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create-new-ref

Systematically add a new memory-system reference to Auto_Memory's reference hub. Use when analyzing a new agent memory system, adding reference/<system>/details.md, saving prompts, or updating reference/hub/technique_map.json.

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包含的文件(1)

  • SKILL.md6.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Create New Reference

Use this skill when adding a new memory system to reference/ and reference/hub/technique_map.json.

The goal is not to summarize a repo. The goal is to distill reusable memory-system design moves that a coding agent can adapt to another agent.

Output Contract

For a new system named <system>:

reference/<system>/
├── details.md
└── prompts/
    └── <prompt-name>.md

Then append high-quality technique entries to reference/hub/technique_map.json.

Use existing systems as examples:

  • reference/zep/details.md
  • reference/open-viking/details.md
  • reference/MIRIX/details.md
  • reference/lightgrep/details.md
  • reference/template/details.md
  • reference/template/technique_map_slot.json

Workflow

1. Inspect the Memory System

Read enough source/docs to identify production behavior:

  • Where memory is written: lifecycle hook, tool call, session end, context-window pressure, explicit user request, batch job.
  • What the memory units are: facts, events, observations, tool lessons, user profile, graph edges, summaries, cache entries.
  • How memory is updated: append, merge, overwrite, invalidate, archive, delete, dedup.
  • How memory is retrieved: always-in-context, keyword/BM25, vector candidate generation, graph traversal, hierarchical search, LLM scoring, reranking, on-demand drilldown.
  • How memory is bounded: token limits, TTL, hotness, compaction, archival, retention windows.
  • What is agent-specific: lifecycle integration, tool schemas, prompt format, storage constraints, latency budget.

Prefer implementation evidence over README claims. If prompts drive behavior, save the prompt text.

2. Write details.md

Follow the 8-section structure from reference/template/details.md:

  1. System architecture: include an ASCII flow diagram and component responsibilities.
  2. Data model and schema: memory types, fields, update semantics.
  3. Storage and indexing: backend, indexes, retrieval unit, partitioning.
  4. Retrieval logic: candidate generation, filtering, ranking/reranking, formatting.
  5. Store and update logic: triggers, extraction, normalization, dedup, validation.
  6. Consolidation and lifecycle: TTL, compaction, archival, conflict/staleness handling.
  7. Important implementation details: key classes/functions and non-obvious engineering decisions.
  8. Transferability notes: reusable parts, tightly coupled parts, best-fit agent/workflow.

Keep it implementation-oriented. Do not dump source files. Include line-level concepts and exact names of important classes/functions when useful.

3. Save Key Prompts

Put important LLM prompts in reference/<system>/prompts/.

Save prompts that define memory behavior:

  • extraction/classification prompts
  • dedup/merge/conflict prompts
  • retrieval planning/ranking prompts
  • compression/consolidation prompts
  • router/meta-memory prompts
  • sufficiency/validation prompts

Do not save generic chat prompts unless they directly control memory behavior.

4. Extract Techniques

Create technique entries only for reusable design moves. A valid technique must answer:

  • What problem does this solve?
  • What is the mechanism?
  • When does it help?
  • What does it cost?
  • What kind of agent should borrow it?

Use categories from reference/hub/technique_map.json:

  • extraction
  • dedup_conflict
  • storage_organization
  • retrieval_ranking
  • lifecycle
  • architecture

Use philosophy tags:

  • weight: lightweight, medium, or heavy
  • logic: rigorous, intelligent, or both

5. Insight Quality Bar

Do not record obvious infrastructure as an insight.

Hard rule: do not treat simple embedding/vector search as an insight. A technique may mention vector search only when it is part of a richer mechanism, such as vector pre-filter + LLM dedup, hierarchical traversal, multi-signal reranking, hotness blending, or fallback selection.

Good techniques look like:

  • lifecycle hook selection tied to agent events
  • memory-type routing with different schemas and tools
  • temporal invalidation instead of overwrite
  • two-stage retrieval with sufficiency gates
  • progressive disclosure with token-cost visibility
  • L0/L1/L2 memory representations
  • hotness-driven archival
  • tool-execution observations as the memory source
  • crash-safe redo logs for memory extraction
  • prompt-cache-friendly session cursors

Reject techniques that are only:

  • "uses embeddings"
  • "stores in a vector database"
  • "summarizes conversation"
  • "uses SQLite/Postgres"
  • "has a prompt"
  • "uses RAG"

If the technique is common, only include it when the system has a specific adaptation, invariant, or engineering constraint that makes it transferable.

6. Add Technique Map Entries

Append entries matching reference/template/technique_map_slot.json:

{
  "id": "<system>-<short-name>",
  "name": "<Technique name in plain English>",
  "source": "<system>",
  "category": "extraction",
  "summary": "<what it does and how>",
  "tradeoffs": "<cost vs benefit>",
  "when_to_use": "<scenario where it shines>",
  "philosophy": {
    "weight": ["medium"],
    "logic": ["intelligent"]
  },
  "detail_refs": [
    { "file": "<system>/details.md", "lines": [10, 25] }
  ],
  "prompt_refs": [
    "<system>/prompts/<prompt-name>.md"
  ]
}

Rules:

  • id must be unique and stable.
  • source must match the directory name under reference/.
  • detail_refs must point to exact line ranges in details.md.
  • prompt_refs should include only saved prompts that support this technique.
  • summary, tradeoffs, and when_to_use should each be one concise sentence.
  • Do not add a technique unless details.md contains enough evidence to support it.

7. Validate

Before finishing:

  • Confirm reference/<system>/details.md exists and uses the 8-section structure.
  • Confirm every prompt_refs path exists.
  • Confirm every detail_refs.file exists and line ranges are meaningful.
  • Confirm technique_map.json is valid JSON.
  • Confirm the new techniques are not duplicates of existing entries.
  • Confirm no real API keys, private keys, tokens, credentials, or .env files were added.
  • Confirm no technique violates the simple-embedding rule.

If ask_ref is installed, smoke test:

ask_ref grep "<system>"
ask_ref cat "<new-technique-id>"

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