SKILLEMALL.ai

BF xurl

A Twitter research and content intelligence skill focused on attracting WordPress and Shopify clients. Use to analyze Twitter profiles, threads, and conversations for: (1) Identifying what small agency founders and eCommerce brands are discussing; (2) Understanding pain points around WordPress performance, Shopify CRO, and development bottlenecks; (3) Extracting high-performing content angles; (4) Turning insights into authority-building posts; (5) Converting Twitter intelligence into business leverage for clear content angles, strong positioning, and qualified inbound leads.

ClawHub Agent Skills author: Gaurang Zalariya v1.0.0 2 files body ≈ 612 tokens Open the sourceclawhub.ai analyzed 3 d ago

A Twitter research and content intelligence skill focused on attracting WordPress and Shopify clients.

As a process F 20/100 · Will not run — References files that are not bundled: references/twitter-profile-analysis.md, references/twitter-thread-breakdown.md, references/pain-point-mining.md

AnalyzerShopifyWordPressMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
55
Run on models
none yet
Process rating
F
20/100
Will not run
References files that are not bundled: references/twitter-profile-analysis.md, references/twitter-thread-breakdown.md, references/pain-point-mining.md
Tools and files w 18
0
Steps w 15
0
Result and completion w 14
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: 2. 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: A Twitter research and content intelligence skill focused on attra… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning missing-ref reference to a missing file: references/twitter-profile-analysis.md
  • warning missing-ref reference to a missing file: references/twitter-thread-breakdown.md
  • warning missing-ref reference to a missing file: references/pain-point-mining.md
  • warning missing-ref reference to a missing file: references/content-opportunity-mapping.md
  • warning missing-ref reference to a missing file: references/lead-intelligence-signals.md

Process rating: all ten parameters 20/100

Will not run. References files that are not bundled: references/twitter-profile-analysis.md, references/twitter-thread-breakdown.md, references/pain-point-mining.md
  • 0Tools and files. 5 referenced file(s) missing: references/twitter-profile-analysis.md, references/twitter-thread-breakdown.md, references/pain-point-mining.md
  • 0Steps. Prose only: no discrete steps
  • 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
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 612 tokens
  • 100Running it twice. No mutating operations

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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 582: enough signal without eating the budget
  • +4Structure: 7 headings

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: clean
This skill is a disclosed Twitter research aid that analyzes user-provided content for marketing and lead-generation ideas, with no executable code or hidden access requests.
LLM: benign (high) · VirusTotal: · 11 Sept 2026