SKILLEMALL.ai

AC notion-coworker

An autonomous Notion coworker agent that monitors Gmail for Notion comment mentions (from notify@mail.notion.so), reads the comment to understand what's being asked, researches an answer using memory, conversation history, the Notion workspace, and optionally the web, then replies directly in the Notion discussion thread. All research gathered is documented as a subpage. Use this skill whenever the user says things like "check my Notion mentions", "handle my Notion comments", "process Notion notifications", "act as my Notion coworker", "respond to mentions", "check notify emails", or any variation of wanting an agent to autonomously read and respond to Notion comment threads. Also trigger when the user pastes a Notion page URL and asks you to "reply to the comment", "handle the discussion", or "check what they asked me". Even if the user just says "check my mentions" or "any new comments?" without saying "Notion", trigger this skill if the user has used it before.

ClawHub Agent Skills author: Lauro v1.0.0 MIT-0 2 files body ≈ 1 993 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureNotionGmailAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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: 2. 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 61/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 8 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 28 steps
    • 100Failures and branches. 8 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1993 tokens
    • 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 978: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 12 example trigger phrases
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 28 items
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This skill is not malware, but it can read Gmail and Notion context, use past chat memory, and automatically post persistent Notion replies and pages with limited confirmation controls.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026