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Fleet — Recent Signups

fleet_product_signups_recent
Read-onlyIdempotent

List recent signups (last N days, hard cap 50 rows) with the same product-backend shape as fleet_product_user_summary — trial/credits/plan/onboarding/Heists per user. Use to see the newest cohort at a glance before drilling into individuals. Requires mcp:fleet:customer_pii. Every call is audit-logged. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoSignup window in days (max 90). Default 7.
limitNoMax rows (default 20, hard cap 50).

TDQS

A4.5/5.0
Behavior5/5

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

Beyond annotations, description adds auth requirement (mcp:fleet:customer_pii), audit-logging, read-only nature, and hard cap of 50 rows. All disclosures are consistent with annotations.

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

Conciseness5/5

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

Three sentences: first states action and constraints, second gives use case, third notes permissions and logging. Every sentence adds value, no redundancy.

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

Completeness5/5

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

For a read-only list tool with full schema and annotations, description covers usage, permissions, shape reference (to fleet_product_user_summary), and logging. No gaps for typical agent use.

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?

Schema covers 100% of parameters with clear descriptions (days, limit). Description reiterates constraints (last N days, hard cap 50) but adds no significant new meaning beyond schema.

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

Purpose5/5

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

Description clearly states 'List recent signups' with specific constraints (last N days, hard cap 50 rows) and shapes (same as fleet_product_user_summary). Distinctive from siblings by focusing on newest cohort.

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

Usage Guidelines4/5

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

Explicitly says 'Use to see the newest cohort at a glance before drilling into individuals' and lists required permission and audit logging. Lacks explicit exclusions or alternatives to other fleet tools.

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

A3.7/5.0
Disambiguation4/5

Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.

Naming Consistency3/5

Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.

Tool Count2/5

112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.

Completeness4/5

The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.