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AC can-free

CAN免费版提供基于Clock Address Naming的核心内容寻址能力. 每条事件一行三列：WHEN（unix毫秒）、WHERE（sha256哈希）、WHAT（可读名称）， 支持本地append-only日志与三问自评估. 核心能力： - 三列协议基础记录 - 内容哈希校验 - 本地append-only日志 - 三问自评估 升级付费版专享：评估端点校验、篡改证明告警、并行索引、OTS时间戳同步、跨管道编码规范化.

ClawHub Hermes author: 天轰穿 v1.0.3 MIT-0 2 files body ≈ 2 084 tokens Open the sourceclawhub.ai↗ analyzed 26 h ago

CAN免费版提供基于Clock Address Naming的核心内容寻址能力.

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

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
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. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 213 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "summary_zh"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "homepage"

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. Tools declared in frontmatter
  • 100Steps. 73 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2084 tokens
  • 100Running it twice. No mutating operations
  • low 25 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
  • +2Single-language instructions
  • +3Description length 213: enough signal without eating the budget
  • +4Structure: 55 headings
  • +3Step-by-step instructions: 73 items
  • +4Has examples (5 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
The skill mainly describes local content hashing and logging, but it also requests broad read/write/exec authority and contains inconsistent callback, API, network, and command-execution claims that users should review before installing.
LLM: suspicious (high) · 2 Aug 2026