SKILLEMALL.ai

BC docparse

Trigger when user mentions OCR/文档解析/阅读/识别/读取 or asks to extract text from documents. Parses PDF/images via remote document parsing service. NOT for audio/video/photos/source code.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Va-AIS v1.0.1 MIT-0 9 files body ≈ 1 255 tokens Open the sourceclawhub.ai analyzed 2 d ago

Trigger when user mentions OCR/文档解析/阅读/识别/读取 or asks to extract text from documents.

As a process C 51/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
82
Quality 40%
89
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Secrets in code
If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 1

  • high Secrets in code meta-credential-files .env
    Credential / dotenv files bundled with the skill (1)
    .env

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 51/100

  • 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
  • 40Consistency. Frontmatter name (docparse) differs from the folder (va-docparse)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 28 steps
  • 100When it triggers. States when to use and when not to
  • 100Execution cost. Instruction body is 1255 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
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 179: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (9 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

External checks

ClawHub: suspicious
This document parser appears purpose-built, but it can upload full local documents to a configured remote service and stores service credentials in plaintext without a strong consent or privacy boundary.
LLM: suspicious (medium) · VirusTotal: · 8 Jun 2026