SKILLEMALL.ai

AF smart-price-monitor

Monitor product prices, stock levels, and market data across any website or API, with intelligent alerts and trend analysis. Use this skill whenever the user wants to track prices, monitor deals, compare prices across stores, get notified about price drops, watch for restocks, track competitor pricing, monitor exchange rates, or build any kind of real-world data monitoring pipeline. Also triggers on: "price alert", "deal tracker", "price history", "price comparison", "stock alert", "restock notification", "market watch", "price scraping", "e-commerce monitoring", "competitor pricing", "price intelligence", "deal finder", "sale alert", "lowest price", "price trend". This is the go-to skill for any real-world data extraction and monitoring task.

ClawHub Agent Skills author: Chloe Park v1.0.0 MIT-0 6 files body ≈ 2 079 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 48/100 · Will not run — References files that are not bundled: url

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
F
48/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: url

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 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. 6 mutating operations with no state check
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 70 steps, 1 vague phrases
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2079 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)
  • +3Output format is not stated: the model decides each time
  • -32 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 15 example trigger phrases
  • +3Description length 753: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 70 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: clean
This is a coherent price-monitoring skill that saves local monitoring data and can optionally support alerts, with some broad wording users should treat carefully.
LLM: benign (high) · VirusTotal: · 29 May 2026