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🧠 Persistent Agent Memory 1.0.1 — 技能工具

v1.0.0

[自动翻译] Add persistent memory to any agent so it can remember prior work, maintain context across sessions, and continue long-running workflows.

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by @gyzx·MIT-0
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License
MIT-0
最后更新
2026/4/11
安全扫描
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OpenClaw
可疑
medium confidence
The skill's purpose (persistent memory via Coral Bricks) is plausible and the requested API key is expected, but there are multiple mismatches and missing pieces (referenced scripts not included, metadata inconsistencies, and an undeclared environment variable) that make the package internally inconsistent.
评估建议
This skill appears to implement persistent memory via the Coral Bricks API and asking for CORAL_API_KEY is expected. However: (1) the SKILL.md references helper scripts (scripts/coral_store, coral_retrieve, coral_delete_matching) that are not included — ask the publisher for the scripts or concrete curl/python examples so you know exactly what will be sent to the Coral endpoint; (2) the _meta.json ownerId and the registry owner ID/version differ — verify the publisher identity and version integr...
详细分析 ▾
用途与能力
The declared purpose (store/retrieve agent memory using Coral Bricks) aligns with requiring a CORAL_API_KEY and network-capable binaries (curl/python3). However the SKILL.md consistently references local helper scripts (scripts/coral_store, scripts/coral_retrieve, scripts/coral_delete_matching) even though this is an instruction-only skill with no script files or install spec. That mismatch makes it unclear how the agent is expected to perform the described operations.
指令范围
The runtime instructions direct the agent to run local scripts under scripts/ to call the Coral API, but no scripts or code are included. The SKILL.md also references an optional CORAL_API_URL environment variable that is not declared in the skill metadata. Aside from sending data to the coralbricks.ai endpoint (expected for the feature), the instructions do not ask the agent to read unrelated system files or other credentials.
安装机制
This is instruction-only with no install spec and no code written to disk, which is the lowest-risk install posture. Required binaries are standard (curl, python3). Because nothing is downloaded or extracted as part of install, there's no additional install risk from the provided manifest.
凭证需求
Only a single primary credential (CORAL_API_KEY) is required, which is proportionate to the declared purpose. However SKILL.md mentions an optional CORAL_API_URL env var that is not listed under requires.env, and the skill instructs exporting CORAL_API_KEY locally — the missing declaration of CORAL_API_URL is a minor inconsistency to be aware of.
持久化与权限
The skill does not request always:true and does not claim elevated platform privileges. Autonomous invocation is enabled (default) which is typical for skills. No instructions attempt to modify other skills or system-wide agent settings.
安全有层次,运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发,无需署名。

运行时依赖

无特殊依赖

版本

latestv1.0.02026/3/15

- Initial release of persistent-agent-memory skill. - Enables any agent to store, retrieve, and delete persistent memories powered by Coral Bricks. - Stores all content in the default collection, allowing context to persist across agent sessions and long-running workflows. - Provides three command-line tools: coral_store, coral_retrieve, and coral_delete_matching for managing memories by meaning. - Allows attaching free-form JSON metadata to memories. - Setup requires a CORAL_API_KEY; optional API URL override supported.

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安装命令 点击复制

官方npx clawhub@latest install persistent-agent-memory-1-0-1
镜像加速npx clawhub@latest install persistent-agent-memory-1-0-1 --registry https://cn.clawhub-mirror.com

技能文档

Memory storage and retrieval powered by Coral Bricks. Store facts, preferences, and context; retrieve them later by meaning. All memories are stored in the default collection.

Use when: (1) remembering facts or preferences for later, (2) recalling stored memories by topic or intent, (3) forgetting/removing memories matching a query.

NOT for: web search, file system search, or code search — use other tools for those.

Setup

Set your API key (get one at https://coralbricks.ai):

export CORAL_API_KEY="ak_..."

Optionally override the API URL (defaults to https://search-api.coralbricks.ai):

export CORAL_API_URL="https://search-api.coralbricks.ai"

Tools

coral_store — Store a memory

Store text with optional metadata for later retrieval by meaning.

scripts/coral_store "text to store" [metadata_json]
  • text (required): Content to remember
  • metadata_json (optional): JSON string of metadata, e.g. '{"source":"chat","topic":"fitness"}'

Output: JSON with status (e.g. {"status": "success"}).

Example:

scripts/coral_store "User prefers over-ear headphones with noise cancellation"
scripts/coral_store "Q3 revenue was $2.1M" '{"source":"report"}'

coral_retrieve — Retrieve memories by meaning

Retrieve stored memories by semantic similarity. Returns matching content ranked by relevance.

scripts/coral_retrieve "query" [k]
  • query (required): Natural language query describing what to recall
  • k (optional, default 10): Number of results to return

Output: JSON with results array, each containing text and score.

Example:

scripts/coral_retrieve "wireless headphones preference" 5
scripts/coral_retrieve "quarterly revenue" 10

coral_delete_matching — Forget memories by query

Remove memories that match a semantic query. Specify what to forget by meaning.

scripts/coral_delete_matching "query"
  • query (required): Natural language query describing memories to remove

Output: JSON confirming the operation completed.

Example:

scripts/coral_delete_matching "dark mode preference"
scripts/coral_delete_matching "forget my workout notes"

Privacy

Privacy Policy

Notes

  • All memories are stored in the default collection; collections are not exposed to the agent
  • All text is embedded into 768-dimensional vectors for semantic matching
  • Results are ranked by cosine similarity (higher score = more relevant)
  • Stored memories persist across sessions
  • The metadata field is free-form JSON; use it to tag memories for easier filtering
  • For more details and examples, see Persistent Agent Memory for AI Agents

Indexing delay (store then retrieve)

In rare cases, memories can take up to 1 second to become retrievable right after storage.

数据来源:ClawHub ↗ · 中文优化:龙虾技能库
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