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Get angle pre-flight

get_angle_preflight
Read-only

BEFORE spending: what can this account's budget actually resolve? Simulates the real stopping rule on the account's own observed spend, CPC and CVR and returns a P20-P80 weeks-to-verdict RANGE for the candidate angle count — never a single week. An unresolvable plan comes back as advice (fewer angles, the clicks-basis alternative with its caveat, or conversion tracking as the real fix), not refusal. Scoped to the active Space — see set_active_space to switch, or pass space_id to override for this one call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesCandidate angle count.
space_idNoOverride the active Space for this one call. Defaults to the active Space set via set_active_space (or GROWOMAT_SPACE_ID on the server). Pass to read/write a different Space without changing the session binding.

TDQS

A4.5/5.0
Behavior5/5

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

Even with readOnlyHint present, the description adds substantial non-obvious behavior: it always returns a probabilistic range rather than a single value, and unresolvable plans come back as advice, not refusal or an error. This is the kind of nuance an agent cannot safely infer from the schema or annotation alone.

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?

The description is compact and front-loads the most important usage signal: 'BEFORE spending.' Each sentence carries distinct information: the purpose, the return shape, the failure-mode behavior, and the scoping mechanism. There is no redundant or filler content.

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?

Even without an output schema, the description covers the return type, its variability, the failure/advice behavior, and how to control scope — which is all an agent needs to invoke and interpret the result correctly. The tool's complexity is low, and this description fully compensates for the absence of structured output definitions.

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?

The input schema already documents both parameters completely, including the meaning of count and the scoping behavior of space_id. The description reinforces this with 'candidate angle count' and 'override for this one call,' but adds little semantic value beyond what the schema already states.

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 states a concrete purpose: it simulates the budget-based stopping rule on the account's observed spend, CPC, and CVR, and returns a P20-P80 weeks-to-verdict range for a candidate angle count. The 'BEFORE spending' framing and 'never a single week' caveat make its function distinct from simple read tools like get_angle or get_angle_readout.

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?

The opening 'BEFORE spending' is a clear usage trigger, and the description gives concrete scoping guidance: use the active Space or pass space_id to override. It does not explicitly name alternatives like get_angle_readout or state when NOT to use the tool, so some inference is still required.

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

A3.6/5.0
Disambiguation4/5

Most tools follow a clear resource+action pattern (get_ad, update_ad, delete_ad), so entity-level tools are easy to distinguish. The main ambiguity is among reporting/status tools like get_conversion_status, get_conversion_health, get_conversion_report, and account_summary vs. get_performance_stats, which could tempt misselection without reading descriptions.

Naming Consistency5/5

Naming is highly consistent: nearly every resource has create_/get_/update_/delete_/list_ variants, with predictable special verbs like set_, trigger_, preview_, and upload_. Minor exceptions like account_summary or get_angle_readout still follow the same readable verb-driven style.

Tool Count1/5

83 tools is an extreme surface for an MCP server, even one covering ad management. Most entities have full CRUD plus many custom readouts and report variants, which creates context bloat and makes tool selection unnecessarily expensive for the agent.

Completeness4/5

The platform covers the full campaign lifecycle: campaigns, ad groups, ads, keywords, assets, business/creative planes, conversion actions, sync, budget, and targeting are all represented. Minor gaps exist—conversion sources have create/list but no get/update/delete, and there is no explicit way to update or remove a conversion source—but these can be worked around.

Resources