Skill: clarkchenkai/memory-taxonomist-clarkchenkai (version 1.0.0)

--- name: memory-taxonomist description: | Memory Taxonomist — Structured Memory Skill for Turning Raw Notes into Stable Knowledge. Use it when the user needs a disciplined protocol and fixed output contract for this kind of task rather than a generic answer. license: MIT metadata: author: clarkchenkai version: "1.0.0" language: en --- # Memory Taxonomist — Structured Memory Skill for Turning Raw Notes into Stable Knowledge Use this skill when the task matches the protocol below. ## Activation Triggers - new notes or transcripts that mix multiple information types - agent memory design or memory cleanup work - meeting outputs that contain decisions, preferences, and open questions together - requests to store user context safely for future retrieval - cases where retrieval quality matters more than storage volume ## Core Protocol ### Step 1: Break input into atomic claims Do not classify a whole paragraph as one memory object when it contains multiple types. ### Step 2: Classify each unit Sort it into fact, preference, procedure, unresolved question, or exception. ### Step 3: Separate durable from provisional Do not let recent mention automatically become durable truth. ### Step 4: Flag conflicts and edge cases Identify contradictions, overrides, and one-off exceptions before writing memory. ### Step 5: Recommend the right storage action Store, update, deprecate, or hold for clarification based on memory type and certainty. ## Output Contract Always end with this six-part structure: ```markdown ## Facts [...] ## Preferences [...] ## Procedures [...] ## Unresolved Questions [...] ## Exceptions [...] ## Recommended Storage Action [...] ``` ## Response Style - Prefer clean classification over verbose summary. - Treat unresolved questions as first-class memory objects. - Do not convert preferences into universal rules. - Call out exceptions instead of hiding them in procedures or facts. ## Boundaries - It does not store everything by default; some information should remain ephemeral. - It does not confuse recency with importance. - It does not turn uncertain statements into durable facts without evidence.

path: agents/openai.yaml
content: interface:
  display_name: "Memory Taxonomist"
  short_description: "Turn raw notes into typed, retrievable memory."
  default_prompt: "Use $memory-taxonomist to classify this information into facts, preferences, procedures, unresolved questions, and exceptions before storing it."

policy:
  allow_implicit_invocation: true


path: references/conflict-signals.md
content: # Conflict Signals

Watch for:

- a new fact that contradicts prior memory
- a preference that is actually role- or context-specific
- a procedure that contains hidden exceptions
- an unresolved question being mistaken for a conclusion


path: references/storage-rules.md
content: # Storage Rules

## Store
Stable facts, durable preferences, reusable procedures, and well-scoped exceptions.

## Update
When a new statement clearly supersedes old memory.

## Hold
When evidence is weak or uncertainty is still active.

## Deprecate
When the memory is contradicted or replaced.


path: references/taxonomy.md
content: # Memory Taxonomy

Use these types:

- Facts: stable statements believed true enough to reuse
- Preferences: user, team, or stakeholder style or choice preferences
- Procedures: reusable steps, workflows, or runbooks
- Unresolved Questions: unknowns that should remain visible
- Exceptions: overrides, caveats, and context-specific departures


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)