SKILLEMALL.ai

BD simmer-briefing

Daily check-in pattern for Simmer agents. One API call returns portfolio, risk alerts, and opportunities across all venues. Use this in your heartbeat to keep your human informed.

ClawHub Agent Skills author: Simmer.Markets v0.1.4 MIT-0 3 files body ≈ 1 289 tokens Open the sourceclawhub.ai↗ analyzed 12 d ago

Daily check-in pattern for Simmer agents.

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
49/100
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 52): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 49/100

    • 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
    • 30Running it twice. 1 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. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1289 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 179: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    The skill is mostly coherent as a Simmer portfolio briefing tool, but it lets remote plain-text briefing content steer financial actions without clear user-confirmation boundaries.
    LLM: suspicious (high) · VirusTotal: · 16 Sept 2026