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Update SparkCap draft

cap_table.update
DestructiveIdempotent

Update selected planning fields after exact confirmation at the current opaque version.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
changesYes
project_idYes
cap_table_idYes
idempotency_keyYes
expected_versionYes
confirmation_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=true, so the safety profile is covered. The description adds genuinely useful behavior beyond that: updates are scoped to selected planning fields, gated by a version match (optimistic concurrency via expected_version), and require a confirmation token. No contradiction with annotations exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single 12-word sentence that front-loads the verb and resource and packs in the version and confirmation conditions without filler. It loses a point because the dense phrasing ('opaque version', 'exact confirmation') prioritizes brevity over immediate comprehensibility.

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

Completeness2/5

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

The output schema covers return values, but the description is under-specified for a tool with 5 required parameters, a confirmation flow, and version-gating. It never explains how to obtain expected_version or confirmation_token (presumably a prerequisite read or preview call), what happens on version mismatch, or whether changes are merged or replaced. An agent cannot confidently invoke this tool correctly from the description alone.

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?

With 0% schema description coverage, the description carries the burden of explaining parameters. Its prose maps well to changes ('selected planning fields'), expected_version ('current opaque version'), and confirmation_token ('exact confirmation'). However, it never explains idempotency_key's retry-safe semantics, and project_id/cap_table_id are left to inference from their names. Partial compensation for a large coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Update'), resource ('selected planning fields'), and key conditions ('after exact confirmation at the current opaque version'). The phrase 'planning fields' distinguishes it from cap_table.update_stakeholder, which targets stakeholder data, and 'selected' implies partial updates rather than full replacement. It loses a point because no sibling is named explicitly and the jargon 'opaque version' is never clarified.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a usage condition — updates should only occur after exact confirmation at a specific version — but gives no explicit when-to-use guidance, no exclusions, and no direction to alternatives such as cap_table.create for new cap tables or cap_table.update_stakeholder for stakeholder-level changes. The 0% schema coverage and 5 required parameters make this gap more costly.

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

B3.1/5.0
Disambiguation3/5

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.

Naming Consistency3/5

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.

Tool Count1/5

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.

Completeness4/5

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.

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