sparkroom.listRead paginated investor-room metadata in the selected Growth project.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No | ||
| project_id | Yes | ||
| include_archived | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description only needs to add behavioral context beyond those. It adds useful specifics: pagination, metadata-only content, and project scoping. Nothing in the description contradicts the annotations.
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?
A single, front-loaded sentence captures the operation type, resource, scaffold, and scope. There is no filler, and every clause adds meaning. The structure is appropriate for a simple read-only list tool.
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?
Annotations cover the safety profile, the output schema covers return values, and the description covers scope and listing behavior. The main gap is that 'Growth project' is not defined and the default exclusion of archived rooms is left implicit to the include_archived parameter, but for a straightforward paginated list this is nearly complete.
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?
Schema description coverage is 0%, so the description must compensate by explaining parameter meaning. It only loosely conveys pagination (limit/offset) and a 'selected Growth project' (project_id), but leaves include_archived unaddressed and does not clarify semantics for the bounds or defaults. This is insufficient given the complete lack of schema-level descriptions.
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 states a specific verb ('Read'), a clear resource ('investor-room metadata'), and a structural characteristic ('paginated'). It is easy to distinguish from sibling tools such as sparkroom.get (single-room retrieval) and sparkroom.list_documents (document listing), and the project scope anchors the operation.
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 implies the tool is for reading room metadata within a project, but it does not explicitly say when to prefer this tool over alternatives like sparkroom.get or sparkroom.list_documents. There are no when-not-to-use conditions or alternative routing, leaving the decision partially to inference.
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.
Domain prefixes (crm., cap_table., landing.) clearly separate broad modules, and most tools target a specific resource and action. However, within modules there are boundary overlaps—crm.add_contact_note vs crm.log_activity and cap_table.dilution_preview vs cap_table.simulate_raise—where descriptions must be read carefully to avoid a wrong pick.
The dominant pattern is module.verb_noun (e.g., crm.create_lead, cap_table.update_stakeholder), which is clear and readable. But a subset of top-level tools uses object_verb with flat underscores (e.g., shortlink_create, qr_generate, campaign_archive) and one outlier (campaign_stats) breaks the verb pattern, so conventions are mixed.
86 tools is an extreme surface for any single MCP server, well past the 50+ threshold that makes coherent selection impractical. Even though the features span several business domains, this would be far more usable split into focused servers per module.
The covered domains are broadly complete: cap table, CRM, incorporation, landing, projects, sparkroom, tasks, and validation all have read/write workflows with few dead ends. Minor gaps remain (no campaign listing/update, no branding palette delete/update, no contact deletion) but none of them blocks the main product workflows.