Produces usable JSON from noisy text, but the skills section collapses into one long string and one education record keeps an unnormalized marks value.
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: Messy real-world resume — John Kumar · pdf · group: resume-parsing
Input — what we sent
A poorly formatted, inconsistent real-world resume for John Kumar, used to test robustness against noisy structure, inconsistent dates, and mixed-content sections.
Why this input is hard
- · messy formatting robustness
- · section detection fallback
- · inconsistent date parsing
- · soft-skills extraction
- · noise and hallucination control
Output — unretouched
Also checked on this input — same tool, 3 other criteria
Accuracy◐ MixedLeaves one education marks value as raw text ("72 percent marks") instead of normalizing it to the percentage form used by the other entries.Field coverage✓ WorkedCovers the six core fields even on messy formatting, including contact info, work experience, education, and skills.Messy resume handling◐ MixedParses a poorly formatted resume, but degrades into non-machine-readable skill output rather than a structured array.
Provenance
- Observation
- 865b57b7-f18b-4795-be43-bb0b47c559e2
- 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: "airparser",
scenario: "resume-parsing"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 5 other tools
measured on Output quality
Extracta.ai✓ WorkedProduces a usable JSON result even on the messy resume, with the important sections still readable and structured.HrFlow◐ MixedThe messy-resume output is moderate overall: contact and basic structure survive, but the result is incomplete for soft skills, certifications, and task detail.LlamaParse✓ WorkedThe messy-resume output was the richest and cleanest among the tested tools, with all 3 education entries, all 14 skills, both certifications, hobbies, and a boolean references field.Parseur⚠ StruggledSkills were returned as one unstructured, space-separated string with no array structure or delimiters, making them hard to split programmatically.Skima AI⚠ StruggledThe messy-resume output degraded sharply: responsibilities became a run-on string, skills collapsed into one concatenated line, and references/certifications/hobbies were missing.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com