SKILLEMALL.ai

AC odata-service

Work with the complete standards-based OData v4.0 and v4.01 protocol: discover models and capabilities; query and track data; create, update, upsert, and delete entities; manage relationships and streams; invoke functions and actions; and use batch or asynchronous requests. Use for integrating or operating any OData v4 service beyond read-only querying. Requires explicit user authorization before state-changing requests.

ClawHub Agent Skills author: 孙灿阳 v1.0.0 MIT-0 14 files body ≈ 1 317 tokens Open the sourceclawhub.ai analyzed 2 d ago

Work with the complete standards-based OData v4.0 and v4.01 protocol: discover models and capabilities; query and track data; create, update, upsert, and…

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 12. 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 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 100Steps. 20 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1317 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
    • +4No input/output examples
    • -31 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 424: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 20 items
    • +4Reference files are cited in the instructions (6 of 6)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: suspicious
    The skill is mostly coherent for OData work, but it ships unnecessary Python bytecode that should be reviewed or removed before installation.
    LLM: suspicious (medium) · 3 Sept 2026