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CC Contacts

查询、创建、更新或删除联系人。当用户要查电话、看联系方式、存号码、补充联系人信息或删除联系人时使用。

The skillemall take

The skill promises contact management: search, create, update, delete. Three files, no scripts. Security score is perfect, but quality landed at 57 out of 100—rough draft territory. Process score sits at 51. No critical findings, but the code needs cleanup work.

Never tested on a model, no sandbox run. Platform coverage is broad: Claude, Cursor, Gemini, Copilot, Qwen and a dozen more. Install if you need contacts now and don't mind working through the rough edges.

kellyvv/PhoneClaw Agent Skills author: kellyvv 3 files body ≈ 706 tokens Open the sourcegithub.com↗ analyzed 4 d ago

查询、创建、更新或删除联系人。当用户要查电话、看联系方式、存号码、补充联系人信息或删除联系人时使用。

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

Proceduretype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
57
Run on models
none yet
Process rating
C
51/100
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "name-zh"
  • note frontmatter-key unknown frontmatter key "icon"
  • note frontmatter-key unknown frontmatter key "disabled"
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "chip_prompt"
  • note frontmatter-key unknown frontmatter key "chip_label"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "side_effects"
  • note frontmatter-key unknown frontmatter key "examples"

Process rating: all ten parameters 51/100

  • 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
  • 30Running it twice. 9 mutating operations with no state check
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 38 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 706 tokens
  • low The response is described with custom markup (9 tags): a typed call is more reliable

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)
  • +3Description length 50: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 38 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.