gtm-engineer

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

With no annotations, the description carries the full burden and does supply useful traits: headless operation with no browser, required email used as license owner, and returned artifacts including a short-lived download URL. It omits mutation-relevant behavior such as idempotency (claiming twice), failure modes, and any rate or permission constraints on issuing a license.

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?

Information is front-loaded: scope and the claim path come first, then return values, then the headless note. Sentences carry weight, though the pair 'The free AI GTM Engineer itself needs no claim: the single install command installs it directly' has mild redundancy.

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 no-output-schema tool, the description explicitly covers return values (license key, install command, short-lived download URL), which the schema does not. It is nearly sufficient, with only idempotency and error behavior left unspecified given zero annotations.

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 both parameters are already documented, including the slug example and the license-issuance semantics of email. The description's restatement ('Requires the agent slug and the user's email') adds little beyond the schema, matching the baseline 3.

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?

States a specific verb (Claim) plus resource (Artemis GTM agent) and narrows it to the claude.ai chat-edition path, with an explicit carve-out that the free GTM Engineer itself needs no claim. It does not, however, name any sibling such as start_purchase or get_install_command, so routing between tools still requires inference.

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?

Gives a concrete when-to-use condition (user installs the free engineer from their buyer library rather than the CLI) and an explicit when-not (the free AI GTM Engineer needs no claim). No alternative tool is named for the non-claim cases, so the exclusion is behavioral rather than cross-tool.

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?

With no annotations, the description carries the full burden. It helpfully discloses the return payload and that both free and paid keys are accepted, but 'redeem' implies a state-changing operation (install creation, possibly key consumption) whose idempotency, reversibility, and auth requirements are never stated.

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 tight sentences with zero filler; the action is front-loaded and the return payload is summarized compactly in the second sentence.

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 single-parameter tool with no output schema, the description adequately covers the action and return shape. It falls short only on side effects, idempotency, and auth, which matter given the absence of annotations.

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?

Only one parameter with 100% schema description coverage, so the schema already documents it as a UUID license key. The description adds no format, validation, or provenance detail beyond what the schema provides — the baseline 3 for well-covered schemas.

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?

States a specific verb and resource — redeeming a license key into an install — plus the concrete outputs (agent slug, version, signed URL, npx command). It is distinguishable from claim_free_agent and start_purchase, though the 'works for both free and paid licenses' line blurs the boundary with claim_free_agent rather than sharpening it.

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?

Usage is only implied: the agent must infer that a license key has already been obtained via claim_free_agent or start_purchase before calling this. There is no explicit when-to-use statement, no prerequisites, and no named alternative to route against.

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?

No annotations are provided, so the description carries the behavioral burden. It discloses that the tool returns slug, name, problem solved, price, and detail URL, and that results can include free agents and bundles, but it does not explicitly state read-only behavior, pagination, authorization needs, or rate limits.

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?

The description is two sentences and front-loads the core action: listing the product, modules, and bundles. It is reasonably efficient, though the first sentence is dense with marketing jargon like 'B2B go-to-market leak' that slightly reduces immediate clarity.

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?

There is no output schema, but the description compensates by naming the returned fields. With only two optional, fully documented boolean parameters and no annotations, the definition is largely complete for a simple listing tool. It could be improved by explicitly relating it to the sibling action 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 two boolean parameters are already fully documented in the schema. The description aligns with those parameters by mentioning free agents and bundles, but it adds no extra meaning, defaults, or semantics beyond what the schema provides.

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 uses a specific verb, 'List', and clearly identifies the resource set: the free AI GTM Engineer, its installable build modules, and bundles. It is clear enough to distinguish a catalog-listing operation from the action-oriented siblings, though it does not explicitly name those siblings as alternatives.

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?

Usage is implied: the tool is for discovering agents/bundles that can later be recommended, claimed, or purchased. However, the description never explicitly says when to use this versus claim_free_agent, recommend_agent, start_purchase, or get_install_command. It provides context but no direct routing guidance.

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?

No annotations are present, so the description carries the behavioral burden. It usefully discloses the fallback outcome and that results include how to claim or buy, but says nothing about read-only nature, permissions, latency, or any limits on repeated calls.

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 that lead with the core action and follow with the fallback behavior; the inline examples earn their space by illustrating acceptable input. Some parenthetical example text could be trimmed, but nothing is redundant.

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 and no annotations, the description compensates by explaining what comes back (a single recommended agent plus how to claim/buy) and what happens when nothing matches. For a one-parameter recommendation tool this is complete enough to call correctly.

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% for the single parameter, so the schema already defines it; the description adds value by showing three concrete example problems that clarify the expected level of specificity and phrasing. One-parameter tools have little room for deeper semantics, so a 4 is appropriate.

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 concrete verb ('recommend') and resource ('the single Artemis GTM agent') and gives three parenthetical problem examples, so an agent immediately knows what it produces. It does not explicitly distinguish itself from siblings like list_agents or claim_free_agent, so it stops short of a 5.

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 clearly frames the trigger condition (a B2B go-to-market problem expressed in plain language) and even covers the no-match case by routing to the free AI GTM Engineer. It does not name a sibling tool as an alternative or state when not to use it, so it lacks explicit routing guidance.

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?

With no annotations, the description carries the full burden and does well: it discloses that the return is a hosted Stripe checkout URL, that card entry happens on Stripe and never within agent scope (a meaningful security boundary), and that the license lands in the user's library post-payment. It does not address repeat/idempotent calls or auth prerequisites, leaving a small gap.

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?

Three compact sentences with no filler; the core action and its payload are front-loaded, followed by the payment-safety note and the post-purchase next step.

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?

Given no output schema and no annotations, the description supplies the return value (checkout URL), the security boundary for payment, and the follow-up tool. That is sufficient for a single-parameter purchase-initiation tool, with only auth/idempotency behavior left unaddressed.

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?

Only one parameter with 100% schema coverage, so the baseline is 3. The description adds no syntax or format detail beyond what the schema already states, including the example slugs that already appear in the property description.

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?

States a specific verb and resource ('Begin purchase of a PAID Artemis GTM agent or bundle') and immediately scopes it to paid items, distinguishing it from the sibling claim_free_agent. It also names the deliverable (a hosted Stripe checkout URL), so an agent knows exactly what the call produces.

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 is for paid agents/bundles and routes the agent to the follow-up step (get_install_command after payment). It never explicitly says to use claim_free_agent for free items, but the capitalized 'PAID' scoping carries that implication.

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