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get_github_app_status

See whether GetFreedomOS (the FreedomOS GitHub App) is connected for this company. Returns claimed org/user accounts. This is the App that lets FreedomOS read and open PRs on the company's repos — not GitHub Copilot MCP. If not connected, call start_github_app_claim. Use before starting a new connect flow.

Routing: GetFreedomOS / Pulse GitHub App connected? → this tool. Not connected? Call start_github_app_claim. GitHub Copilot MCP is list_integrations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations supplied, the description carries the behavioral burden. It clearly indicates a read-oriented status check using 'See whether' and 'Returns', and adds helpful behavioral context about what the app does (read/open PRs) and what the tool returns (claimed org/user accounts). It doesn't explicitly state that the call has no side effects or describe error conditions, but the read-only intent is strongly conveyed.

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 front-loads the core purpose and return value, then gives a routing paragraph. It is clear and focused, though there is some duplication: 'If not connected, call start_github_app_claim' appears twice. Still, the prose is dense enough to earn its place by disambiguating similar tools.

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 single-parameter status tool with no output schema, the description gives the essential complete picture: what the tool checks, what it returns, which app it refers to, when to use it, and which sibling to fall back to. The context needed to invoke it correctly is largely present.

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?

The input schema already fully documents companyId with 'FreedomOS company id, required, membership requirement, and company-scoped tools context', so schema coverage is 100%. The description only adds 'for this company', which doesn't add meaningful parameter semantics. This meets the baseline but adds no real extra value to the parameter meaning.

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?

The description names a specific action and resource: checking whether the FreedomOS GitHub App is connected for a company, and states it returns claimed org/user accounts. It clearly distinguishes itself from GitHub Copilot MCP and from start_github_app_claim, so an agent can select it without opening the schema.

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

Usage Guidelines5/5

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

The description explicitly says when to use this tool: before starting a new connect flow, and as the routing decision point for whether the app is connected. It also names the exact alternatives and conditions: call start_github_app_claim if not connected, and list_integrations for GitHub Copilot MCP. This leaves no ambiguity.

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.

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