SKILLEMALL.ai

AC odl-pdf

Procedure for extracting structured data from PDFs with opendataloader-pdf (ODL) correctly: read the installed tool's own help to discover its current options, build the minimal command for the user's goal, verify the extraction actually succeeded, and diagnose silent failures the tool does not report. Use when the user is using, evaluating, or considering opendataloader-pdf/ODL to extract, parse, or convert PDF content to text, markdown, JSON, or HTML — including scanned-PDF OCR, tables, bounding boxes, or a RAG pipeline over PDFs. Do NOT use for PDF merge/split/rotate, Office-format conversion, form filling, or PDF/UA accessibility-compliance tagging.

opendataloader-project/opendataloader-pdf Agent Skills author: opendataloader-project Apache-2.0 12 files · 4 scripts body ≈ 4 045 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Procedure for extracting structured data from PDFs with opendataloader-pdf (ODL) correctly: read the installed tool's own help to discover its current…

As a process C 61/100 · Has gaps — References files that are not bundled: references/…, scripts/…

ProcedureData and analyticsAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
61/100
Has gaps
References files that are not bundled: references/…, scripts/…
Tools and files w 18
0
Running it twice w 4
30
Failures and branches w 10
50
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: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/…
  • warning missing-ref reference to a missing file: scripts/…

Process rating: all ten parameters 61/100

Will not run. References files that are not bundled: references/…, scripts/…
  • 0Tools and files. 2 referenced file(s) missing: references/…, scripts/…
  • 30Running it twice. 9 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4045 tokens
  • 85Steps. 37 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 661: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 37 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)
  • +3All 4 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.