sparkroom.update_itemChange a room item title, section or order after current-state confirmation. Revision and live-source modes remain unchanged.
| Name | Required | Description | Default |
|---|---|---|---|
| changes | Yes | ||
| item_id | Yes | ||
| room_id | Yes | ||
| project_id | Yes | ||
| idempotency_key | Yes | ||
| expected_version | Yes | ||
| confirmation_token | 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 signal that this is a non-read-only, idempotent, destructive operation. The description adds useful behavior beyond that: updates require current-state confirmation and the operation deliberately leaves revision and live-source modes untouched. This helps the agent understand expected_version/confirmation_token semantics without contradicting 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?
Two sentences communicate the core action, the affected fields, a safety precondition, and a non-impacted area. There is no filler or repetition of schema details.
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 7-parameter destructive update, the description is a bit thin on operational details: it does not explain what 'current-state confirmation' concretely requires or how expected_version and confirmation_token should be supplied. The output schema and annotations fill some gaps, but the description alone leaves important invocation semantics somewhat ambiguous.
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 carries much of the semantic burden. It maps 'title, section, or order' to the three fields inside the changes object and hints at current-state confirmation for expected_version/confirmation_token. However, it does not explain idempotency_key usage, how to obtain or satisfy the confirmation flow, or the roles of the identifier parameters beyond their names.
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 gives a specific verb ('Change') and a precise resource ('a room item') plus the exact mutable presentation aspects: title, section, and order. This clearly distinguishes it from room-level operations like sparkroom.update and from destructive counterparts like sparkroom.remove_item.
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 provides clear context for when to use it: any time a room item's presentation fields need to change. It also adds a precondition ('after current-state confirmation') and a constraint ('Revision and live-source modes remain unchanged'), but it does not explicitly name alternatives or state when not to use this tool.
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.