SKILLEMALL.ai

AB monday-ops

Agentic framework for operating monday.com workspaces via the Monday MCP connector. Use this skill whenever the user wants to interact with monday.com — creating boards, managing items/tasks, updating statuses, querying board data, building automations, generating sprint reports, triaging work, or performing any project management operation on monday.com. Trigger on phrases like "monday board", "create a task", "update status", "sprint summary", "move item", "board schema", "column values", "monday.com", "project board", "work tracker", "create a group", or any reference to managing work items, boards, columns, or workflows in monday.com. Also trigger when the user references a board ID, asks about task progress, or wants to automate monday.com workflows.

ClawHub Agent Skills author: Sharoon Sharif v0.1.1 MIT-0 4 files body ≈ 2 103 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 73/100 · Nearly there — weak spots: result and completion, running it twice

ProcedureOperations and projectsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
B
73/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
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: 4. 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 73/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 22 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 26 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 5 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2103 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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

    • +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
    • +5Description quotes 11 example trigger phrases
    • +3Description length 765: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: suspicious
    This skill is mostly a monday.com workspace helper, but it gives broad real-workspace mutation guidance and expands into Gmail, Google Calendar, and Fireflies without clear consent boundaries.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026