SKILLEMALL.ai

AC html-markdown-hybrid

Combine high-quality Markdown to HTML rendering with robust HTML to Markdown extraction in one skill. Use when converting Markdown into nicer-looking standalone HTML pages, or when converting HTML files, raw HTML, URLs, and directories into clean Markdown with article/docs/forum cleanup profiles. Prefer the Python renderer for best-looking Markdown to HTML output, and use the Node pipeline for HTML to Markdown, batch mode, metadata, reports, and advanced profile-based cleanup.

ClawHub Agent Skills author: Xiao Mu v1.1.1 MIT-0 8 files body ≈ 889 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructureSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
95
Quality 40%
91
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token package-lock.json:37
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…CNV+7cXy…ufL+9esx72/eLhsRdGZwaldu/h+E4t4BA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:193
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…Jpc+4xGg…NTg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:206
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…GLw+xYSd…cqA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:223
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…hCu+wO3O…kUg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:281
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…Lsu+QC+s3BV…TgQ==",
      detector

    Files scanned: 8. 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 56/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
    • 100Steps. 35 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 889 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 481: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    This is a straightforward HTML and Markdown converter; it can fetch webpages and read/write chosen files, but I found no hidden or unrelated behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026