAUDE.md is a memory system with one tier and no eviction: every durable fact and every passing preference land in the same always-loaded file, until the important lines are diluted by the incidental ones. Facts learned mid-session vanish at teardown unless someone writes them down.

The fix is not more storage — it is a promotion ladder. A claim earns its way toward always-loaded context by recurring; a human confirms the last step.

The four tiers

Tiers are distinguished by injection policy, not storage format.

Tier	Holds	Injected	Committed
L0	raw session transcripts	never	no (already on disk)
L1	candidate atoms	on relevance, at prompt time	no (gitignored)
L2	this project's context	every session start	yes, after adopt
L3	stable cross-project persona	always	yes, after adopt

The gates

Nothing moves up because it sounded important. It moves up because it recurred.

L0 → L1 — an explicit marker fires (a directive, a correction, a stated preference, a named lesson, a reproducible failure). Rule-based, high precision, deliberately low recall.
L1 → L2 — ≥ 3 distinct sessions spanning ≥ 2 distinct calendar days. A claim stated outright needs 2 sessions; the distinct-day rule still applies. A verified claim promotes on one observation and is the only day-exempt path.
L2 → L3 — held in ≥ 2 distinct projects, aged ≥ 30 days, uncontested.

Two gates refuse rather than guess. A claim whose text was altered by redaction never promotes on evidence alone — the flag firing is evidence the source was sensitive, and a lexical filter finding one secret is not proof it found all of them. A claim with an open contradiction is frozen at L1 until a human resolves it; the incumbent is never silently overwritten.

Use it

# what is remembered, and what is blocking the next promotion
python3 scripts/memory_inspect.py --tier L1

# where did this line come from — sessions, days, transcript, quoted source
python3 scripts/memory_inspect.py --why "PR base branch is dev"

# every claim with an open contradiction, both directions of the join
python3 scripts/memory_inspect.py --contested

# dry-run the promotion pass; writes nothing
python3 scripts/memory_promote.py

Three hooks run the loop unattended: SessionStart injects L2 + L3, UserPromptSubmit recalls relevant L1 atoms, SessionEnd captures and stages. Each is disabled independently with AGENT_MEMORY_SESSIONSTART=0, AGENT_MEMORY_USERPROMPTSUBMIT=0, AGENT_MEMORY_SESSIONEND=0. Every hook fails open: a broken memory system costs you memory, never a session.

Hard rules

Redact before writing. Every atom passes the filter before it reaches disk. Anything altered is quarantined from promotion.
Propose, never apply. Promotions land in .memory/staged/. Only an explicit /cs:memory adopt touches a CLAUDE.md, and it backs both up first.
Cite, don't invent. Every atom carries a back-pointer to the transcript line that produced it. --why resolving to ambiguous prints nothing rather than guess: a wrong citation is worse than a missing one.
Never surface a contested claim as fact. It is still injected — hiding the conflict is worse — but always tagged.
The committed tiers carry no paths. Promotion strips the back-pointer prefix, which embeds an OS username.

Forcing questions

Walk these one at a time before trusting the store.

Which line in your CLAUDE.md did you last actually read before acting?
Would you rather the agent forget a true thing, or remember a false one?
When two remembered rules disagree, who decides — and when?
What would make you delete .memory/ entirely?

Rationale, open decisions, field schema: ../../DESIGN.md.

Lihat sumber ↗

Metadata berkas

name: agent-memory
description: Use when a project's CLAUDE.md has grown past what anyone reads and you want the agent to learn durable facts from its own sessions instead — or when asking why the agent keeps re-learning the same correction, why a remembered rule is wrong, or where a memory line came from. Implements a four-tier store (L0 transcripts / L1 candidates / L2 project context / L3 stable persona) where promotion is earned by recurrence across sessions and days, never by one confident statement, and nothing reaches a committed file without a human adopting it.
argument-hint: "[optional: status | why \"<claim>\" | a tier name]"
license: MIT
metadata:
  version: 1.0.0
  build_pattern: "Tencent TencentDB-Agent-Memory's tiering concept rebuilt natively on Claude Code hooks; deterministic recurrence gates, no LLM, no database"
  distinct_from: "llm-wiki (a vault you write on purpose; this writes itself from sessions); skillopt-sleep (replays tasks to improve a skill; this extracts facts to remember); memory-engineering (audits and prices any memory system; this IS one, and is a legitimate subject of that audit)"

Lihat teks asli

---
name: agent-memory
description: Use when a project's CLAUDE.md has grown past what anyone reads and you want the agent to learn durable facts from its own sessions instead — or when asking why the agent keeps re-learning the same correction, why a remembered rule is wrong, or where a memory line came from. Implements a four-tier store (L0 transcripts / L1 candidates / L2 project context / L3 stable persona) where promotion is earned by recurrence across sessions and days, never by one confident statement, and nothing reaches a committed file without a human adopting it.
argument-hint: "[optional: status | why \"<claim>\" | a tier name]"
license: MIT
metadata:
version: 1.0.0
build_pattern: "Tencent TencentDB-Agent-Memory's tiering concept rebuilt natively on Claude Code hooks; deterministic recurrence gates, no LLM, no database"
distinct_from: "llm-wiki (a vault you write on purpose; this writes itself from sessions); skillopt-sleep (replays tasks to improve a skill; this extracts facts to remember); memory-engineering (audits and prices any memory system; this IS one, and is a legitimate subject of that audit)"
---

# Agent Memory — promotion is earned, not asserted

> **Portability:** stdlib only. No database, no embeddings, no network, no LLM calls.

## The problem

A project's `CLAUDE.md` is a memory system with one tier and no eviction: every
durable fact and every passing preference land in the same always-loaded file,
until the important lines are diluted by the incidental ones. Facts learned
mid-session vanish at teardown unless someone writes them down.

**The fix is not more storage — it is a promotion ladder.** A claim earns its
way toward always-loaded context by recurring; a human confirms the last step.

## The four tiers

Tiers are distinguished by **injection policy**, not storage format.

| Tier | Holds | Injected | Committed |
|---|---|---|---|
| **L0** | raw session transcripts | never | no (already on disk) |
| **L1** | candidate atoms | on relevance, at prompt time | no (gitignored) |
| **L2** | this project's context | every session start | yes, after adopt |
| **L3** | stable cross-project persona | always | yes, after adopt |

## The gates

Nothing moves up because it sounded important. It moves up because it recurred.

- **L0 → L1** — an explicit marker fires (a directive, a correction, a stated
preference, a named lesson, a reproducible failure). Rule-based, high
precision, deliberately low recall.
- **L1 → L2** — ≥ 3 distinct sessions spanning ≥ 2 distinct calendar days. A
claim stated outright needs 2 sessions; the distinct-day rule still applies. A
verified claim promotes on one observation and is the only day-exempt path.
- **L2 → L3** — held in ≥ 2 distinct projects, aged ≥ 30 days, uncontested.

**Two gates refuse rather than guess.** A claim whose text was altered by
redaction never promotes on evidence alone — the flag firing is evidence the
source was sensitive, and a lexical filter finding one secret is not proof it
found all of them. A claim with an open contradiction is frozen at L1 until a
human resolves it; the incumbent is never silently overwritten.

## Use it

```bash
# what is remembered, and what is blocking the next promotion
python3 scripts/memory_inspect.py --tier L1

# where did this line come from — sessions, days, transcript, quoted source
python3 scripts/memory_inspect.py --why "PR base branch is dev"

# every claim with an open contradiction, both directions of the join
python3 scripts/memory_inspect.py --contested

# dry-run the promotion pass; writes nothing
python3 scripts/memory_promote.py
```

Three hooks run the loop unattended: `SessionStart` injects L2 + L3,
`UserPromptSubmit` recalls relevant L1 atoms, `SessionEnd` captures and stages.
Each is disabled independently with `AGENT_MEMORY_SESSIONSTART=0`,
`AGENT_MEMORY_USERPROMPTSUBMIT=0`, `AGENT_MEMORY_SESSIONEND=0`. Every hook fails
open: a broken memory system costs you memory, never a session.

## Hard rules

1. **Redact before writing.** Every atom passes the filter before it reaches
disk. Anything altered is quarantined from promotion.
2. **Propose, never apply.** Promotions land in `.memory/staged/`. Only an
explicit `/cs:memory adopt` touches a `CLAUDE.md`, and it backs both up first.
3. **Cite, don't invent.** Every atom carries a back-pointer to the transcript
line that produced it. `--why` resolving to *ambiguous* prints nothing rather
than guess: a wrong citation is worse than a missing one.
4. **Never surface a contested claim as fact.** It is still injected — hiding
the conflict is worse — but always tagged.
5. **The committed tiers carry no paths.** Promotion strips the back-pointer
prefix, which embeds an OS username.

## Forcing questions

Walk these one at a time before trusting the store.

1. Which line in your `CLAUDE.md` did you last actually read before acting?
2. Would you rather the agent forget a true thing, or remember a false one?
3. When two remembered rules disagree, who decides — and when?
4. What would make you delete `.memory/` entirely?

Rationale, open decisions, field schema: [`../../DESIGN.md`](../../DESIGN.md).

Tinjau sumber

Harga dan biaya penggunaan

Dapatkan skill: Harga belum dikonfirmasi
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Lisensi: MIT
Harga belum dikonfirmasi: Harga belum dikonfirmasi. Tautan sumber dan instalasi yang ada tetap tersedia.

Gratis diperoleh bukan berarti gratis dijalankan. Harga bukan penilaian keamanan. Kirim informasi harga →

Sumber skill tercatat

Jalur instruksi telah dicatat. Ini bukan uji eksekusi, jaminan keamanan, atau sertifikasi kompatibilitas.

Tinjau sebelum memasang: Hindari pemasangan otomatis

Lisensi: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
The provided SKILL.md excerpt is truncated and may lack a complete 'Setup' or 'Installation' section, which could be present in the full file but not visible here.
The skill relies on custom scripts and hooks; without explicit installation instructions, users may not know how to correctly wire the hooks into Claude Code.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Buka audit lengkap

Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.

Mulai dengan tugas kecil

1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.

Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.

Sumber dan catatan penggunaan

Terindeks

Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.

Repositori sumber: alirezarezvani/claude-skills
Lisensi: MIT
Versi: 1.0.0
Push GitHub terakhir: 27 Agu 2026
Direktori diperbarui: 1 Sep 2026
Jalur instruksi: .gemini/skills/agent-memory/SKILL.md

Versi dilaporkan dalam metadata direktori; periksa rilis sumber.

Kualitas

88/100

Sangat baik

Kepercayaan

62/100

Hanya sandbox

Audit

80/100

Perlu ditinjau

Buka audit lengkap Lihat laporan evaluasi

Dependency or permission surface needs review
Permission surface may require sandboxing
The provided SKILL.md excerpt is truncated and may lack a complete 'Setup' or 'Installation' section, which could be present in the full file but not visible here.
The skill relies on custom scripts and hooks; without explicit installation instructions, users may not know how to correctly wire the hooks into Claude Code.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Hasil: —

Menyalin bukan memasang. Jumlah instalasi memerlukan laporan berhasil dan bukan jaminan kualitas menyeluruh.

Akses agent

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka API pemasangan Format teks LLM Buka Manifest Rencana resolusi otomatis

Detail lainnya

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  "trust": {
    "score": 70,
    "label": "Manual review",
    "version": "trust-score-v4",
    "install_policy": "block",
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      "stars": "25K GitHub stars",
      "repoActivity": "25K stars, 3.5K forks",
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  "quality": {
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    "scenario": "Workflow automation",
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    "No OpenAgentSkill engagement data yet",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
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      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "alirezarezvani-agent-memory",
      "task": "Use agent-memory in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/alirezarezvani-agent-memory",
    "api": "https://www.openagentskill.com/api/agent/skills/alirezarezvani-agent-memory",
    "audit": "https://www.openagentskill.com/skills/alirezarezvani-agent-memory/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=alirezarezvani-agent-memory&task=Use%20agent-memory%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20agent-memory%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20agent-memory%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/alirezarezvani-agent-memory/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/alirezarezvani-agent-memory"
  }
}

Untuk kreator

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator: alirezarezvani
Sumber: alirezarezvani/claude-skills
Diindeks oleh: Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan alirezarezvani, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit berbagi

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/alirezarezvani-agent-memory?metric=listed&label=Listed)](https://www.openagentskill.com/skills/alirezarezvani-agent-memory?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/alirezarezvani-agent-memory?metric=trust&label=Trust)](https://www.openagentskill.com/skills/alirezarezvani-agent-memory?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/alirezarezvani-agent-memory?metric=audit&label=Audit)](https://www.openagentskill.com/skills/alirezarezvani-agent-memory/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/alirezarezvani-agent-memory?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/alirezarezvani-agent-memory?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

Pratinjau badge Buka audit Kit kreator

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.