List this company's recent original X posts from the connected account — no URL paste. Use when the operator posted on X and FO should see it. Does not post.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max posts (5–20, default 10). | |
| 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?
With no annotations, the description must self-disclose side effects. It explicitly states 'Does not post', which is a crucial safety guarantee in an action-oriented ecosystem. This goes beyond the verb 'list' to reassure the agent that no mutation occurs. It does not mention additional behaviors (e.g., token refresh, network calls), but for a simple read tool, this is sufficient.
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?
Two sentences, highly front-loaded with the core action and scope. Every clause adds value: 'List this company's recent original X posts', 'from the connected account — no URL paste', 'Use when...', 'Does not post.' No redundancy or filler.
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?
For a simple list tool with no output schema, the description adequately covers purpose, use case, and safety. It does not describe the return format or pagination, but given the tool's simplicity and the presence of explicit usage guidance, it is reasonably complete. However, it lacks any mention of ordering or time range defaults, which could be considered a minor gap.
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 full descriptions for both parameters (coverage 100%), so the description adds no new parameter-level meaning. The mention of 'recent' and 'original' is about the tool's behavior, not the parameters. Baseline 3 is appropriate because the schema covers all parameter semantics.
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 uses a specific verb 'List' with a clear resource ('recent original X posts') and scoping ('this company's... from the connected account'). It distinguishes from sibling tools like 'list_operator_cos_events' by specifying 'X posts' and 'no URL paste', which implies a different ingestion mechanism. The phrase 'recent original' adds specificity about the post type.
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?
It explicitly states when to use ('Use when the operator posted on X and FO should see it') and clarifies a limitation ('no URL paste'). It also disambiguates from potential alternatives by saying 'no URL paste', though it does not name a specific alternative tool. The context is clear enough for an agent to decide when this tool applies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.