# Search Filters & Criteria

Source: https://docs.mira.day/en/docs/agent-sourcing/search-filters-and-criteria

> Understand the difference between hard filters and AI-powered criteria in Mira.



When you describe a role to Mira, your requirements are processed in two ways: as **hard filters** and as **AI criteria**. Understanding the difference helps you write better descriptions and get more accurate Shortlists.

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Hard filters vs. AI criteria [#hard-filters-vs-ai-criteria]

|                   | Hard filters                                    | AI criteria                                                     |
| ----------------- | ----------------------------------------------- | --------------------------------------------------------------- |
| **What they do**  | Strictly include or exclude candidates          | Influence ranking and matching analysis                         |
| **Examples**      | Location, language, minimum years of experience | "Startup DNA", "has built from 0 to 1", company type preference |
| **How they work** | Binary, candidate either passes or doesn't      | Gradient, candidates are ranked by degree of match              |
| **When to use**   | Non-negotiable requirements                     | Strong preferences that allow flexibility                       |

Hard filters [#hard-filters]

These are requirements that candidates must meet. If a candidate doesn't match a hard filter, they won't appear in your Shortlist:

* **Location**: "Must be in Berlin", only Berlin-based candidates.
* **Language**: "Must speak German", only German-speaking candidates.
* **Minimum experience**: "At least 5 years", excludes anyone with less.

AI criteria [#ai-criteria]

These are preferences that Mira Reasoning Embedding evaluates through reasoning. Candidates who match these criteria rank higher, but candidates who partially match may still appear:

* **Company type**: "Preferably from a high-growth startup", startup backgrounds rank higher, but strong candidates from other environments still surface.
* **Implicit qualifications**: "Has built a team from scratch", The MRE looks for leadership patterns across career history.
* **Cultural signals**: "Scrappy, hands-on", The MRE identifies candidates from environments that typically develop these qualities.

How the clarification form uses both [#how-the-clarification-form-uses-both]

When the Agent generates its clarification form after your initial input, it's essentially separating your requirements into hard filters and AI criteria:

* **Seniority level** → Sets a hard filter or strong AI criterion depending on your choice.
* **Number of candidates** → Controls search scope.
* **Company type preferences** → Sets AI criteria for ranking.

Tips [#tips]

* **Start with fewer hard filters.** You can always narrow down after seeing the first Shortlist. Over-filtering upfront may exclude strong candidates.
* **Use AI criteria for "nice-to-haves."** Instead of "must be from a startup," try "preferably from a startup", you might discover great candidates from unexpected backgrounds.
* **Refine in conversation.** After seeing results, tell the Agent: "Only show me candidates from startups" to tighten criteria, or "Broaden to include enterprise backgrounds" to relax them.