SKILLEMALL.ai

BD ortho-expo-contacts

骨科展会名录合规查询工具。覆盖 AAOS 2026、OMTEC 2025、DKOU 2026、AAHKS 2025、AOSSM 2025、SOFCOT 2025 共 2600+ 条参展商与参会者记录,内置实名登记、反骚扰承诺、配额限速、撞车提醒、拒访名单与哈希链审计四道闸门。当用户要查骨科展会联系方式、找某国参展商、找某类产品供应商、查 OMTEC 参会人、整理展会名录时使用。

ClawHub Hermes author: zhaoxinghua09-cell v1.1.0 MIT-0 11 files body ≈ 1 204 tokens Open the sourceclawhub.ai analyzed 3 d ago

骨科展会名录合规查询工具。覆盖 AAOS 2026、OMTEC 2025、DKOU 2026、AAHKS 2025、AOSSM 2025、SOFCOT 2025 共 2600+…

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
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.
  2. 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: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 190 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "description_en"

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. 12 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1204 tokens
  • 100Running it twice. No mutating operations
  • low 11 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 190: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 12 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 3 scripts are documented
  • +1License stated

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

External checks

ClawHub: clean
This skill is a local contact-directory lookup tool with disclosed safeguards and no evidence of hidden data export or unsafe automatic behavior.
LLM: benign (high) · VirusTotal: · 4 Sept 2026