hire_agent_with_context
Hire a new specialist with full hiring context gathered from the interview. Use AFTER walking through the interview phases. The richer the context, the better the agent. [sensitive-tier, initiates a multi-step agent process — first use may require a manager's approval; a from-now-on approval make...
This record as markdown: /tools/com-getfreedomos-freedom-mcp/hire-agent-with-context.md
What hire_agent_with_context does on Freedom Mcp
AI agents invoke hire_agent_with_context to trigger actions in Freedom Mcp. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
goal | string | Yes | The specific mission this hire will achieve — be as specific as possible, include real numbers |
companyId | string | Yes | FreedomOS company id to act within (you must be a member). Required for company-scoped tools. |
obsession | string | — | The ONE demand-path KPI this agent lives or dies by (leads, enrolls, revenue, cash, customers). Not "agents activated" or team-hygiene metrics. Specific with nu |
role_name | string | Yes | A descriptive role name (e.g., "YouTube Growth Specialist", "Cash Flow Analyst", "SEO Content Writer") |
agent_name | string | — | OPTIONAL. The exact display name the user explicitly asked for — a single first name (e.g. "Garth" from "name it Garth" / "call it Garth"). Set this ONLY when t |
guardrails | array | — | What this agent should NEVER do (e.g., "Never recommend cutting product investment", "Never ignore cash runway below 3 months") |
first_72_hours | array | — | 3 demand-bound first actions (leads/enroll/outbound/content-to-market/cash/fulfillment). FORBIDDEN: placement audits, governance of inactive agents, fleet owner |
reports_to_name | string | — | Name or role of the team member this agent should report to. Use an existing team member name if one is a natural manager. Say "Linnet" for Chief of Staff, or " |
success_metrics | array | Yes | Specific, measurable outcomes that define success |
domain_expertise | string | — | Role-specific domain knowledge that makes this agent an expert (frameworks, ratios, best practices specific to this role and industry) |
reporting_cadence | string | — | How often to send updates: weekly, biweekly, monthly, or realtime |
personality_traits | array | — | Communication style preferences (e.g., "direct", "data-heavy", "encouraging", "concise", "detailed analysis") |
Parameters from the server's own tool schema.
Why hire_agent_with_context is rated High
Triggers a multi-step agent hiring process with external operational effects.
From the tool's definition Hire a new specialist, initiates a multi-step agent process
Risk signalsHigh parameter count (14 properties)
Attacks that exploit this kind of access
The rule that runs hire_agent_with_context safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Freedom Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For hire_agent_with_context, this is the rule to start with:
hire_agent_with_context stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Freedom Mcp, apply this rule, and every hire_agent_with_context call is checked against it from then on.
Questions about hire_agent_with_context
Hire a new specialist with full hiring context gathered from the interview. Use AFTER walking through the interview phases. The richer the context, the better the agent. [sensitive-tier, initiates a multi-step agent process — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]. It is categorised as a Execute tool in the Freedom Mcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
hire_agent_with_context accepts 12 parameters: goal, companyId, obsession, role_name, agent_name, guardrails, first_72_hours, reports_to_name, success_metrics, domain_expertise, reporting_cadence, personality_traits. Required: goal, companyId, role_name, success_metrics. The full parameter table on this page comes from the server's own tool schema.
Register the Freedom MCP server in PolicyLayer and add a rule for hire_agent_with_context: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Freedom Mcp. Nothing to install.
hire_agent_with_context is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the hire_agent_with_context rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for hire_agent_with_context. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
hire_agent_with_context is provided by the Freedom MCP server (https://twuluxmoognlwtmaoqgo.supabase.co/functions/v1/freedom-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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