AC task-memory
任务遗忘防护系统 — 解决 AI Agent 任务发出但未执行的记忆漏洞问题。 当需要创建、追踪、管理长期任务时使用，特别是：提出或承诺了某项计划后、设置 cron/自动化任务时、任务状态变更后、晨间/心跳检查时。 核心功能：通过 todo.json 持久化任务状态，todo_manager.py 管理增/查/改/完成，系统自动追踪不过期。
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedurePersonal productivityInfrastructureAI and agentstype and topics are labelled automatically from the skill text
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: 5. 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 51/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 19 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 773 tokens
- 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)
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +3Description length 171: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +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 useful local task-memory skill, but it needs review because it stores durable task data, runs on broad automatic triggers, describes external QQ/IM reminders, uses an unexpected hard-coded write path, and ships with active finance-related task records.
LLM: suspicious (high) · VirusTotal: · 29 May 2026