SKILLEMALL.ai

AC weekly-report-framework

智能装备研究所项目周报管理框架V2.5。用于研究室经理生成周报给所长汇报。触发条件:提到"周报"、"生成周报"、"导出周报"、"项目周报"、"研究室周报"。支持三种初始化方式(md模板/对话式/Excel模板)。包含11阶段生命周期、双表格簿结构、12列字段定义、群聊抓取、增量迭代、异常检测(V2.5新增)、学习迭代。

ClawHub Agent Skills author: paudyyin v1.0.0 MIT-0 8 files body ≈ 1 553 tokens Open the sourceclawhub.ai analyzed 3 d ago

智能装备研究所项目周报管理框架V2.5。用于研究室经理生成周报给所长汇报。触发条件:提到"周报"、"生成周报"、"导出周报"、"项目周报"、"研究室周报"。支持三种初始化方式(md模板/对话式/Excel模板)。包含11阶段生命周期、双表格簿结构、12列字段定义、群聊抓取、增量迭代、异常检测(V2.5新增)、学习迭代。

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureExcelData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description 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. 73 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1553 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 160: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 73 items
  • +4Has examples (12 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: 79.

External checks

ClawHub: suspicious
The skill is a coherent weekly-report assistant, but it needs Review because it can collect workplace chat history and retain chat-derived records permanently.
LLM: suspicious (high) · 3 Aug 2026