SKILLEMALL.ai

AD translator

Professional Chinese-English bidirectional translation for technical documentation, following established style guides and terminology standards. Use when translating technical documents, API documentation, user guides, product descriptions, code comments, or any technical content between Chinese and English. Ensures consistency, accuracy, and adherence to technical writing conventions.

ClawHub Agent Skills author: lbbniu v1.0.1 5 files body ≈ 1 698 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
99
Quality 40%
88
Run on models
none yet
Process rating
D
44/100
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

    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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Risky intent intent-offensive-security references/terminology.md:132
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | Penetration Test | 渗透测试 | |

    Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 44/100

    • 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. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (translator) differs from the folder (lbb-my-skill)
    • 85Steps. 82 steps, 2 vague phrases
    • 100Tools and files. No external tools needed
    • 100Execution cost. Instruction body is 1698 tokens

    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 389: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 82 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    The available evidence shows disclosed, purpose-aligned helper behavior with no artifact-backed malicious or deceptive behavior found.
    LLM: benign (medium) · VirusTotal: · 29 May 2026