DC heartbeat-memory
自动记忆保存 Skill。支持 Heartbeat 自动触发和主 Agent 中手动调用两种方式。自动检查新 sessions，生成 Daily 笔记，定期提炼 MEMORY.md，支持备份已删除的 sessions。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.
Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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 · 3
-
high Obfuscation
uni-zero-widthreferences/config.md:11Zero-width / invisible characters (possible hidden text) (15 occurrences)**默认工作区（单 Agent 用户）：␀**
-
high Obfuscation
uni-zero-widthreferences/troubleshooting.md:6Zero-width / invisible characters (possible hidden text) (28 occurrences)> - **相对路径（`./`）␀**：在工作区目录下执行，适用于所有工作区，无需替换。
-
high Obfuscation
uni-zero-widthSKILL.md:16Zero-width / invisible characters (possible hidden text) (19 occurrences)**特点：␀**
Files scanned: 15. 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 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 34 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1773 tokens
- 100Running it twice. No mutating operations
- low 10 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)
- +3Description length 109: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -233 emoji in the instructions: noise for the model
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 34 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (16 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.