SKILLEMALL.ai

AD ontology-modeling

Use when explaining Palantir Ontology concepts, guiding users to model a Foundry Ontology from scratch, parsing Feishu or local documents to extract business entities, or designing Object Types, Link Types, Action Types, Functions, and Interfaces for a Foundry implementation. / 当用户询问本体建模概念、需要从零引导建模、解析飞书或本地文档提取业务实体、或设计 Object Type / Link Type / Action Type / Function / Interface 时使用。

ClawHub Agent Skills author: sunny v1.0.0 MIT-0 9 files body ≈ 1 057 tokens Open the sourceclawhub.ai analyzed 2 d ago

Use when explaining Palantir Ontology concepts, guiding users to model a Foundry Ontology from scratch, parsing Feishu or local documents to extract business…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
D
43/100
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 · 0

    ✓ No critical or high findings

    Files scanned: 9. 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 43/100

    • 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. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1057 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 385: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (6 of 6)

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

    External checks

    ClawHub: suspicious
    This ontology-modeling skill is mostly coherent, but it can read sensitive business documents and save full raw copies locally without a clear consent or cleanup step.
    LLM: suspicious (medium) · VirusTotal: · 28 May 2026