SKILLEMALL.ai

BD competitive-intelligence-agent

Monitors competitors across pricing, social media, online reviews, and product changes — distills everything into a concise weekly briefing.

ClawHub Agent Skills author: marcvanstad v1.0.0 MIT-0 9 files · 1 script body ≈ 2 465 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

AnalyzerInfrastructureAI and agentsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
98
Quality 40%
69
Run on models
none yet
Process rating
D
41/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration exfil-webhook-url reference/config/delivery.yaml:23
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    webhook_url: "https://hooks.slack.com/services/T00/B00/xxxxxxxx"
    placeholder
  • low Exfiltration exfil-webhook-url SKILL.md:76
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    slack_webhook: "https://hooks.slack.com/services/..."
    placeholder

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 41/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2465 tokens
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 tags): a typed call is more reliable

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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 140: enough signal without eating the budget
  • +4Structure: 22 headings
  • +4Has examples (14 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This is a disclosed competitive-monitoring skill; it uses scraping and optional report delivery as expected, but users should configure data sharing and retention carefully.
LLM: benign (high) · VirusTotal: · 28 May 2026