The two-column output was only moderately usable: core contact and work-history fields were present, but sidebar skills/certifications/languages, projects, and GPA were missing or poorly handled.
What was measured
Output quality
Is the parsed result clean, complete, and usable overall?
decisive for this rankingtransformation
The whole point is usable structured extraction; clean, complete, usable output is the core measure of success. (3 of 3 judges)
What was given, what came back
Test input: Multi-column sidebar resume — Priya Sharma · pdf · group: resume-parsing
Input — what we sent
Multi-column sidebar resume — Priya Sharma
A two-column sidebar resume for Priya Sharma, used to test whether parsers can preserve reading order and correctly extract content split across columns.
Why this input is hard
- · multi-column layout handling
- · sidebar content extraction
- · reading-order robustness
- · projects extraction
- · languages and certifications extraction
Output — unretouched
Also checked on this input — same tool, 3 other criteria
Accuracy✗ FailedThe parser truncated responsibility text mid-sentence on the multi-column resume, cutting off the quantified detail after 'cutting costs by.'Field coverage◐ MixedThe parser extracted the basic identity and work-history fields, but it did not fully return the core six-field resume set because skills from the sidebar were missing.Multi-column handling✗ FailedOn the two-column sidebar layout, the parser lost the entire right-side sidebar block, so skills, certifications, and languages were not preserved in reading order.
Provenance
- Observation
- 161e513d-c61e-466c-a3e5-47779ac96b21
- Evidence run
- cbbef4db-964c-49fa-a57f-a2977822bdfc
- Study
- Parse resumes into structured data using an API
- Research task
- 86b9jm30n
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "skima-ai",
scenario: "resume-parsing"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 6 other tools
measured on Output quality
Airparser◐ MixedProduces structured JSON, but the skills section loses its original category grouping and comes back as a flat list.Extracta.ai✓ WorkedReturns an excellent, clean JSON result that captures both columns completely and avoids irrelevant metadata.Hireability✗ FailedOutput quality collapsed on the two-column resume because the parser produced a job-order-style structure instead of a candidate resume structure.HrFlow◐ MixedThe two-column output is only moderate quality: core fields are present, but title truncation, noisy skills, and incomplete task extraction reduce usability.LlamaParse✓ WorkedThe multi-column output was clean and complete overall, with fully extracted work histories, projects, certifications, and languages.OpenResume◐ MixedText extraction is largely correct, but the overall result is only moderate because the two-column layout produces significant work-experience mapping errors.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com