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freedom-mcp

by com.getfreedomos

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 — company managers (executive/gm) run this without a card. Other members ask once; a from-now-on approval makes future calls seamless. Connecting a connector still needs the OAuth/connect card (request≠grant).]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesThe specific mission this hire will achieve — be as specific as possible, include real numbers
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
obsessionNoThe ONE demand-path KPI this agent lives or dies by (leads, enrolls, revenue, cash, customers). Not "agents activated" or team-hygiene metrics. Specific with numbers when possible (e.g., "Close the $4,200/mo freedom gap").
role_nameYesA descriptive role name (e.g., "YouTube Growth Specialist", "Cash Flow Analyst", "SEO Content Writer")
agent_nameNoOPTIONAL. 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 the user named the agent; leave unset to auto-generate a fitting name. NEVER fold the requested name into role_name.
guardrailsNoWhat this agent should NEVER do (e.g., "Never recommend cutting product investment", "Never ignore cash runway below 3 months")
first_72_hoursNo3 demand-bound first actions (leads/enroll/outbound/content-to-market/cash/fulfillment). FORBIDDEN: placement audits, governance of inactive agents, fleet ownership maps, agent scoreboards. These become Day 1-3 tasks; hygiene shapes are stripped at write time.
reports_to_nameNoName 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 "founder" for direct-to-founder reporting.
success_metricsYesSpecific, measurable outcomes that define success
domain_expertiseNoRole-specific domain knowledge that makes this agent an expert (frameworks, ratios, best practices specific to this role and industry)
reporting_cadenceNoHow often to send updates: weekly, biweekly, monthly, or realtime
personality_traitsNoCommunication style preferences (e.g., "direct", "data-heavy", "encouraging", "concise", "detailed analysis")
required_resourcesNoTools, integrations, or data sources this agent needs. Default documents, briefs, and reports to the FreedomOS Knowledge Base (save_knowledge / read_knowledge — always available, visible in-app); list an EXTERNAL integration (e.g. Google Sheets) only when the role genuinely needs it. Do NOT list Google Docs/Sheets as a default — the agent can request a connector via request_connector and state the limitation until it is granted.
context_and_resourcesNoWhat the user has already tried, existing tools/data/resources available

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It discloses that this is a sensitive-tier tool that "initiates a multi-step agent process" and explains manager vs. member approval rules and connector OAuth caveats. It does not fully describe what the multi-step process returns or its side effects beyond hiring the specialist.

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

Conciseness4/5

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

The description is concise, front-loaded with purpose, and follows with usage and governance context. The bracketed sensitivity note is dense but relevant; no sentence feels wasted.

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

Completeness3/5

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

The description covers purpose, timing, and governance, but with 14 parameters and no output schema, the agent is left without information about what the hire process returns or how success/confirmation is communicated. A brief note on the expected outcome would make this more complete.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description does not add much parameter-level meaning beyond saying richer context improves the hire, but the schema already explains each individual parameter.

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

Purpose4/5

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

The description states a specific action and resource: "Hire a new specialist with full hiring context gathered from the interview." It clearly differentiates from interview_for_hire by saying "after walking through the interview phases," but it does not explicitly name sibling alternatives or contrast with update_agent/deactivate_agent.

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?

The description gives explicit when-to-use guidance: "Use AFTER walking through the interview phases." It also provides access/approval context for sensitive-tier usage, though it does not describe when to prefer alternatives like update_agent or recalibrate_agent_jd.

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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TDQS

A3.6/5.0
Disambiguation4/5

The tool set is heavily disambiguated by detailed routing descriptions, domain prefixes, and lifecycle verbs, so most tools have a clear intended purpose. However, at 297 tools there are still close pairs and overlapping decision surfaces (e.g., approval workflows, 'what should I work on' readers, multiple finance/ads readers) that require careful description reading to avoid misselection.

Naming Consistency4/5

Naming is predominantly consistent snake_case verb_noun with strong domain prefixes like shopify_, x_, posthog_, and list_/create_/update_ patterns. Minor inconsistencies exist, such as several collection-returning tools using get_ (get_team_members, get_icps, get_okrs) instead of list_, and some generate_ vs create_ vs draft_ verbs, but the pattern is still predictable overall.

Tool Count1/5

297 tools is an extreme outlier and far beyond a usable MCP tool surface. Even a large suite has no justification for this count in one server; the agent would struggle to select among hundreds of similarly descriptive tools, and the natural 3-15 tool range is exceeded by nearly 20x.

Completeness4/5

The individual domains represented — OKRs, CRM/leads, Shopify, content pipelines, ads, PostHog, team hiring, knowledge, finance, and session management — are covered remarkably well with full lifecycle patterns. Minor gaps exist, such as no full deal CRUD, no delete for several Google/Shopify artifacts, and some analytical surfaces being read-heavy, but most workflows can be completed without dead ends.

Resources