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Heista

by co.heista

Fleet — Customer Product Summary

fleet_product_user_summary
Read-onlyIdempotent

Look up ONE customer's product-backend state by email: trial status, credit balance, workspace plan, installed Heists, onboarding completion, plus PostHog attribution/engagement signals (source, 30d activity, page journey). This is the data PostHog structurally cannot see — whether they actually have active credits, are on a paid plan, or installed anything. Requires mcp:fleet:customer_pii (a separate, PII-adjacent scope — see Docs/systems/fleet-access.md). Every call is audit-logged. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe user email to look up.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly and idempotent hints. Description adds 'Every call is audit-logged' and explicitly states 'Read-only', reinforcing and extending behavioral context. No contradiction 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.

Conciseness4/5

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

Two sentences with dense, useful information. Could be slightly more structured (e.g., bullet points), but it's concise and front-loaded with purpose. No wasted words.

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?

No output schema but description lists returned data points comprehensively. Covers input, prerequisites, and behavior. Given the single parameter and rich output, this is complete.

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 has 100% coverage with email description. The description does not add parameter-specific details beyond what the schema provides, so baseline of 3 is appropriate.

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?

The description starts with a specific verb+resource ('Look up ONE customer's product-backend state') and lists concrete fields (trial status, credit balance, etc.), distinguishing it from sibling tools like fleet_product_funnel_summary. Clearly states what it does.

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 states required scope ('mcp:fleet:customer_pii') and references documentation. Implicitly tells when to use: when needing customer product state. No explicit alternative exclusion, but specificity makes it clear.

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.

Resources