oa-compare
Skill2 starsChanged 27 days agoMITView on GitHub
Compare the online-assessment patterns of several companies from OAHelper (question count, coding vs MCQ split, difficulty, topics, recency) to decide what to study first or which OAs overlap. Use when the user says "compare X and Y OAs", "which of these companies' OAs are similar", "what topics are common across my upcoming OAs", or lists several companies they are applying to.
In this repository8 other files it gives its agents.
- interview-insightsSkill
- mcq-drillSkill
- oahelper-setupSkill
- oa-mockSkill
- oa-prepSkill
- revise-mistakesSkill
- solve-coachSkill
- study-planSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 14
If not saved, oahelper_search(company) (one request) gives set dates, counts and question types.
- Distinctive: line 18
Ask before syncing more than 4 companies in one go.
- Distinctive: line 22
Use sets from the last 12 months.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Compare OAs across companies
Part of oahelper-mcp by Sirjan Singh.
1. Gather (cheap first)
For each company:
oahelper_offline(company). Use the saved pack when it exists.- If not saved,
oahelper_search(company)(one request) gives set dates, counts and question types. That is enough for the comparison table. Only runoahelper_syncif the user wants topic-level detail, and cap it at about 20 requests per company.
Ask before syncing more than 4 companies in one go; it burns the daily cap.
2. Compare
Use sets from the last 12 months; fall back to older ones and flag it.
| Column | From |
| Sets in last 12 months | set dates |
| Questions per OA | set question counts |
| Coding / MCQ / SQL split | question types |
| Typical difficulty | difficulty scores of saved questions |
| Top topics | question titles, tags and statements |
| Latest set | newest date |
3. Output
- The table above, one row per company.
- Shared topics: topics that appear in 2 or more companies, ranked by how many. These are the highest-leverage things to study.
- Company-specific: anything only one company tests (e.g. SQL only at X).
- Study order: a short ranked list, factoring in the OA dates if the user gave them.
Say where data is thin (one set, old sets, no saved questions). Write UNKNOWN instead
of guessing a number.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

