gtm-alpha-consultant

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely new behavior: results are downgraded to "preliminary" when optional inputs are omitted, and it discloses what the response contains (lead motion, warnings/notes, buying committee, objections). No auth or rate-limit details, but those are not required for a read-only computation.

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, front-loaded with the return contents and followed by the conditional-full-score rule. The first sentence is long and list-heavy but every clause describes a distinct part of the output, so little is wasted.

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?

With 12 parameters, 1 required, and no output schema, the description carries the burden of describing return values, which it does (scores, lead motion, warnings, notes, buying committee, objections). It is nearly complete; only the preliminary-vs-full distinction's effect on specific fields could be spelled out more.

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 100%, so the baseline is 3 and the schema already documents every parameter including enums and examples. The description adds only a collective reference to "optional inputs" and notes that naming the sector triggers buying-committee/objections output, but no per-parameter syntax or format detail beyond the schema.

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?

Names a specific verb (get) and resource (EPIC framework scores) and enumerates the four motions returned (Ecosystem/ABM, PLG, Inbound/Outbound, Community-Led, each 1-10). It is clearly distinguishable from siblings like generate_roadmap or gtm_consultation by being a scoring/audit tool, though it never names those alternatives directly.

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?

States a usage condition for the optional inputs ("Add the optional inputs for a full score; without them the result is marked preliminary"), which is helpful. However, it gives no guidance on when to prefer this over gtm_consultation or generate_roadmap, leaving tool selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare this is a read-only, closed-world, non-destructive text generator. The description adds that it 'Builds text from the inputs only', which usefully signals deterministic, no-lookup behavior, but it does not describe output shape, length, or any caveats about the plan quality.

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?

A single tight sentence plus a short behavioral sentence, front-loaded with the output type and scope. The parenthetical EPIC expansion is slightly dense but earns its place by defining the enum letters for an agent reading only the description.

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 read-only text-generation tool with 3 fully documented enum parameters and no output schema, the description covers what it returns (action plan with immediate/short/medium-term steps), the timeframe scope, and the business-model exclusion. It is nearly sufficient; only a hint on output structure/length is missing.

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 coverage is 100% and every parameter already has enum values and descriptions, so the schema carries the parameter semantics. The description restates the EPIC letters and the self-serve exclusion rule, adding marginal value beyond the schema baseline.

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 states a specific verb ('Return a GTM action plan') and resource ('EPIC motion… over 30, 60 or 90 days'), and it names the EPIC categories explicitly. It is distinguishable from the siblings (audit vs consultation vs roadmap) without opening the schema.

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 makes clear this produces a plan for one motion and one timeframe, and notes the self-serve exclusion for non-subscription models, which guides when to pick certain inputs. It does not explicitly compare itself to epic_audit or gtm_consultation, so the alternative-selection guidance is only implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is already covered. The description adds genuinely new behavior: it enumerated the exact output contents (1-10 scores, primary/secondary motion, 30-day plan, sector notes) and disclosed the preliminary-vs-full result condition. It says nothing about latency or repeat-run caching.

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, front-loaded with the output contract before the input advice. The parenthetical list of optional inputs is a mild restatement of the schema, but it is compact and it earns its place by tying those inputs to the preliminary/full distinction.

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?

With no output schema, the description carries the burden of explaining returns, and it does so concretely. For a 13-parameter tool with only one required input, the description plus 100% schema coverage is nearly sufficient; the only real gap is the lack of routing guidance relative to the two sibling tools.

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 100%, so the baseline is 3 and the schema already documents all 13 parameters, including optional markers and enum values. The description goes beyond that by grouping the optional inputs (ACV, deal cycle, NRR, TAM, self-serve, deal source, geography) and explaining their effect on output quality, which the per-parameter schema text does not convey.

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 states a specific verb set and resource: it scores the four GTM motions, names primary/secondary motion, and lists 30-day steps. An agent knows exactly what it gets back. It does not, however, differentiate this tool from the siblings epic_audit or generate_roadmap, which appear closely related.

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?

It gives input-level guidance ('add the optional inputs for a full score; without them the result is marked preliminary'), which tells the agent how to get the best result. It offers no guidance on when to choose this tool over epic_audit or generate_roadmap, so tool-selection context is implied rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.