AD smart-agent-memory
跨平台 Agent 长期记忆系统。分层上下文供给 + 温度模型 + Skill经验记忆 + 结构化存储 + 自动归档。三层存储：Markdown（人可读，QMD 可搜索）+ JSON（结构化）+ SQLite/FTS5（高性能全文搜索）。纯 Node.js 原生模块，零外部依赖。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
This is a copy of a skill from another catalog; the rating counts the canonical one: smart-agent-memory (ClawHub)
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "keywords"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (smart-agent-memory) differs from the folder (smart-agent-memory-cn)
- 100Tools and files. No external tools needed
- 100Steps. 12 steps
- 100Execution cost. Instruction body is 1334 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 140: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (10 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.
External checks
ClawHub: suspicious
This is a real local memory tool, but it needs review because it stores broad conversation data and can generate new agent skills in the live skills directory.
LLM: suspicious (high) · VirusTotal: · 29 May 2026