> ## Documentation Index
> Fetch the complete documentation index at: https://docs.spott.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Understanding Spott's Matching Tool
> The Matching tab runs an AI search across your candidate database to surface the best new candidates for a role.
**Matching** in Spott uses AI to compare the job's requirements against your candidate
database, surfacing the most relevant matches in seconds. It runs on the same engine as
[candidate search](/docs/candidates/search-candidates), using the job's description,
notes, and sourcing criteria as input.
Matching is built to surface **new** candidates, so it leaves out anyone already in
this job's pipeline. To review the people already on the job, use its
[pipeline](/docs/jobs/job-pipeline) instead.
## Access a job's Matching tab
In Spott, go to **Jobs**, open the job, and click the **Matching** tab.
## Run a search for the job
The first time, click **Start new job search**. Spott converts the job's context
from the Overview tab into filters and criteria, which you can review and adjust
with **Edit criteria** before clicking **Run search**.
The better the sourcing criteria on the job's Overview tab, the better the
matches. Upload intake call notes or a detailed job description first.
## Filters vs criteria
When Spott builds the search from the job, it splits your requirements into two parts,
shown separately when you use **Edit criteria**:
**Pre-filters** narrow the candidate pool *before* ranking. They are structured
conditions such as **Job Title**, **Field of Study**, **Keywords**, and **Years of
Experience**. Use the **Match all filters** toggle to require every filter (AND) or any
of them (OR). Spott shows how many candidates currently match, so you can widen the
filters when too few come through.
**Criteria** rank the candidates that pass the pre-filters. They are plain
natural-language statements (for example, "Business-level fluency in French") and are
**numbered in priority order** — criteria higher in the list weigh more heavily in the
match score. Drag a criterion by its handle to change that order, click the **×** on a
row to drop it, or use **Add criteria** to add your own.
A good rule of thumb: use **pre-filters** for the hard requirements that must be true,
and **criteria** for the softer qualities you want to rank on.
Both editors open from the **pre-filters** and **criteria** chips above the results,
so you can adjust a search and re-run it without starting over.
## Read the results
Candidates are ranked by a **match score from 0 to 100**, from Very Weak to Very
Strong Match.
Every **criterion** you set also becomes its own column: each candidate gets a thumbs
rating for it, from one to three thumbs-up for a match down to a thumbs-down where they
fall short. This lets you see at a glance *which* requirements a candidate meets, not
just their overall score.
Click a candidate's score to open the full **reasoning** — the assessment behind each
per-criterion rating — where you can **Accept** the candidate or **mark them reviewed**.
Each row also shows the candidate's active jobs and last interaction, so you can spot
who is already in a process elsewhere.
## Review workflow
Use the **All**, **To Review**, and **Reviewed** tabs to work through the results:
* Review the candidates with the highest match scores.
* Add strong fits directly to the job's pipeline.
* You can re-run or refine the search at any time by editing the criteria.
**Accept**, **Reject**, and **Reviewed** only track your progress through the list.
They do not train or personalize the matching model, so marking candidates does not
change future results.
## Next steps
Send your best matches to the client.
Track applicants through the job's stages.