Launchkit MCP

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

With no annotations, the description carries the burden and does well: it discloses on-chain verification (Transfer to configured address, required confirmations, amount), single-credit idempotency keyed on tx hash + log index, and cross-customer exclusivity. It omits what an agent observes on rejection (error vs. pending) and whether the call blocks until confirmations land.

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?

Short, front-loaded with the action, then verification mechanics, then the prerequisite. Every sentence carries signal, including the negative note about x402, though that clause is the least essential to invoking the tool correctly.

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 one-parameter mutation tool with no annotations and no output schema, this covers prerequisites, verification, idempotency, and exclusivity – the things an agent must know before writing money to a ledger. The remaining gap is the response/error surface, which is undocumented anywhere.

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% and the single parameter already documents the 0x-prefixed Base mainnet transaction hash. The description's 'Pass the transaction hash' adds context about which transfer to point at but no syntax or format meaning beyond the schema, so the baseline 3 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?

States a specific verb and resource ('Credit this API key after a USDC transfer on Base mainnet') and ties it to a concrete chain, asset, and target (the API key), which cleanly separates it from siblings like get_balance and get_payment_info. An agent knows exactly what action this performs 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?

Gives an explicit prerequisite and ordering: 'Call get_payment_info first for the address and packs', and rules out x402 explicitly as unimplemented. It does not spell out what to do when verification fails or when a user has already claimed, so it falls short of full when/when-not coverage.

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 must carry the full behavioral burden; it does disclose the key async trait (returns job_id immediately, assets via get_job) and that two variants are produced. It omits cost/credit implications (relevant given get_balance and list_pricing siblings) and any moderation or rights-enforcement behavior beyond what the schema already says.

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 tightly packed sentences: output spec first, async retrieval contract second. No filler, and the most decision-relevant facts are front-loaded.

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 3-param async tool with no output schema, it covers what is produced, at what size, and how to retrieve it, which is most of what an agent needs. The gap is the undocumented headline parameter and no hint about cost or failure modes.

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 67%: prompt and owns_rights are documented, but headline is undocumented in the schema and the description says nothing about it either. The description adds only the fixed dimension context, not meaning for any parameter, so the baseline 3 fits.

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 (Generate) and resource (two wide X banner variants) with exact output dimensions 1536x512 (3:1 / 1500x500 class), which cleanly separates it from the generic generate_image sibling. An agent knows precisely what artifact this produces 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?

It gives a clear follow-up workflow ('poll get_job for assets') but never states when to choose this over generate_image or the other kit tools, nor any prerequisites beyond the schema. Usage is implied by the fixed banner format rather than explicitly contrasted with alternatives.

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 at all, the description carries the full behavioral burden and it discloses exactly one real trait: 'Runs synchronously', which tells the caller no job polling (get_job) is needed. It says nothing about cost/credit consumption, rate limits, or what happens on refusal, which are the material behaviors for a paid media-generation call.

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, zero filler, and the most decision-relevant facts — what it produces, the exact kinds, and synchronous execution — are front-loaded and compressed into fragments that still parse cleanly.

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 and no annotations, so the description would need to say what comes back (asset URL? id? job reference?) and whether the call consumes credits, given that pricing/balance/payment siblings exist. It covers shape and execution mode but leaves the return value and cost profile entirely unspecified for a tool with three required parameters.

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 50% (prompt and owns_rights documented, kind and style not), and the description compensates by mapping the three enum values to concrete intents and adding banner dimensions (1536x512 / 1500x500) that appear nowhere in the schema. The one remaining gap is 'style', a 400-character free-form string with no explanation of expected content or examples.

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 (generate) and resource (one still image) and enumerates the three supported kinds, so an agent knows exactly what it produces. It partially distinguishes itself from kit siblings via 'one still', but never names generate_banner or generate_logo_kit, so the overlap with generate_banner (which accepts the same 'banner' kind) is left ambiguous.

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?

No explicit when-to-use/when-not guidance or prerequisites beyond the schema's owns_rights flag. The phrase 'Generate one still' implicitly signals single-asset usage versus the kit siblings, but the agent must infer which tool to pick when it wants a banner, since both this tool and generate_banner appear to cover it.

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 the async contract (returns job_id immediately so the connection need not stay open), the polling path via get_job, conditional ffmpeg mixing behavior, and per-tier pricing. It omits failure/refund behavior and whether a failed job still incurs cost.

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?

Four tight sentences, each delivering distinct information, with the output manifest front-loaded and the async/polling contract following immediately. No filler or restatement of the tool name.

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 multi-asset generation tool with no output schema and no annotations, the description covers what is produced, the async lifecycle, where to get results, and cost tiers. Gaps remain around failure handling, latency expectations, and the project_name parameter, but the core calling contract is complete.

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?

The description adds real semantics beyond the schema: it ties each tier enum value to a concrete price ($2.49 / $4.49 / $6.99), which the enum alone does not convey. The undocumented project_name parameter (accounting for the 50% coverage gap) is not addressed, so not a 5.

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+resource with exact output composition: 'logo x4, wide banner x2, alpha stickers x6, teaser, and music'. This clearly distinguishes it from single-asset siblings like generate_logo_kit, generate_banner, and generate_sticker_pack.

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 'full kit' framing implies this is the one-shot alternative to calling the individual generators, and it explicitly directs the agent to 'Poll get_job for status, progress, and asset links'. However, it never states the inverse condition (use generate_logo_kit if you only need logos), so the routing is implied rather than explicit.

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 disclose the key behavioral trait: it is asynchronous and returns a job_id immediately rather than assets. However, it omits cost/credit implications, failure modes, and the significance of the mandatory owns_rights confirmation.

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, zero filler, with the deliverable stated first and the async return/polling contract immediately after. Every clause earns its place.

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 tool with no output schema and no annotations, the description covers the two things an agent most needs: what is produced and that the result arrives via get_job. Minor gaps remain around cost and the hard owns_rights=true gate, but nothing blocking 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 67% — prompt and owns_rights are documented in the schema, project_name is not. The description adds no parameter meaning at all (not even that prompt drives the four variants), so it neither compensates for the gap nor adds value 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?

States a specific verb and resource plus the concrete deliverable: four named logo types (wordmark, emblem, lettermark, mascot). This clearly distinguishes it from generate_banner, generate_music_bed, or generate_teaser_video, though it doesn't explicitly say how it differs from the closer sibling generate_image.

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?

Provides a follow-up workflow instruction ('poll get_job for assets'), which is genuinely useful, but gives no guidance on when to pick this over generate_image or generate_launch_kit, and no prerequisites or exclusions are stated.

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 whole burden, and it does disclose the single most important trait: this is asynchronous and returns a job_id that must be polled via get_job. It says nothing about cost/credits, expected generation latency, output audio format or length, or whether the request is billed even on failure — gaps that matter given the presence of get_balance and list_pricing siblings.

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 short sentences with zero filler: the first states what is produced, the second states the async contract and the next tool to call. The most actionable information (job_id + get_job) is front-loaded 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?

The async lifecycle is covered, but for a paid generative tool with no annotations and no output schema, an agent still lacks cost expectations, rough generation duration, and what the finished asset looks like (duration, format). Adequate to invoke, thin for planning around it.

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 67%, and the description adds no parameter-level meaning at all — 'mood' is undocumented in both places, and nothing explains how 'prompt' for a music bed should differ from a prompt for generate_image. The required owns_rights licensing gate is entirely schema-borne, so the description contributes nothing here.

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 names a specific verb and resource ('Generate an instrumental music bed') plus the intended use case ('launch video or stream'), which clearly separates it from generate_image, generate_banner, and generate_teaser_video. It stops short of explicitly naming any sibling as the alternative, so it lands at a strong 4 rather than 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 gives concrete usage context (launch video or stream) and the critical follow-up workflow: 'Returns a job_id immediately; poll get_job,' which routes the agent to the successor tool. It does not state when NOT to use this tool (e.g. voiceover or full-song requests), so it is clear but not exhaustive.

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 the async job pattern, the exact output format (512x512 PNG, true alpha via solid plate + BiRefNet cutout), and the fixed count of six stickers. It omits cost/payment implications, notable given the presence of get_balance, list_pricing, and claim_payment siblings.

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 dense sentences with zero filler; the output shape is front-loaded and the async polling instruction follows immediately after. Every clause conveys information an agent needs.

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?

No output schema exists, but the description compensates by specifying the artifact format, count, and alpha-channel technique, plus how to retrieve results via get_job. The remaining gap is the absence of any cost, credit, or failure-mode context for what is clearly a paid generation operation.

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 prompt and owns_rights are already documented in the schema. The description hints that the prompt drives character consistency ('consistent-character') but adds no syntax, length, or rights-enforcement detail beyond the structured fields, so baseline 3 applies.

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 with concrete output specs: 'Generate six consistent-character Telegram stickers, 512x512 PNG with a real alpha channel.' The Telegram-sticker framing implicitly separates it from sibling generators like generate_image, generate_banner, and generate_logo_kit, though it never names them explicitly.

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 explicit downstream workflow guidance — the tool returns a job_id immediately and the caller must poll get_job for assets — which names the alternative tool and the condition for using it. It does not, however, say when to pick this over the other generation siblings.

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 burden and does well: it discloses async behavior (returns job_id immediately, poll get_job), the ~10s output length, that text is never baked in, and that project_name is only applied in post when ffmpeg is available — implying graceful degradation. It omits cost/rate-limit implications and what happens on a failed render job.

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?

Four short sentences, front-loaded with the deliverable and its constraints, then tier guidance, then the async/return contract, then the music alternative. No sentence is redundant with another.

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 supplies the essential return contract (job_id + poll get_job) and the asset characteristics an agent needs to build a prompt. It leaves cost/balance considerations to the sibling pricing tools, which is reasonable, but the absence of any failure-mode note keeps it just short of complete.

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 only 50%, and the description compensates for both undocumented parameters: it explains that project_name is a post-production overlay applied only when ffmpeg exists, and that tier=budget maps to MiniMax Turbo. The two schema-documented params (prompt, owns_rights) need no further help.

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 opening sentence names a specific verb ('Generate'), the exact asset ('~10 second launch teaser'), and two defining constraints ('original', 'no baked-in text') that separate it from generate_banner and generate_image. It also names the sibling that handles the adjacent asset (music via generate_launch_kit).

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 explicit guidance on the tier choice ('Use tier=budget for MiniMax Turbo'), the next action after calling ('poll get_job'), and where to get music instead ('separate tool or mixed in generate_launch_kit'). It does not state when to prefer this tool over generate_image or generate_banner for a launch asset, so it stops short of a full routing rule.

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 exist, so the description carries the full burden; 'Return' plus the caller-scoped wording does establish this is a safe per-caller read with no arguments. However, it says nothing about auth requirements, rate limits, credit units, or error behavior, and with no output schema the return contract is only a one-line summary.

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 front-loaded sentence that enumerates exactly the three returned values with zero filler. Nothing could be removed without losing information.

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 zero-parameter read tool with no annotations and no output schema, naming the three returned fields is the right level of completeness. Minor gaps remain (units/currency of credits, whether the caller is inferred from the session), but nothing blocks correct invocation.

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?

There are zero input parameters, so there is nothing for the description to disambiguate. Baseline 4 applies; the schema is an empty object and needs no elaboration.

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 ('Return') and the exact resource fields (remaining credits, daily spend, spend cap), so the agent knows precisely what comes back. It does not explicitly contrast with nearby siblings such as list_pricing or get_payment_info, so it falls short of full sibling differentiation.

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 read-only nature and the returned fields imply the usage ('check my balance'), but there is no explicit when-to-use statement. No alternative is named — an agent unsure whether it wants balance vs. pricing (list_pricing) or payment details (get_payment_info) gets no routing help.

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 usefully discloses the return shape (status, progress, asset links when done) and the API-key scoping constraint. It omits terminal-state semantics, whether an unknown or expired id errors, and whether reads are side-effect free.

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 short sentences, front-loaded with the action, then the payoff, then the scoping caveat. Nothing is padded or repeated.

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 polling tool with no output schema, the description covers the verb, the required input's origin, the return fields, and auth scoping. Polling cadence and terminal/error states are the remaining gaps.

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 the schema already explains that job_id comes from an async generate tool, so the description adds almost nothing beyond 'by id'. Baseline 3 applies when the schema does the heavy lifting.

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 ('poll a background generation job by id') plus the return payload, which is enough to tell it apart from the generate_* siblings that create jobs. It stops short of naming those siblings explicitly as the creating counterpart.

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?

'Poll' implies repeated invocation while a job is in flight, and 'by id' ties it to the async generate tools, so usage is inferable. However, it gives no guidance on polling cadence, when to stop, or what to do with a failed/expired job id.

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 must carry the full burden, and it does disclose the network/token constraint, the human-free workflow, and the x402 caveat. It stops short of stating that this is a read-only operation, whether the receiving address is stable or single-use, and any authentication requirements.

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 tight sentences: returned payload first, then the operational steps, then the forward-looking caveat. Every sentence earns its place and the most important information (what it returns and how to pay) is front-loaded.

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 does the right thing by enumerating the returned fields and the follow-up call. For a zero-parameter informational tool it is nearly complete; only the response shape and whether the address is reusable are left implicit.

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?

The tool takes zero parameters, so there is nothing for the description to document beyond what the empty schema already conveys. Baseline 4 applies; no parameter claims are made or missing.

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 and enumerates exactly what is returned: the USDC-on-Base receiving address, network, token, credit packs, and top-up instructions. This is far more useful than a tautology, though it does not explicitly differentiate itself from siblings like list_pricing or get_balance, which also touch on credits and pricing.

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 states the concrete trigger (an agent topping up its own credits without a human), the required network/token (native USDC on Base mainnet), the post-condition (wait for confirmations, then call claim_payment with the tx hash), and an explicit non-option (x402 is not implemented). That is when-to-use, sequencing, and exclusions all in one paragraph.

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 burden. It usefully discloses the pricing unit ('1 credit = $0.01'), which is genuine domain context an agent cannot infer from a zero-parameter schema. However, it never states that the operation is read-only/safe or that it needs no authentication, and it gives no indication of result shape beyond 'credit prices'.

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 short sentences with no filler. The core purpose is front-loaded, the unit conversion follows, and the purchase routing comes last where it belongs. Every sentence earns its place.

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 zero-parameter, non-mutating catalog tool with no output schema, the description covers what is returned (prices for every generation tool and launch-kit tier) and the unit of account. Since no output schema exists, a brief hint at return structure would have closed the remaining gap.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies a parameterless, full-catalog listing rather than a filtered query.

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 ('List credit prices') plus the exact scope covered ('every generation tool and launch-kit tier'). This clearly separates it from sibling tools like get_balance and get_payment_info, which handle account state rather than a price catalog.

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?

Explicitly routes the agent elsewhere for a related need: 'To buy credits with USDC on Base, use get_payment_info and claim_payment.' That names the alternatives and the condition selecting them. It does not state when-not to use this tool (e.g., that it takes no arguments and needs no setup), but the usage context is clear.

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