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posthog_list_vision_observations

List Replay Vision observations (what scanners saw on recordings) for the operator or analytics agent. Filter by scanner_id and/or session_id. Observation text is untrusted model output. Use when reviewing scanner findings. Only works if PostHog is connected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows (default 20, max 50)
statusNosucceeded | failed | pending | ineligible | in_flight
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
scanner_idNoLimit to one scanner UUID
session_idNoLimit to one session recording id

TDQS

A4.2/5.0
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses that 'Observation text is untrusted model output' (a security/data-quality warning) and the PostHog dependency. It implies a read-only operation by listing, but does not explicitly state lack of side effects. Still, it covers important behavioral aspects beyond just the function name.

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?

The description is three sentences, front-loaded with the core purpose, then filters, a warning, and a dependency. Every sentence adds value without redundancy. It is efficiently structured and easy to parse.

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

Completeness4/5

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

For a list tool with 5 parameters and no output schema, the description covers the essential context: what it lists, who it's for, filter options, a data-integrity warning, and a runtime prerequisite. It does not describe return fields or pagination behavior, but the lack of output schema and the presence of a limit parameter mitigate that gap.

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% for all parameters, so the baseline is 3. The description adds no new parameter meaning beyond mentioning filter capability (scanner_id and session_id) which is already in the schema. It does not elaborate on limit, status, or companyId semantics beyond what is provided.

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 clearly states the tool lists Replay Vision observations with a specific verb ('List') and resource ('Replay Vision observations'), defines what they are ('what scanners saw on recordings'), and distinguishes itself from sibling tools like posthog_list_vision_scanners and posthog_get_vision_observation by focusing on observations rather than scanners or single items.

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?

Provides explicit usage context: 'Use when reviewing scanner findings.' Also states a critical prerequisite: 'Only works if PostHog is connected.' However, it does not explicitly mention alternatives or when not to use it, though the purpose is clear enough for an agent to infer alternatives.

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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