SKILLEMALL.ai

AB xparse-parse

Parse documents into clean markdown or structured JSON via the xparse-cli. Use this skill when the user provides a PDF, image, Office file, HTML, OFD, or other supported document and wants it read, converted, summarized, or prepared for downstream agent use. Handles encrypted PDFs, page ranges, markdown/text output, and detailed structured extraction. Prefer this skill whenever the task starts from a local file or document URL and the first step is to turn it into agent-friendly content rather than manually inspect the raw file.

ClawHub Agent Skills author: JerryZhao v0.1.1 MIT-0 7 files body ≈ 1 030 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 67/100 · Nearly there — weak spots: result and completion, consistency

IntegrationAI and agentsInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Consistency w 8
40
Tools and files w 18
60
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 · 0

    ✓ No critical or high findings

    Files scanned: 7. 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 67/100

    • 0Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (xparse-parse) differs from the folder (textin-xparse-parser-safe)
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 18 steps
    • 100Failures and branches. 9 branches, has a failure section
    • 100Execution cost. Instruction body is 1030 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (10 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 534: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 18 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This is a coherent document-parsing skill, but users should understand it relies on xparse/TextIn services and may process documents outside the local machine.
    LLM: benign (high) · VirusTotal: · 29 May 2026