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Add sourced candidates to screening

add_sourced_candidates_to_screening

Add people from a source_candidates result to a role's screening and run them through the CV pipeline. This consumes the user's daily processing limit; people already in the screening are skipped. Pass either the role id or the screening id, not both. The screening must be active. Requires OAuth and a workspace role that can edit.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspaceId": "<workspaceId>",
      "sourcedCandidateIds": "<sourcedCandidateIds>"
    },
    "name": "add_sourced_candidates_to_screening"
  }
}

Input Schema

NameRequiredDescriptionDefault
roleIdNoAdd to this role's screening, from list_roles.
batchIdNoAdd to this screening, from list_batches.
workspaceIdYesThe workspace id returned by list_workspaces. Use 'personal' for the personal workspace.
sourcedCandidateIdsYesSourced candidate ids from a source_candidates result.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations (readOnly=false, destructive=false, openWorld=false) by disclosing the costly side effect (consumes the user's daily processing limit), idempotency behavior (people already in the screening are skipped), and the auth requirement (OAuth plus an edit-capable workspace role).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four short sentences, front-loaded with the action and its consequence, followed by the parameter rule and the prerequisite. No filler sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutating bulk-add tool with a fully described schema and no output schema, the description covers side effects, skipping behavior, parameter exclusivity, and authorization. Nothing an agent needs before calling is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already documented; the description adds the mutual-exclusivity rule between roleId and batchId that the schema does not express, which is genuinely useful selection guidance. It adds nothing further about sourcedCandidateIds limits or the 'personal' workspace value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Add people from a source_candidates result to a role's screening') plus the downstream effect ('run them through the CV pipeline'). The mention of source_candidates clearly distinguishes it from siblings like import_ats_candidates or source_candidates itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete preconditions: pass either roleId or batchId but not both, and the screening must be active. It does not name a sibling alternative for the cases where this tool does not apply, but the usage context is otherwise unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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