SKILLEMALL.ai

AD puget-sound-salmon-report

Scrape WDFW Puget Sound creel data into salmon CPUE reports: daily digest, weekly top-launch email with chart, and proactive hot-bite alerts.

ClawHub Agent Skills author: Calvin Tsai v1.0.1 MIT-0 4 files body ≈ 1 187 tokens Open the sourceclawhub.ai analyzed 3 d ago

Scrape WDFW Puget Sound creel data into salmon CPUE reports: daily digest, weekly top-launch email with chart, and proactive hot-bite alerts.

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
99
Quality 40%
87
Run on models
none yet
Process rating
D
43/100
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Concealment en-hide-from-user scripts/creel_report.py:710
      Instruction to hide actions from the user (negated — the text forbids it)
      # hard failure: don't silently send to an empty list — signal the caller to abort
      negated

    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 43/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1187 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 141: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (5 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill appears to do what it claims: scrape public fishing data, generate reports, and optionally email user-configured recipients.
    LLM: benign (high) · VirusTotal: · 8 Sept 2026