SKILLEMALL.ai

BC xingtuTaskAuthor

This skill should be used when the user needs to query the registered author list for a XingTu (星图) recruitment task. It fetches all registered influencers from the XingTu platform via the provider_get_task_author_list API, handles login/cookie management, paginates through all results, and exports the data to a formatted Excel file. Trigger phrases include: 星图任务达人, 查星图报名达人, 获取星图作者列表, xingtu task authors, 星图任务 ID, provider_get_task_author_list, 星图达人名单.

ClawHub Agent Skills author: juanjuan2538 v1.0.1 MIT-0 3 files body ≈ 1 393 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions

IntegrationExcelPeople and hiringInfrastructureData and analyticstype 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
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Tools and files w 18
60
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 · 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 frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: This skill should be used when the user needs to query the registe… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 40 steps
    • 100Failures and branches. 7 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1393 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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 456: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 40 items
    • +4Has examples (3 code blocks)
    • +3All 1 scripts are documented

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

    External checks

    ClawHub: suspicious
    The skill appears to perform the promised XingTu export, but it asks users to paste a live browser cookie into chat and stores it in plaintext for reuse.
    LLM: suspicious (high) · 28 May 2026