> For the complete documentation index, see [llms.txt](https://docs.senseloaf.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.senseloaf.ai/hiring-pipeline/screen-candidates.md). # Screen Candidates Get candidates into your pipeline and let SIA take it from there Once your workflow is active, you're ready to start bringing candidates in. From here, the platform handles the heavy lifting — automatically screening, scoring, and moving candidates through the pipeline based on the workflow you've set up. #### 1. Open your workflow Navigate to the workflow you've set up for the role. Once you open it, you'll land on the **Candidate Listing page** — this is your central view for managing all candidates for this role.

From the Candidate Listing page, you can: * View all candidates added to the workflow * See their current stage and status at a glance * Take actions on individual candidates #### 2. Add Candidates To bring candidates into the workflow, click **Screen Candidates** in the top-right corner of the Candidate Listing page.

You can add candidates in bulk (upto 50 at a time) or individually depending on your preference and how many you're working with. {% hint style="warning" %} Candidates added here will immediately enter the workflow. If Resume Matching is enabled, the system will begin evaluating them as soon as they're added. {% endhint %} #### 3. Evaluate Candidates Once candidates are in the pipeline, SIA starts the resume screening process automatically. SIA analyses each candidate's resume against your configured matching strategy - no manual scoring needed.

As each resume is processed, candidates begin appearing in the **Resume Matching** stage with key details like their recent role, total experience, and matching grade — making it easy to identify strong fits quickly. Once the screening process is complete, each candidate is automatically assigned a **grade**.

Grades are calculated based on how well the candidate matches the job requirements defined in your matching strategy. Here's what each grade means at a glance:

Grade	What it means
A	Excellent match — strong candidate to prioritise
B	Good match — worth reviewing in detail
C	Moderate match — may meet some but not all requirements
D	Weak match — significant gaps against requirements
E	Poor match — does not meet the role requirements

{% hint style="warning" %} If you have automation rules set up in your workflow, candidates will automatically move to the next stage based on their grade — no manual action required. For example, a grade A or B might automatically trigger the AI Prescreening Agent. {% endhint %} #### 5. What's next? Once candidates are graded, you can: * **Review Matching Insights** for a detailed breakdown of how each candidate was evaluated → [AI Matching Report Card](/agents-output/ai-matching-report-card.md) * **Let automation handle progression** — if [Hiring Automation](/hiring-agents/hiring-automation.md) is enabled, candidates move stages automatically based on the rules you've configured * **Manually move candidates** — you can manually progress a candidate to the next stage at any time. [Click the respective agent action ](/hiring-pipeline/trigger-agents.md)(Trigger [AI Prescreening](/hiring-agents/ai-prescreening-agent.md) or Trigger [AI Interview](/hiring-agents/ai-interview-agent.md)) directly from the Candidate Listing page. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.senseloaf.ai/hiring-pipeline/screen-candidates.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `build a script that syncs our docs to a CMS` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.