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碳阻迹（Carbonstop）CCDB 碳排放因子与排放系数查询、比较和匹配。当用户需要电力、天然气、柴油、汽油、煤炭、水泥、钢材、铝材、塑料、运输、包装或食品等活动与材料的真实排放因子（emission factor），或为产品碳足迹（PCF / carbon footprint）、企业碳核算及生命周期评价（LCA）查找和选择因子时使用。支持按国家/地区、年份等条件检索，核对单位、系统边界、技术规格及数据来源，并比较候选因子的适用性。

ClawHub Agent Skills author: Carbonstop | 碳阻迹 v1.0.0 MIT-0 2 files body ≈ 947 tokens Open the sourceclawhub.ai↗ analyzed 35 h ago

碳阻迹（Carbonstop）CCDB 碳排放因子与排放系数查询、比较和匹配。当用户需要电力、天然气、柴油、汽油、煤炭、水泥、钢材、铝材、塑料、运输、包装或食品等活动与材料的真实排放因子（emission factor），或为产品碳足迹（PCF / carbon…

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationGitHubAI and agentsDesignSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 58/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 947 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 220: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill’s CCDB lookup instructions are coherent, but it asks users to globally install a changing third-party CLI, so it should be reviewed before use.
LLM: suspicious (high) · VirusTotal: · 8 Sept 2026