List THIS operator's CoS lessons (open + settled_keep by default) for self-improve memory. Use when reviewing what CoS has learned for this user only before a long call or hygiene pass. Not cross-user.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max rows (1–40, default 20). | |
| companyId | No | FreedomOS company id to act within (you must be a member). Required for company-scoped tools. | |
| include_dropped | No | If true, include settled_drop rows. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosure. It reveals the scope (operator-specific, not cross-user) and default state filters (open + settled_keep, with optional settled_drop via include_dropped). Although it doesn't explicitly state it is read-only, the verb 'List' implies a non-mutating operation, and the described behaviors add useful context.
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?
Three sentences, front-loaded with the core action, and every sentence adds value: what it lists, default filters, intended use case, and a scoping exclusion. No fluff or repetition.
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?
The description covers the what, when, scope, and defaults, which is sufficient for a simple list tool. There is no output schema, and the description doesn't describe return fields or pagination, but that is not required for this simplicity. It is slightly less complete than the benchmark 'get_calls' because it lacks explicit read-only assurance, but overall it is well-rounded.
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 has 100% coverage with descriptions for all three parameters, so the baseline is 3. The description adds default behavior context (open + settled_keep) that helps interpret include_dropped, but it doesn't clarify the role of companyId in the context of 'THIS operator's lessons' beyond the schema's generic note.
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 tool lists 'THIS operator's CoS lessons,' specifying the resource and scope. It also distinguishes from sibling tools like append_cos_lesson (which writes) and list_knowledge, and the default filter adds precision.
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?
Explicitly explains when to use: 'when reviewing what CoS has learned for this user only before a long call or hygiene pass.' It also indicates a limitation with 'Not cross-user,' which helps the agent choose this over cross-user list tools.
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.