SKILLEMALL.ai

BF ClawHub Skill Growth Engine

AI-powered ClawHub skill growth optimizer v2.0 — analyzes reviews, tracks 2026 trending topics (AI Agent, MCP, video SEO), rewrites titles/descriptions for maximum downloads and stars. Supports video thumbnail prompts, cross-platform social syndication, and growth metrics tracking. Triggers: clawhub optimization, skill growth, SEO, stars, downloads, review analysis, trending keywords, skill improvement, GitHub stars strategy, video SEO, social media integration, thumbnail generation.

ClawHub Agent Skills author: lingfeng-19 v2.1.1 MIT-0 5 files body ≈ 6 605 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 34/100 · Will not run — References files that are not bundled: references/video_seo_guide.md

IntegrationGitHubMedia and videoMarketingAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
78/100
safety, quality, tests
Safety 60%
100
Quality 40%
44
Run on models
none yet
Process rating
F
34/100
Will not run
References files that are not bundled: references/video_seo_guide.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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: 5. 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: AI-powered ClawHub skill growth optimizer v2.0 — analyzes reviews,… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 6605 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/video_seo_guide.md
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "capabilities"

Process rating: all ten parameters 34/100

Will not run. References files that are not bundled: references/video_seo_guide.md
  • 0Tools and files. 1 referenced file(s) missing: references/video_seo_guide.md
  • 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. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (ClawHub Skill Growth Engine) differs from the folder (clawhub-skill-optimizer)
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 6605 tokens
  • 100Steps. 8 steps

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)
  • -298 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 488: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 8 items
  • +3Output format is stated explicitly
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 44.

External checks

ClawHub: clean
This is a markdown-only ClawHub skill optimization guide with disclosed example API code, not an installed program that runs by itself.
LLM: benign (high) · VirusTotal: · 2 Jun 2026