SKILLEMALL.ai

BD cue-global-macro

用 Cue 跑「全球宏观」场景的深度研究:追踪全球主要经济体的通胀、GDP、就业与对外贸易官方读数,横向对比各国宏观表现。覆盖全球通胀监测、经济体宏观体检、全球央行利率与汇率追踪、跨国宏观对比、港新枢纽宏观等核心搭子,用官方数据看清各经济体在全球版图中的相对位置,支撑跨境配置、出海选址与宏观研判。

ClawHub Agent Skills author: wangxiaoxu v1.0.1 MIT-0 2 files body ≈ 518 tokens Open the sourceclawhub.ai analyzed 3 d ago

用 Cue 跑「全球宏观」场景的深度研究:追踪全球主要经济体的通胀、GDP、就业与对外贸易官方读数,横向对比各国宏观表现。覆盖全球通胀监测、经济体宏观体检、全球央行利率与汇率追踪、跨国宏观对比、港新枢纽宏观等核心搭子,用官方数据看清各经济体在全球版图中的相对位置,支撑跨境配置、出海选址与宏观研判。

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 2. 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 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 518 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
  • +2Single-language instructions
  • +3Description length 149: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This skill is a disclosed Cue macroeconomic research workflow that uses public data and requires user confirmation before spending credits.
LLM: benign (high) · VirusTotal: · 11 Aug 2026