SKILLEMALL.ai

AC yoooclaw-work-report-en

Automatically extract the work progress, communication points and to-dos of the day or week from work-related message notifications, and generate a daily or weekly work report. Trigger: daily report/weekly report/work report/what you did today/what you did this week/help me write my daily report/help me organize my weekly report/work briefing/work summary.

ClawHub Agent Skills author: vivalavida-say-hi v1.0.0 MIT-0 4 files body ≈ 1 947 tokens Open the sourceclawhub.ai analyzed 2 d ago

Automatically extract the work progress, communication points and to-dos of the day or week from work-related message notifications, and generate a daily or…

As a process C 63/100 · Has gaps — weak spots: when it triggers, running it twice, progress reporting

GeneratorNotionGitHubData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
63/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

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

    • 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: Automatically extract the work progress, communication points and … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 63/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 37 steps, 2 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1947 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 358: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 37 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

    External checks

    ClawHub: suspicious
    The skill’s work-report purpose is clear, but it reads broad notification archives and can surface identifiable workplace information without enough source scoping or review safeguards.
    LLM: suspicious (high) · 17 Jul 2026