BD zwjh-skill
统一记忆底座：长期记忆 + 知识图谱 + 自动沉淀 + 检索。让 AI「记得你」，跨会话持久记忆、实体/关系图谱、语义与时间线检索、记忆健康度审计、本地备份（可接百度网盘）。纯本地、零密钥、按硬件自适应，不拖累电脑。并保留 v1.7 的根因分析/预测性维护/进化报告。
统一记忆底座：长期记忆 + 知识图谱 + 自动沉淀 + 检索。让 AI「记得你」，跨会话持久记忆、实体/关系图谱、语义与时间线检索、记忆健康度审计、本地备份（可接百度网盘）。纯本地、零密钥、按硬件自适应，不拖累电脑。并保留 v1.7 的根因分析/预测性维护/进化报告。
As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Dangerous commands
cmd-persistencescripts/setup.py:45Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)f'schtasks /create /tn "{TASK_NAME}" /tr "{tr_escaped}" 'code literal
Files scanned: 29. 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")
Process rating: all ten parameters 43/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 118 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3526 tokens
- low 13 top-level sections: this looks like several domains in one skill
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
- -2localhost URLs: will not work for another user
- -313 of 24 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 134: enough signal without eating the budget
- +4Structure: 46 headings
- +3Step-by-step instructions: 118 items
- +4Has examples (25 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.