Get one Replay Vision scanner by id, including its prompt/config and credit usage this month, for the operator or analytics agent. Use when inspecting a scanner before editing or enabling it. Only works if PostHog is connected.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Scanner UUID | |
| companyId | Yes | FreedomOS company id to act within (you must be a member). Required for company-scoped tools. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits on its own. It mentions that it returns 'prompt/config and credit usage this month' and includes the PostHog prerequisite, which is useful. However, it does not explicitly state that the operation is read-only (no side effects) or describe error behavior (e.g., if the ID is invalid). The name 'get' implies read-only, but for a tool without annotation support, this is a moderate gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action and what is returned, followed by a usage scenario and a prerequisite. Every sentence adds value, with no redundancy or filler. It is appropriately concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema, the description compensates by specifying the key return contents ('prompt/config and credit usage this month') and the prerequisite. For a single-item retrieval tool, this is sufficient for an agent to decide when to call it. It does not cover edge cases like not-found errors, but that is typically handled by tool-level error responses rather than description detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides thorough descriptions for both parameters: 'id' as 'Scanner UUID' and 'companyId' with context about membership and scope. The schema coverage is 100%, so the baseline is 3. The description adds no additional parameter-specific detail beyond what the schema already conveys, so it stays at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get one Replay Vision scanner by id'), the specific resource, and what is included ('prompt/config and credit usage this month'). It distinguishes this from listing all scanners by emphasizing retrieval by ID, and the mention of 'inspecting a scanner before editing or enabling it' provides context that separates it from create/update/delete siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when inspecting a scanner before editing or enabling it', which is a clear use case. It also gives a prerequisite ('Only works if PostHog is connected'). It does not explicitly mention alternatives or when not to use it, but the 'by id' framing implies that list_vision_scanners is for multiple. Overall, clear guidance without exclusions, hence a 4.
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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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 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.
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.
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.