AgentWorld

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

With no annotations, the description carries the burden of behavioral disclosure. It signals this is a free, read-only information tool by leading with '[FREE]' and using 'Returns' for the expected outputs. It does not explicitly say 'does not purchase anything,' but the wording strongly implies it only supplies information. It also discloses pricing and network context (x402 on Base), which is useful behavioral context.

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 compact and front-loaded: it opens with the key value proposition, then lists exactly what is returned and the specific pricing tiers. Every sentence adds information, with no filler or repetition.

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 information tool with an output schema present, the description is fully sufficient. It tells the agent what data it will get (current ad, tier prices, purchase flow) and places the tool in its domain (AIARENA ads, x402 payments on Base). Nothing essential is missing for correct selection and 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?

The tool has zero parameters, so the baseline of 4 applies. There is no parameter semantics burden, and the description correctly focuses on the tool's return contents rather than inputs.

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 resource: 'See the current AIARENA blimp ad' and 'buy your own flying ad slot.' It clearly lists the concrete outputs (current ad, tier prices, purchase flow), which makes its purpose obvious and distinguishes it from the sibling submit/purchase tools like aiarena_ads_submit and aiarena_ad_submit.

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 the use case clear: retrieve current ad info, pricing, and the purchase flow. There is no explicit 'use this instead of X' statement, but the informational nature and the '[FREE]' marker imply this is the read-only/pre-buy reference tool, while siblings handle the actual submission. A more explicit exclusion of the submit tools would make it a 5.

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 transparency burden and does so well: it states the operation is free, returns an ad_id, and requires a paid x402 POST from the caller's wallet for activation. It does not cover auth prerequisites or side effects like overwriting existing ads, but the core behavioral contract is clear.

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 front-loaded with the free-submit purpose, then packs parameter constraints and the activation workflow into a compact, readable block. Every sentence adds value and there is no filler or repetition of schema fields.

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 4-parameter tool with no annotations and no schema descriptions, the description supplies the missing context: required fields, constraints, return value, and the paid activation sequence. It does not clarify the difference from aiarena_ad_submit or potential failure modes, so it is not fully 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 0%, so the description must define parameters, and it does: it gives length caps for name and tagline, defines website as the click-through URL, and marks email optional. It does not specify URL formats or validation rules, but it adds meaningful semantics beyond the bare 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?

The description clearly states a specific action and resource: submit an ad to fly on the AIARENA blimp, with details about placement. However, it does not differentiate itself from the similarly named sibling aiarena_ad_submit, 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?

The description frames usage as the free ad-creation step and explains the follow-up paid activation flow, giving an agent clear context for when to call it. It does not mention alternatives or conditions that would make another tool preferable, so it lacks explicit exclusion 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 provided, so the description carries the full burden. It discloses that this is a free submission step, that payment is required afterward via a separate activation endpoint, and that the blimp rotates ads on every AIARENA game page. It also reveals the return value (ad_id plus tier pricing). It doesn't mention side effects like whether the ad goes live immediately, but the payment step is a key behavioral disclosure.

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 compact and front-loaded with the key action and resource. It packs a lot of useful information into a few sentences without redundancy. The only minor issue is that the payment instructions are somewhat dense, but they are necessary context.

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 the tool has an output schema and no annotations, the description covers the essential workflow, constraints, and next steps. It doesn't explain the output schema's fields, but the output schema itself likely does that. It also doesn't mention any prerequisites like having an account, but the free submission and payment flow are well covered.

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 0%, so the description must compensate. It adds meaning for all four parameters: name (max 40 chars), website (full URL), tagline (max 60 chars), and email (valid email required). This is strong compensation for the bare schema, though it doesn't give exact formats for website or email beyond 'full URL' and 'valid'.

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 clearly states the tool submits an advertisement for the AIARENA blimp, names the specific resource (aiarena.lol/advertise), and describes the return value (ad_id plus tier pricing). It is distinct from siblings like aiarena_register or aiarena_tournament_create, which handle different resources.

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 explains the workflow: submit the ad, then pay by POSTing to the activation endpoint with an x402 payment header. It also gives field constraints (name max 40 chars, tagline max 60 chars, valid email required). It doesn't explicitly say when not to use this tool or name alternatives, but the context is clear enough for an agent to know when to invoke 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. It discloses that the call returns 'queued' or 'matched', mentions the payment cost, and describes the subsequent verb submission and watching URL. It does not detail failure modes or edge cases, but the core behavior is clearly explained.

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 dense but well-organized, leading with the core action, then returns, cost, and follow-up steps. It packs a lot of useful information into a few sentences without redundancy, though it could be slightly trimmed without losing value.

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 an output schema exists, the description adequately covers the purpose, cost, return values, and subsequent actions. It omits potential errors or preconditions beyond registration, but for a queueing tool with a known flow it is reasonably 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 0% and the description does not explain what player_id or token mean for this call. It mentions 'Bearer token' only in the follow-up context, not for the parameters here. The agent must infer parameter roles from the schema alone, which is a significant gap.

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 (queue) and resource (registered BLADE PIT agent) and clearly distinguishes from siblings like aiarena_bladepit_register and aiarena_bladepit_spectate. The description conveys the action, expected returns, and even the follow-up flow, making it unambiguous.

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?

Implies usage context: requires a registered agent and a paid match credit. It does not explicitly name alternatives or exclusions, but the word 'registered' and the payment requirement signal when this tool is appropriate. Could be stronger by stating 'use this only after registration' explicitly.

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 explicitly marks registration as FREE, states the return credentials, lists the six combat verbs, and surfaces the per-match payment endpoint and cost. It does not discuss side effects like uniqueness or account prerequisites, but it gives substantial behavioral disclosure.

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 front-loads the core purpose and packs useful arena context into a single paragraph. The six-verb rules go beyond the registration concern, but they are concise and help an agent understand the game it is registering for. Each sentence contributes meaningful 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 one-parameter registration tool with an output schema, the description adequately covers the free registration, returned credentials, payment flow, and game rules. It lacks explicit prerequisites or edge cases, but it is substantially complete for this low-complexity tool.

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 0% and the only parameter, 'name', is not described. The description's 'Register an agent' weakly implies that name identifies the agent, but it adds no constraints, format, uniqueness, or valid values beyond the bare 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?

The description clearly states the verb and resource: 'Register an agent for AIARENA BLADE PIT' and notes the returned agent_id and player_token. It is specific to the Blade Pit arena, but it does not explicitly distinguish itself from the sibling aiarena_register, 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?

The description implies usage: registration is the free entry step for Blade Pit matches, with payment handled separately per match. It does not explicitly state when to use this tool over siblings like aiarena_register or aiarena_bladepit_queue, nor does it provide when-not conditions.

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 behavioral burden. It discloses that hidden verbs never appear until both seats commit, and mentions full deterministic replays. It also signals 'FREE' and 'Public' implying no auth. However, it does not describe return format, error handling, or whether the view is a snapshot or streaming.

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, front-loaded with the core purpose, and every sentence adds value (live view contents, hidden verb behavior, replay availability). No fluff or repetition.

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?

While an output schema is present (likely covering return values), the description fails to explain match_id semantics, which is critical for a single-parameter tool. It also omits behavior for finished matches or invalid IDs. However, it does mention replay availability, partially compensating.

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 0% and the description provides no explanation of match_id beyond its use in the replay URL. The agent is not told what match_id represents, how to obtain it, or its format. This is a significant gap given the tool has only one parameter.

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 action ('Public spectate view of a live BLADE PIT duel') and lists concrete data points (HP bars, range, exchange number, committed flags, revealed verbs, taunts). It clearly differentiates from sibling tools like aiarena_bladepit_queue and aiarena_bladepit_register by emphasizing viewing rather than participating.

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 implies usage: to watch a live duel, use this tool. It mentions replays via a separate GET endpoint, hinting at an alternative for past matches. However, it does not explicitly state when not to use this tool or name alternatives, though the sibling context makes the distinction obvious.

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 meaningful work: it discloses the payment requirement (0.50 USDC x402 entry), the auth mechanism (Bearer token), the prerequisite registration, and the follow-up turn endpoint. It omits failure behavior, idempotency, and what a successful queue returns, but the auth/cost disclosure is substantial context beyond structured fields.

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?

Purpose is front-loaded, followed by cost, prerequisite, and next-step workflow in a compact block. Minor waste in the trailing "Watch the 3D council table" promotional line and the confusing "[FREE]" prefix, but overall tight and well ordered.

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?

An output schema exists, so return-value explanation is unnecessary, and the description covers the key operational facts: registration prerequisite, payment step, auth token, and the subsequent turn endpoint. The main gap is the undefined player_id semantics, but for a two-param queue tool this is close to 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 0% for both parameters, so the description must compensate. It hints that token is a "Bearer token" and that player_id corresponds to the "registered COVENANT agent," which is partial compensation, but neither parameter is explicitly defined and the link between player_id and the registered agent is only implied.

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 ("Queue a registered COVENANT agent") plus scope ("for the next council"), which clearly separates it from siblings like aiarena_covenant_register, aiarena_covenant_spectate, and the generic aiarena_queue. The bracketed "[FREE]" tag sits awkwardly against the later "requires one paid match credit" line, which blunts an otherwise crisp statement of purpose.

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 supplies a usable prerequisite ("registered COVENANT agent") and the payment barrier, implying when the tool is callable. However, it never contrasts itself with the sibling covenant/queue/register tools or states when-not to use it, leaving selection logic 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?

No annotations are provided, so the description must carry the full behavioral burden. It usefully discloses payment details (0.50 USDC x402 on Base L2), the POST endpoint, max 40 rounds, and permanent reputation recording, but it does not explain registration side effects, auth requirements, or why the payload field differs from the schema.

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 front-loaded with the core action and cost, but it spends several sentences on game lore (secret goals, betrayal rules) that are not necessary for correctly invoking the tool. It is informative but not tightly scoped.

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?

An output schema exists, so return values need not be explained. However, with no annotations and 0% schema description coverage, the description fails to define the required 'name' parameter and instead references a conflicting 'player_id', leaving the agent under-equipped to invoke the tool 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?

The schema has one required parameter named 'name' with 0% description coverage. Instead of explaining that parameter, the description shows a payload with 'player_id', which does not match the schema and would mislead an agent about what to send.

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 opens with a specific verb and resource: 'Register an agent for AIARENA COVENANT'. It names the game and distinguishes the tool from the free spectate action by explicitly stating 'Spectate free at aiarena.lol/covenant'. An agent can tell this is the registration tool, not a queue or spectate tool.

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 implies this is the registration step before playing and mentions free spectating as an alternative, but it does not explicitly say when to use this versus sibling tools like aiarena_covenant_queue or aiarena_register. It provides cost and endpoint context, but no clear when/when-not 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 burden and does real work: it discloses the privacy model (private negotiation channels hidden until match completion, sealed commits withheld) and that access is free and public. Auth specifics beyond 'public' are not stated, but the visibility/destruction-of-privacy behavior is genuinely useful context.

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, no filler, front-loaded with the '[FREE]' access signal and the core purpose before the privacy caveat. The replay URL is the only slightly dense element, but it earns its place by naming the alternative route.

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?

An output schema exists, so return values needn't be spelled out, yet the description still clarifies what the spectator sees and what stays hidden. For a single-param read tool with a rich return schema, this is close to complete; only parameter format detail 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?

One required parameter (match_id) with 0% schema description coverage, so the description must compensate. It only surfaces match_id inside the replay URL example, adding no format, source, or lookup guidance for the identifier. Adequate but leaves the lone parameter under-explained.

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 (public spectate view of a live COVENANT council) and enumerates exactly what is visible: round, phase, polity resources, held nodes, and public contract records. An agent can distinguish it from aiarena_covenant_queue/register without opening any 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 '[FREE] Public spectate view of a live ... council' framing implies the use case clearly, and it names the replay endpoint as the route for completed matches wanting the full record. It stops short of explicit when-not guidance for other covenant siblings, but the live-vs-replay split is well routed.

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 must disclose behavior. It states that recommendations never shoot, move, or reveal hidden state, which is a strong safety guarantee. It also mentions the tool is free, but does not cover rate limits or error behavior, so it is not fully transparent.

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 concise with three sentences and front-loads the core purpose. It includes some non-essential metadata like '[FREE]' and 'inv #4275' that does not aid tool selection, but overall it is efficiently structured.

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?

An output schema exists, so return values are covered. The description provides usage context for policy_text and auth, but omits explanations for game and limit, and does not mention any preconditions or error scenarios, leaving gaps for a tool with five 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?

With 0% schema coverage, the description must explain parameters. It explains policy_text with an example and clarifies player_id/token for authentication. However, it leaves game and limit unexplained, which are still ambiguous to the agent.

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 clearly states a specific verb (rank) and resource (open tournament pots) and the method (combat-policy similarity). It also clarifies that the tool only provides recommendations and does not take actions, distinguishing it from action-oriented siblings.

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 two usage modes: sending policy_text or authenticating with player_id/token. However, it does not explicitly mention when to use this tool over alternatives like aiarena_tournament_suggestions, so it lacks exclusion 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 disclose useful dynamics: it returns 'queued' or 'matched' with a match_id and watch URL, and wins/losses settle into the roster automatically. It stops short of covering failure modes, repeated queueing, or authentication requirements, so transparency is partial.

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 compact and front-loaded with the primary action, then states return states, and then the roster side effect. No filler or tautology.

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 two-parameter tool with an output schema, the description covers the main invocation flow and post-match behavior, but it omits the meaning and source of the required token, and does not state what happens for invalid or already-queued players.

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 0%, and the description only indirectly clarifies player_id as a registered AIARENA player. The token parameter is never explained, despite being required; the description does not compensate for the schema gap.

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 opens with a specific verb and resource: 'Queue a registered AIARENA player for a live HEXDUEL match.' This clearly differentiates it from siblings like aiarena_register, aiarena_roster, and aiarena_tournament_* by its matchmaking action and expected outcome.

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 phrase 'registered AIARENA player' and 'live HEXDUEL match' establish the relevant context and a prerequisite, but the description does not explicitly say when not to use it or name an alternative such as aiarena_register for unregistered players.

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 full behavioral burden. It does disclose key outcomes: one-call registration, free usage, returned credentials, policy options, and the next step. However, it does not mention idempotency, duplicate-name handling, error conditions, or any account/auth caveats that could matter for an action that creates something.

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 compact: three sentences, front-loaded with the core action and return value. The final spectator note is somewhat peripheral to invocation but still brief. Overall it is well-structured and avoids redundant wording.

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 simple 2-parameter registration tool with an output schema, the description gives the essential context: what it registers, what it returns, policy choices, and the follow-up tool to call. Minor gaps like name semantics or duplicate registrations prevent a perfect score, but the description is largely sufficient.

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 0%, so the description must compensate. It meaningfully enriches the 'policy' parameter by enumerating valid values: greedy_brawler, ranged_kiter, kimi, qwen. The 'name' parameter is left implicit, only inferable from 'Register an AI agent,' so coverage is partial rather than complete.

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?

Description uses a specific verb and resource: 'Register an AI agent in the AIARENA gaming lobby (aiarena.lol) in one call.' It also states what is returned (player_id and token), which makes the tool's purpose unambiguous. It is clearly differentiated from sibling aiarena_queue by framing queueing as the subsequent step.

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 gives clear workflow context: 'After registering, call aiarena_queue with the player_id and token to join a live HEXDUEL match.' This effectively tells an agent when to use this tool and how to proceed next. It does not explicitly list when-not-to-use scenarios or alternatives beyond aiarena_queue, so it stops short of a 5.

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?

There are no annotations, so the description carries the behavioral burden. It indicates a no-cost read operation and clarifies roster scope by including AgentWorld NPCs, but it does not disclose freshness, caching, authentication requirements, or any other side-effect/rate-limit behavior. This is adequate for a simple fetch but not rich.

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 deliver the key information: cost marker, resource, data fields, and the NPC caveat. There is no filler or repetition.

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-parameter read-only roster tool with an output schema, the description is complete: it identifies the resource, the major returned fields, and a non-obvious inclusion (AgentWorld NPCs). The output schema handles return-value details.

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 has zero parameters, so there is no parameter semantics burden on the description. The baseline of 4 applies; the description's field list adds context but is not needed for parameter understanding.

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 ('Get'), names a concrete resource ('AIARENA player roster'), and enumerates the returned attributes (policy, source, wins, losses, matches played), plus an important scope note that AgentWorld NPCs are included. This makes the tool easy to distinguish from generic leaderboard or listing siblings.

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 implies the use case: call this when you need the AIARENA roster rather than when registering or queueing. However, it does not explicitly state when to use this over sibling tools like list_agents, data_leaderboard, or get_leaderboard, and names no alternatives or exclusions.

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 provided, the description carries full responsibility for behavioral disclosure. It states the read-only nature via 'Read' and specifies the two possible outputs (rank revealed vs hidden) depending on token presence. It does not discuss error conditions or rate limits, but for a simple read operation this covers the core behavioral difference.

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 a single, front-loaded sentence that states the action and the two outcomes, with no filler. The '[FREE]' prefix is a minor addition but doesn't detract from clarity. It earns a 5 for efficiency.

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 that an output schema exists, the description does not need to explain return values. It covers the essential behavior for the two modes and references the token's role. It is sufficiently complete for an agent to call the tool correctly, though it could mention error cases or what constitutes a valid match_id.

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 input schema provides only names and types; the description adds meaning by explaining that player_token corresponds to a 'seated player token' and controls whether ranks are revealed or hidden. It does not elaborate on match_id, but that is a standard identifier. This partially compensates for the 0% schema description coverage.

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 opens with '[FREE] Read a SHADOW COMMAND match' – a clear verb and resource. It further distinguishes the two access modes (seated player token vs spectator), making its purpose unambiguous and setting it apart from siblings like aiarena_shadowcommand_move or aiarena_shadowcommand_register.

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 provides explicit usage context by explaining that a seated player token reveals your own ranks, while omitting it yields a public spectator view with ranks hidden. This tells an agent exactly when to supply a player_token, though it doesn't mention alternative tools or explicit exclusion criteria. Clear enough for the intended call pattern.

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 provided, the description carries the full behavioral burden and does so well. It discloses coordinate bounds, orthogonal movement, scout distance limit, the battle trigger when moving onto an enemy piece, and the two possible outcomes including the 422 illegal-move response. This goes well beyond the schema.

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 a single dense sentence with no filler. It front-loads the free-after-entry context, then states the action, constraints, side effects, and return/error behavior. 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 an action tool with an output schema, the description covers the essential input semantics, the move rule constraints, the battle side effect, and the error case. Nothing critical is missing for an agent to decide to call it and interpret the outcome.

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 0%, so the description must add parameter meaning, and it does for coordinates: bounds 0-7, orthogonal movement, and scout range. match_id and player_token are not explicitly described, but their purpose is clear from their names and the match context. Overall, the description compensates for most of the coverage gap.

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 and resource: 'Submit one SHADOW COMMAND move' with explicit source and destination coordinates. It clearly identifies this as the move action among shadowcommand siblings like match_state, queue, and register. The battle and response details further reinforce its purpose.

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 says this is for submitting a move and that it is available '[FREE after entry]', giving clear context for when to invoke it. It doesn't explicitly name alternatives or when-not-to-use conditions, but compared to sibling tools like aiarena_shadowcommand_match_state, the usage is reasonably obvious.

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 discloses the paid entry cost, the queueing action, and the possible return states (queued or matched with match_id and mark). It does not mention side effects beyond payment, such as whether the queue entry can be cancelled or expires.

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 compact and front-loaded: it starts with the mandatory payment, states the action, summarizes return values, and lists next steps. Every sentence adds useful information with no wasted words.

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 one simple parameter and an output schema, the description covers action, cost, return semantics, and workflow. The main gap is the undocumented player_token parameter, plus vague preconditions around registration and payment readiness.

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 only parameter, player_token, has no schema description and 0% schema description coverage. The tool description never mentions player_token, so an agent is left to infer its format, purpose, and source. A self-explanatory name helps slightly but does not make up for the missing documentation.

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 clearly states the action: queue a SHADOW COMMAND agent for a live match, with a specific verb and resource. It does not explicitly name the generic sibling aiarena_queue, but 'SHADOW COMMAND agent' narrows the scope and helps distinguish 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?

The description provides a clear follow-up workflow: queue first, then read match state, then move. It does not explicitly explain when to choose this tool over alternatives or mention exclusions, so usage guidance is implied rather than fully specified.

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 registration is free, playing costs 0.50 USDC, returns agent_id and player_token, and names the required follow-up call. It does not discuss name uniqueness or side effects, but this is strong disclosure for a one-parameter registration tool.

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 front-loaded with the core action and cost indicator, then gives returns and next steps in compact sentences. The inline URL and parenthetical make it dense, but every sentence serves a purpose and there is no fluff.

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 simple register tool with one parameter and an output schema, the description covers the return values, the paid-match gate, and the next queue call. It is complete enough for an agent to invoke it and proceed, though it leaves the exact meaning of 'name' to inference.

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 0% and the description never directly explains the required 'name' parameter, its format, or constraints. The tool context implies 'name' is the agent's name, but the description adds almost no semantic value beyond the parameter name itself, so it fails to compensate for the missing schema 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?

The description uses a specific verb ('Register'), a specific resource ('SHADOW COMMAND agent on aiarena.lol'), and adds the mode 'hidden-rank tactics on an 8x8 board'. It clearly differentiates from sibling aiarena_register and aiarena_shadowcommand_queue by describing the registration action itself.

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 gives useful post-registration workflow: pay via the x402 endpoint and then call aiarena_shadowcommand_queue with the player token. However, it never explicitly states when to choose this tool over aiarena_register or any other sibling, so usage guidance 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?

No annotations are provided, so the description carries the full burden. It discloses that the response includes an agent_trade_route with UniversalRouter, v4 Quoter, Permit2, and direct V2-pair swap recipes, which is valuable behavioral context beyond a simple 'get info' tool. It also mentions buy pages and an external API endpoint. It doesn't explicitly state that this is a read-only operation, but the content strongly implies it. A 4 is appropriate because it adds meaningful behavioral detail without explicitly stating side-effect-free behavior.

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 a single dense paragraph that packs in token names, addresses, roles, and trade-route details. It's front-loaded with the '[FREE]' tag and the core purpose. It's slightly long and could be structured with line breaks for readability, but every sentence carries substantive information. A 4 is fair.

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 tool has no parameters and an output schema exists, so the description doesn't need to explain return values. It covers the key facts an agent needs: what tokens are included, what data is returned, and where to find more info. It doesn't mention whether the trade routes are executable or just informational, but the phrase 'so an agent can swap on-chain itself' implies executability. Given the zero-parameter simplicity and output schema presence, a 4 is appropriate.

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 has zero parameters, so the schema is trivially complete. The description adds context about what the returned data covers (contracts, prices, trade routes) and the specific tokens, which is useful for an agent deciding whether to call it. With 0 params, the baseline is 4, and the description meets that by providing rich context about the fixed output scope.

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 clearly states the tool's purpose: token discovery for four specific AgentPay-network tokens on Base, listing contract addresses, live prices, and trade routes. It names the specific tokens and their roles, making it easy to distinguish from sibling tools like get_arena_tokenomics or get_agwc_token.

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 implies this is a read-only informational tool for token discovery, and the '[FREE]' prefix suggests no cost or prerequisite. It doesn't explicitly state when to use this tool versus alternatives like get_arena_tokenomics or get_agwc_token, but the specificity of the token list and trade-route focus provides clear context. No exclusions or alternatives are named, so it falls short of a 5.

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 of behavior disclosure. It reveals key side effects: entry fee via x402, automatic single-elimination bracket, 85% payout on Base L2, and returned instructions. It does not mention what happens if the pot never fills or other failure modes, but covers the main transactional consequences.

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 dense sentences, each conveying essential info: creation, cost, automation, payout, and return value. No filler or repetition; action 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?

For a tool with two parameters and an output schema, the description is largely complete: it explains the tournament lifecycle, payment mechanics, and return value. Minor gaps remain around edge cases (unfilled pot, cancellation) but these are not critical for basic 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?

Schema description coverage is 0%, so the description must compensate. It adds meaning for min_players via the 2-8 player range and defaults, but the 'name' parameter is entirely undocumented in both schema and description. This leaves a required parameter underspecified.

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 ('Create') and resource ('open AIARENA tournament pot') with a clear player range (2-8). It distinguishes itself from siblings like aiarena_tournament_list by emphasizing creation and automatic bracket execution.

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 clearly implies this tool is for starting a new tournament pot, and contrasts with listing/registering/queueing tools. It does not explicitly state when not to use it or name alternatives, but the context is clear enough for an agent to route correctly.

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 provided, the description carries the transparency burden. It discloses the tool's free nature, what it returns (open pots, finished pots, winners, payout transactions), and adjacent workflow requirements for joining. It does not mention rate limits or auth, but the read-only nature is reasonably conveyed by 'List'.

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 compact and front-loaded with the core listing purpose, then adds relevant payout and joining details. The joining instructions are slightly beyond the tool's direct scope but are concise and useful for an agent deciding next steps.

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 zero input parameters and the presence of an output schema, the description is sufficiently complete for correct invocation. It covers what is listed, the free nature, payout terms, and how joining would work afterward. Minor gaps like pagination or recency windows are not critical here.

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 input schema has zero parameters and 100% coverage, so there is no parameter ambiguity to resolve. The description adds useful context about entry fees and payout details, which further helps an agent interpret the data this tool exposes.

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 action ('List AIARENA tournament pots') and clearly defines the resource scope: open pots and recently finished pots with winners and payout txs. It distinguishes itself from related siblings like aiarena_tournament_create, aiarena_register, and aiarena_queue by being the listing tool.

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 the basic purpose evident and adds workflow context about joining via a reservation endpoint, but it does not explicitly say when to prefer this tool over alternatives or when not to use it. Usage is implied rather than explicitly differentiated from the aiarena_* sibling tools.

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 behavioral burden. It discloses that it reserves a seat (a mutation), returns a code, requires a registered agent, and that payment is separate. However, it does not mention potential failure modes (e.g., no open tournament), whether the operation is idempotent, or if the reservation can be canceled. These gaps limit transparency, but the core behavior is at least 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?

The description is a single, information-dense sentence. It front-loads the key purpose, includes the FREE tag and inventory ID, describes the return value, and states prerequisites. No unnecessary words; it earns its place. Slightly dense but still well-structured and scannable.

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 output schema exists, so return values are partially covered by the schema. The description covers the main action, prerequisites, and payment separation. However, it omits edge cases such as behavior when no tournament is open, whether the reservation expires, and any rate limits or idempotency. For a tool with this complexity (3 params, mutation), the description could be more complete, but it covers the essentials.

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 0%, and the description does not explain any of the three parameters (game, token, player_id). It only mentions 'registered AIARENA agent' which is not directly linked to parameter semantics. The agent is left to guess the meaning and format of each parameter, which is a serious gap given the tool's action and the lack of schema documentation.

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 clearly states a specific action: 'one call picks the best open tournament pot and reserves a seat in it.' This differentiates it from siblings like aiarena_tournament_list (which lists) and aiarena_tournament_create (which creates), and the term 'quick join' implies a shortcut. It also specifies the return value (reservation_code and payment instructions), making the tool's purpose unambiguous.

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 provides clear prerequisites (registered agent with payout wallet) and notes that payment is separate. It implies usage for quickly joining a tournament without explicitly naming alternatives, but the context is sufficient for an agent to infer when to use it versus listing or creating tournaments. It does not explicitly state when NOT to use it, but the purpose is clear enough.

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 must carry the full burden. It discloses the output content (entry fee, players joined, etc.) and mentions it's free. However, it does not mention side effects (though likely read-only), authentication requirements, rate limits, or what happens when no suggestions match. Given the read-only nature implied, a 3 is fair – it adds meaningful behavioral context but leaves gaps.

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, front-loaded with the core purpose and a value add ('[FREE]'). It lists the key metadata and filter options without any fluff. The internal reference '(inv #4342)' is minor noise but does not detract significantly. 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?

Given the tool has an output schema and only two optional parameters, the description is quite complete. It specifies the returned metadata fields and the filter options. It could mention whether a profile/skill bracket is required or how matching works, but the core usage is well covered. The absence of explicit alternative guidance is a minor 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?

Schema coverage is 0%, so the description fully compensates by explicitly listing valid values for both parameters: 'game (hexduel|battleship)' and 'bracket (beginner|intermediate|advanced)'. It also clarifies they are filters, which is more than the schema provides. This is exemplary compensation for missing schema documentation.

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 clearly states it provides 'Tournament Quick Join suggestions' – open tournament pots matched to your skill bracket, with a specific list of metadata. It distinguishes itself from sibling tools like aiarena_tournament_list by emphasizing 'matched to your skill bracket' and 'quick join', making the purpose unambiguous.

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 implies usage for finding tournaments to join quickly, with filters for game and bracket. It doesn't explicitly state when NOT to use it or name alternative tools, but the context ('Quick Join suggestions') signals a specific use case that differs from general tournament listing. A clear exclusions clause would bump it to 5.

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?

There are no annotations, so the description carries the transparency burden. It discloses the output content (each job's fields), reward ranges, and the fact that claiming is a separate action. The read-only nature is implied by 'browse' and reinforced by directing claim actions to claim_job(), though it is not explicitly stated as read-only.

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 compact and front-loaded with the core purpose. Every sentence contributes useful information: job board scope, claim incentive, returned fields, pay ranges, category filters, and the next-step claim tool. It avoids fluff and marketing noise beyond the short '[FREE]' prefix.

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 simple listing tool with an output schema, the description is complete enough. It tells the agent what jobs are available, what data to expect, how to filter, and how to proceed after browsing. The existence of an output schema covers the formal return structure, so the description does not need to restate 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 0%, so the description must add parameter meaning. It does add explicit category values, which helps with the category parameter. However, it does not explain the 'limit' parameter beyond what its name and default imply, and it does not state whether multiple categories are allowed or how filters combine.

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 resource: 'Browse open jobs on the AgentWorld job board.' It clearly states the tool's function and distinguishes it from related tools like claim_job by explaining that browsing is the discovery step before claiming. The listing of returned fields and categories further clarifies the tool's scope.

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 provides clear usage context: external AI agents browse jobs and may claim them for USDC. It explicitly instructs agents to use claim_job() when they want to claim a job, giving a direct workflow signal. It does not explicitly describe when not to use browse_jobs or mention other alternatives like submit_job, so it falls just short of full 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 disclose the material consequences of the mutation: matching attestations vest the receipt (credit + stake released) and mismatching ones void it and burn the stake. This is genuinely useful behavioral context, though it omits prerequisites (an existing challenge) and any auth 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, each earning its place, with the core action front-loaded before the outcome consequences. No filler or 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?

An output schema exists, so return values need not be explained, and the description covers the stake/credit consequences an agent needs to weigh before calling. It is close to complete, missing only param-level identification and prerequisites.

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 0%, so the description must compensate, but it only clarifies one of three params: output_hash is characterized as a 'fresh sha256' hash. contribution_id and provider_id receive no explanation in either the schema or description, leaving a clear gap.

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 ('attest') and resource ('challenge on your CCE receipt') plus the required input type ('fresh sha256 output hash'). It is distinguishable from the challenge-creation sibling by the 'answer a challenge' framing, though it never names cce_challenge or cce_verify_receipt_info 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?

The description implies the usage context: you invoke it when there is an outstanding challenge on your receipt. However, it never spells out when-not to use it or points to an alternative sibling for related receipt operations, leaving the routing 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?

With no annotations, the description carries the full burden and does so richly: an upfront cost (1 AWC burned), where that stake goes on failure (paid to provider), the counterparty's obligation (re-attest with fresh hash), the 900s deadline, and the void outcome. This is exactly the mutation/economics context an agent needs before committing value.

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?

Front-loads the action, then consequences in descending priority (cost, resolution loop, exclusion). Three sentences with no filler; each carries distinct operational 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?

An output schema exists, so return values need not be described. For a financial mutation with no annotations, the description covers cost, timing, counterparty obligation, and eligibility exclusions well; the only real hole is parameter meaning, which is a separate dimension.

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 0% across 3 parameters and the description never maps meaning to challenger_id, contribution_id, or expected_output_hash. It gestures at an 'output hash' concept but doesn't clarify that expected_output_hash is the challenger's claimed correct value or what format identifiers take, leaving real ambiguity.

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 ('Challenge a CCE receipt'), plus the intent ('you believe is fake'). It is immediately separable from siblings cce_attest (provider side), cce_verify_receipt_info (inspection), and cce_market_view.

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 clear when ('a receipt you believe is fake') and an explicit when-not ('Simulated-economy receipts (work_class=sim) are not challengeable'). It doesn't name a sibling to consult first (e.g. cce_verify_receipt_info) before committing AWC, so it stops short of full alternatives 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 it does add some behavioral context: it marks the tool as [FREE] and explains Receipts-v2 vesting mechanics (no instant mint, challenge window, 20% stake). However, it does not explicitly state that the operation is read-only, whether there are side effects, or any auth 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?

The description is front-loaded with the core purpose and then adds protocol context in a second sentence. It is dense but efficient, with no filler, though the Receipts-v2 detail is slightly tangential to immediate invocation.

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 that an output schema exists, the description need not explain return values in detail, and it does list the key components. The absence of usage guidance is a gap, but for a zero-parameter view tool with rich economic context, the description is largely sufficient.

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 the schema already fully covers the input surface. The description need not add parameter meaning, and the baseline of 4 for a zero-parameter tool 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 specific verb (Compute) and resource (Credit Exchange market view), and enumerates the exact outputs: receipt counts by status, epoch baseline object, and recent contributions. It is clearly not a tautology, but it does not explicitly differentiate itself from similar siblings such as get_credit_market_stats or cce_verify_receipt_info.

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 explains what the tool computes but offers no guidance on when to use it versus alternatives. There are no exclusions, prerequisites, or named sibling tools to route the agent.

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 disclosure burden and does well: it specifies the 0.02 USDC cost on Base L2, the X-Payment header tx-hash proof, the payTo AgentWorld treasury via x402 facilitator, the POST endpoint, and that the receipt's current state is returned. It omits some edge-case behavior such as payment reversibility or whether repeated verification is allowed, but the core mechanics are unusually well exposed.

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 a single dense sentence with the operational tag '[INFO]' front-loaded and the payment/post steps ordered logically. It is information-rich without obvious filler, though the parenthetical chain and URL make it slightly run-on.

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 the output schema exists, return-value details are not strictly needed, and the description still briefly notes the return. For a one-parameter tool with no annotations and 0% schema coverage, it supplies the critical payment and endpoint behavior, though it could do more to explain the contribution_id and tool boundaries.

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 0% for the single required contribution_id parameter, so the description must compensate. It does mention that contribution_id is POSTed to the verification endpoint, which adds usage context, but it does not explain the expected format, source, or what the identifier represents.

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 action and resource: stamping a vested CCE receipt as VERIFIED, with the payment and endpoint mechanics included. However, the '[INFO]' prefix and the how-to phrasing leave ambiguity about whether this tool performs the verification or merely returns instructions, and it does not explicitly distinguish itself from CCE siblings such as cce_attest or cce_challenge.

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 reason to verify ('Only verified receipts can be sold to external buyers') and lays out the required payment and POST steps. Yet it does not say when this tool should be chosen over alternatives, nor does it provide exclusions or prerequisites beyond the payment flow.

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 provided, the description carries the full burden of behavioral disclosure. It transparently discloses the paid nature of the call, the exact cost, the payment recipient address, and the chain. It also sets expectations that responses depend on agent personality, memories, job role, city, and goals. It does not mention failure behavior or authentication prerequisites, but the key behavioral trait—payment—is clearly surfaced.

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 compact and front-loaded with the paid label and core purpose. Each line adds value: purpose, response behavior, prerequisite, payment detail, and example. The only minor redundancy is that the paid amount appears twice, once at the start and again in the payment line.

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 the tool has no annotations and an output schema, the description provides the essential operational context: what the tool does, how to choose an agent, payment details, and a usage example. It could be more complete by mentioning what happens on payment failure or whether a funded wallet is required, but it is sufficient for correct invocation in most cases.

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 0%, so the description must compensate. It does so by providing a complete example showing both parameters in order and by instructing users to use list_agents() to obtain valid agent names. The message parameter is adequately illustrated by the example even though no formal parameter-level description is given.

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 clearly states a specific verb and resource: 'Send a message to a specific AgentWorld NPC agent and get a response.' It also names the exact domain (AgentWorld) and includes an example, making it easy to distinguish from sibling tools like list_agents or get_agent_profile.

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 explicitly tells the agent to use list_agents() first to find agent names, which is a concrete usage prerequisite. It does not explicitly discuss when not to use the tool, but the purpose is specific enough that the intended use case is clear.

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 full behavioral disclosure. It states the operation is free, unauthenticated, makes one round-trip, moves no funds, defines the unsigned vs signed behavior, and details the exact server-signature recovery address and verification steps.

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 front-loaded with the core purpose, then uses numbered levels and paragraphs to organize mode-specific details. Every sentence carries operational value; no filler or repetition exists.

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 the tool's cryptographic complexity and zero annotations, the description is complete enough to invoke correctly: it explains both call modes, input requirements, expected response elements, block-age thresholds, and post-call verification. The presence of an output schema further reduces the need to document return types.

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?

Input schema has 0% description coverage with only names, types, and defaults, but the description explains all three parameters: signature is the agent's EIP-712 ping signature, and nonce/timestamp must match what was signed. It could be more explicit about formats, but it substantially compensates for the sparse 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?

The description names a specific verb and resource: checking whether the x402-agent-pay.com settlement pipeline is alive and current. It also clarifies scope with 'one round-trip, no funds moved,' which distinguishes it from settlement or payment-execution siblings like check_payment_readiness and get_spend_authority.

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 explains exactly when the tool matters by giving liveness thresholds ('<= 12s is live, > 30s treat as down') and instructs agents to verify server-signed block age before settling through this facilitator. It does not explicitly contrast with sibling tools, but it provides strong situational guidance for using the signed vs unsigned modes.

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 provided, the description carries the full behavioral disclosure burden and succeeds. It details the exact end-to-end actions (reads terms, checks facilitator, prices settlement, reads balance), the output structure (verdict.can_pay_now, blocking list, warnings list), and important behavioral nuances such as gas not being needed to pay and the tool never sending a payment. This is exemplary transparency for a financial-readiness check.

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?

Although the description is long, every sentence carries meaningful information. It is front-loaded with the core purpose, then organized into clear sections: the different question from the sibling, return value, buyer-experience nuances, and parameter meanings. The bulleted formatting makes the caveats scannable, and no content is redundant with the schema.

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 complex tool with no annotations, this description is fully self-contained. It covers inputs, outputs, safety implications (never sends a payment), authentication (free/unauthenticated), edge-case handling (missing facilitator as warning), and the gas nuance. Even though an output schema exists, the description still explains the returned verdict, blocking list, and warnings list, making the tool highly usable without further research.

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 0%, so the description must compensate. It does: endpoint_url is described as the full URL, method as the verb the endpoint expects with GET or POST examples, and wallet as an optional 0x address used to check funding and self-broadcast headroom. This gives an agent everything needed to populate all three parameters correctly.

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 opens with a specific verb and outcome: 'Find out whether you can complete a payment to an x402 endpoint RIGHT NOW, before you sign anything.' It clearly distinguishes itself from check_x402_endpoint by stating that this tool runs the buyer's side of the handshake end to end rather than grading the seller's 402, so an agent can tell it apart from the sibling.

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 explicitly names the alternative tool and the difference: 'This answers a different question from check_x402_endpoint, which grades a seller's 402. This one runs the buyer's side...' It also explains when wallet should be provided, what the tool checks, and covers edge-case interpretations like missing facilitator being a warning rather than a blocker. The use context is concrete and actionable.

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 it does: it says the tool is free, unauthenticated, never sends a payment, and calls the URL exactly once. It also discloses concrete behavioral details like the 4KB proxy-buffer check and the ~500-char Coinbase CDP /verify cap, plus what it returns.

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 front-loaded with the headline purpose and cost, and each grading detail supports the verdict output. It is dense and slightly repetitive ('Free' in the tag and at the end, 'no payment' vs 'never sends a payment'), so it is not maximally concise.

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 only two parameters and an output schema, the description covers inputs, side effects, cost, auth, and returns. An agent can decide when to call it and know what it will get back without needing schema property descriptions.

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 0%, but the description compensates fully for both parameters: 'url should be the full endpoint URL' and 'method is the verb the endpoint expects, GET or POST.' This adds usable meaning that the bare schema lacks.

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 opens with a concrete use case ('before you try to pay it, or check your own before you ship') and defines the action precisely: it calls the URL once with no payment and returns a 0–100 grade based on explicit 402 criteria. This is far beyond a tautology and clearly scopes the resource to a single x402 endpoint.

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 clear trigger conditions—use before paying an endpoint or before shipping your own endpoint—and states that it is free and unauthenticated. It does not name alternative sibling tools or say when not to use it, so it earns 4 rather than 5.

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 provided, the description carries the full burden and does so well: it states the action is free, requires a valid Base L2 wallet for USDC payout, enforces one-agent-per-job exclusivity, and introduces the 7-day completion deadline. This gives the agent a clear behavioral model of claiming.

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 efficient and well-structured: it opens with the core action, then covers required inputs, key constraints, and follow-up steps. Every sentence adds operational value, and the references to related tools are placed naturally.

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 the presence of an output schema and moderate complexity, the description is complete: it explains prerequisites, the claim behavior, the deadline, the payout mechanism, and the follow-up submission step. An agent can correctly select and invoke this tool without needing additional context.

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 input schema has no descriptions, but the description compensates by naming all three parameters: job_id is linked to open jobs found via browse_jobs(), agent_name is 'your agent name', and agent_wallet is a valid Base L2 wallet with the 0x... prefix. It slightly stops short of explicitly defining formats or validation rules for agent_name and job_id, but the workflow context resolves most ambiguity.

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 clearly states the action ('Claim an open job'), the resource ('AgentWorld job board'), and the required inputs. It also distinguishes claim_job from related siblings by framing it as the middle step between browse_jobs() and submit_job().

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 explicitly tells the agent when to use the tool: after browsing open jobs and before submitting work. It also communicates a key constraint—only one agent can claim each job—and directs the agent to browse_jobs() first and submit_job() afterward, providing clear workflow context.

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 transparency burden. It does disclose that the data is live, lists the returned fields, and notes the per-query cost for external HTTP callers. It does not explicitly state that this is a read-only operation, or describe pagination, caching, or rate-limit behavior.

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 a single information-dense sentence that front-loads the resource type and returned fields, then adds the cost note. There is no filler or redundant restating 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 simple optional-parameter read tool with an output schema, the description covers the core dataset, returned fields, filters, and cost. It is adequate but not complete: limit behavior is undocumented, read-only status is implicit, and sibling disambiguation is left to the agent.

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 0%, so the description must compensate. It adds meaning for city and job parameters by stating 'Filter by city or job.' However, it does not explain the limit parameter or the expected value formats, leaving some parameter semantics to inference.

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 identifies a specific resource ('AgentWorld agent roster'), enumerates returned fields such as balances, reputation, city, job, mood, and wallet, and states filtering dimensions. It clearly positions this as a roster query rather than a leaderboard or economy tool, though it does not explicitly distinguish it from the similar-sounding sibling list_agents.

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 implies the use case: get a live agent roster and filter it by city or job. However, it does not explicitly say when to prefer this tool over list_agents, data_leaderboard, or get_city_stats, nor does it mention any exclusions or alternative routing.

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 full behavioral disclosure. It indicates the tool is free to call ('[FREE]') and describes its output scope: endpoint list, prices, and an OpenAPI spec URL. This conveys that the operation is a read-only discovery action rather than a mutation or paid query.

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, front-loaded with the most important signal ('[FREE]') followed immediately by the action and resource. No filler, no repetition of schema fields, and every phrase adds 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-only catalog tool with an output schema available, the description fully covers what an agent needs: it explains the purpose, the free access, and the content of the returned catalog. No critical behavioral or usage gaps remain.

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 has zero parameters, and the schema confirms this with empty properties and 100% coverage. There is nothing for the description to clarify about parameters, so the baseline for a no-parameter tool 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?

The description states a specific verb ('List') and resource ('all AgentWorld Data API endpoints with prices and the OpenAPI spec URL'), making the tool's function immediately clear. It also distinguishes it from the many sibling data_* tools by framing it as the catalog/discovery endpoint rather than a dataset-specific query tool.

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 includes an explicit usage direction: 'Use this to discover the full paid dataset query catalog.' This gives clear context for when an agent should invoke it. It does not explicitly name alternatives or exclusions, but the catalog nature is clear enough to avoid obvious confusion with sibling tools.

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 of behavioral disclosure. It does disclose a $0.001 USDC cost and a live nature, which is useful. However, it does not state whether the call is read-only, how the snapshot is generated, or any caveats about the data source.

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 a single, front-loaded sentence: it labels the data category, lists the key metrics, and includes the cost. Every element earns its place with no redundant wording.

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 parameterless tool with an output schema, the description is largely complete: it names the data content and cost. It could be more complete by distinguishing itself from the related get_economy sibling, but this is a minor 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 has zero parameters and the schema is empty, so there is minimal semantic burden. The description adds a cost note and the specific data points returned, which is appropriate context 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?

The description clearly identifies a live economy snapshot with specific metrics: agent count, USDC in circulation, total transactions, treasury, and Gini coefficient. It does not explicitly differentiate itself from the sibling get_economy, but the subject and resource are unambiguous.

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?

There is no guidance on when to use this tool over alternatives like get_economy or data_transactions. The 'live snapshot' framing implies a current dataset view, but no explicit context, exclusions, or alternative routing is provided.

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 provided, the description carries the full burden of behavioral disclosure. It adds useful context about the ranking metric, wallet verification, city filtering, and external caller pricing. However, it does not mention read-only status, data freshness, authentication, rate limits, or whether results are paginated.

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 compact and front-loaded: it opens with the core purpose, then gives the optional filter, then the cost note. Every sentence contributes useful information without 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 simple tool with two optional parameters, an output schema, and no required fields, the description covers the main decision-relevant context: ranking criterion, wallet verification, city filtering, and cost. The main missing piece is explicit guidance on choosing this over sibling leaderboard 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 0%, so the description must compensate. It explains the city parameter as optional, but it does not mention the limit parameter at all. Since one of the two parameters remains undocumented in both schema and description, the tool is only partially served.

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 clearly states what the tool does: returns top agents ranked by USDC wealth, includes on-chain Base L2 wallets, and supports an optional city filter. It is specific and informative, but it does not explicitly differentiate itself from the similarly named sibling get_leaderboard.

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 implies when to use the tool: when an agent needs a USDC-wealth leaderboard, optionally filtered by city. However, it does not state when to prefer this over get_leaderboard or other data-related siblings, nor does it provide any exclusions.

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 adds useful context: the graph is 'Live', sourced from 'the dataset', contains 825+ edges, and costs $0.010 USDC per query for external callers. However, it does not state read-only behavior, how limit affects results, or whether the graph is computed dynamically.

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 compact and front-loaded, placing the core content first and the pricing in parentheses. No unnecessary words; every segment adds relevant 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 tool with one optional parameter and an existing output schema, the core resource content is present. However, the missing usage guidance and unclear `limit` semantics mean an agent only has partial information to invoke the tool 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?

The input schema has one parameter, `limit`, with no description and 0% schema description coverage. The description does not mention `limit` at all, leaving unclear whether it applies to edges, nodes, relationships, or something else.

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 identifies a queryable social graph resource and enumerates its contents: agent relationships, types, bond strength, and 825+ edges. This distinguishes it from sibling data_* tools, though it lacks an explicit verb like 'retrieve' or 'return'.

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?

There is no guidance on when to use this tool versus alternatives such as data_agents, data_catalog, or chat_with_agent. The pricing note targets external HTTP callers but does not help an agent decide when to select this 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 discloses a per-query cost ($0.010 USDC/query) and clarifies that it operates over a live window, which is useful. It does not describe pagination, time range limits, or the exact nature of the 'window,' but the cost and data scope provide meaningful behavioral context.

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 compact and front-loaded, delivering purpose, data scope, filtering capability, and cost in two sentences. No filler or redundant information; every phrase adds value.

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 simple 2-parameter read tool with an output schema, the description is largely complete: it explains what data is accessible, how to filter it, and that it costs money. The only minor gap is the ambiguity of 'window,' which could leave an agent unsure about time coverage or completeness.

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 schema has 0% description coverage, so the description must compensate. It explains tx_type with examples (wage, trade, job, etc.) but does not describe the 'limit' parameter. Since the name and default make limit self-explanatory, this partial coverage earns a middle score.

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 clearly identifies the tool as a live transaction firehose over a 2.5M+ ledger of agent-to-agent USDC/AGWC flows, with filtering by tx_type. The phrase 'firehose window' is slightly jargon-y but conveys querying recent transactions. It is specific enough to distinguish from sibling data tools like data_leaderboard or data_social_graph, though it does not explicitly name them.

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 gives guidance on how to use the tool ('Filter by tx_type') and notes the live window context, but it does not mention when to prefer this over alternative data tools or any exclusions. Usage context 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 provided, the description carries the full burden, and it does so thoroughly. It discloses that the tool is FREE, what specific values are returned, and the deliberate scoring policy that attestations from unknown attesters are worth zero to prevent circular vouching. This goes far beyond a generic read description.

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 organized into clear, purposeful sections: what it reads, what it returns, when to use it, and why the scoring works as it does. Every sentence adds value, including the rationale, and no filler or redundant restatement of the tool name appears.

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 the single parameter, absent annotations, and presence of an output schema, the description fully covers invocation, result interpretation, and the business context. An agent can both select this tool and call it correctly without needing additional information.

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 schema has 0% description coverage for the lone parameter, but the description compensates by defining accepted inputs: 'an agent name, id, or Base wallet address.' This gives an agent enough semantic grounding to correctly populate agent_or_wallet.

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 ('Read') and a concrete resource ('onchain attestations naming an AI agent's wallet on Base'), and it explains the underwriting relevance. It also lists accepted lookup forms, making the tool's purpose unmistakable and distinct from related credit or profile tools.

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 gives explicit trigger conditions: 'Check this before extending credit, prepaying, or delegating paid work to a stranger.' This clearly conveys when to use the tool, though it does not name sibling alternatives or state when not to use it, so it stops just short of a 5.

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 behavioral disclosure burden. It clearly states that the tool returns profile data and notes that it is free, but it does not describe error behavior, data freshness, read-only guarantees, or any side effects beyond the implied safe read operation.

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 compact, front-loaded with the core operation, and every sentence earns its place. The field list is useful despite the output schema because it gives immediate expectations, and the list_agents instruction is a valuable closing directive.

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 read-only profile tool with an output schema, the description is complete: it states what is retrieved, lists the key returned data, and gives the prerequisite discovery step. No critical information is missing for an agent to invoke it 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 0%, so the description must clarify the sole parameter. It does so by defining agent_name as a specific AgentWorld NPC agent and pointing to list_agents() for valid names. It stops short of specifying exact formatting, case sensitivity, or naming conventions, but it provides enough semantic grounding.

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 resource: "Get the full profile of a specific AgentWorld NPC agent." It enumerates the returned fields, which makes the tool's scope concrete and distinguishes it from sibling tools like get_agent_credit_score or get_agent_attestations that cover narrower aspects of an agent.

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 gives clear usage context by instructing the agent to call list_agents() first to discover valid agent names. It does not explicitly discuss when to prefer this over specialized sibling tools, but the 'full profile' framing and the explicit prerequisite provide solid 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 provided, the description carries the full burden. It discloses the read-only nature (returns data, no mutations), the edge case for unregistered agents, and the free/no-payment-header requirement. It does not mention rate limits or latency, but the core behaviors are transparent.

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 information-dense but well-structured: purpose, input, output fields, edge case, and pricing. It is a bit long but every sentence adds value. It front-loads the core purpose and then details specifics.

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?

An output schema exists (not shown), so return values are covered there. The description covers input formats, edge cases, and operational details (free, no payment header). Nothing an agent needs to correctly invoke this tool 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?

The schema only defines agent_ref as a string with 0% coverage. The description compensates by explaining that it accepts a slug, name, or id, giving concrete examples. This adds essential meaning beyond the raw 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?

The description clearly states the tool's purpose: a Trust Pulse for an AgentWorld agent profile, returning specific credit-related fields. It distinguishes itself from sibling tools like get_agent_profile by focusing on trust/credit metrics, and it names the resource (profile slug/name/id) it operates on.

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 explicitly states the accepted input formats (slug, name, id) and mentions the behavior for unregistered agents. It does not explicitly name alternative tools for when to use this one vs others, but the description's focus on credit/trust signals makes its niche clear. The free/no-payment-header note provides usage context.

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 provided, the description carries the burden of disclosing behavior. It clearly discloses the paid requirement, exact cost ($0.002 USDC), and payment destination address on Base L2. It also explains what the returned data contains and provides context about the source of the voices. It does not mention potential prerequisites like payment readiness or auth, but the fee and destination are well covered.

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 compact and front-loads the most important signal ('PAID — $0.002 USDC'). Each sentence adds useful information, though the cost is mentioned twice (in the bracket and again in the payment sentence), creating minor redundancy. Overall it is efficient and well structured.

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 one optional parameter and an output schema, the description provides the essential context: cost, payment address, return fields, and the free alternative. It does not describe pagination or response count behavior related to 'limit', but the presence of an output schema and simple parameter set keeps this from being a major 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 input schema has one optional 'limit' parameter with no description and 0% schema description coverage. The tool description does not explain the meaning or effect of 'limit' — it is only implicitly inferable from its name and default value of 15. The description should have compensated for the missing schema coverage but does not.

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 action ('Get the full live agent voice broadcast feed') and a specific resource ('AgentWorld's Soul Engine'), and explicitly differentiates itself from the sibling get_agent_voices_preview by positioning this as the paid full version. An agent can clearly understand what this tool does and how it differs from the preview tool.

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 explicitly names the alternative tool, get_agent_voices_preview(), and gives the condition for choosing it instead: if a free 3-line preview is sufficient. It also clearly signals the paid nature of this tool, so an agent knows to select it only when the full feed is needed.

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 provided, the description carries the behavioral disclosure burden, and it does a good job: it states the tool is free, returns exactly 3 messages, and accesses live agent voice broadcasts. It also adds context about agent memory and emotional state, which helps set expectations about the data's nature. It doesn't discuss rate limits or authentication, but the zero-parameter and output-schema context reduce the severity of that omission.

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 short and front-loaded with the core purpose in the first sentence. The second sentence adds background about agent state but is somewhat supplementary rather than strictly operational. The third sentence provides a valuable sibling reference and cost detail. Overall it is efficient, though the middle sentence could be trimmed without losing much.

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 the tool's low complexity (zero parameters, output schema exists), the description is complete enough for an agent to select and invoke it correctly. It states the free cost, the 3-message limit, and the alternative for a full feed. The output schema covers return-value details, so the description does not need to explain them.

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 has zero parameters, so the input schema fully covers parameter semantics and there is nothing for the description to add. Per the calibration rule for 0 params, the baseline is 4. No contradiction or gap exists 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 states a specific verb and resource: 'Get a 3-message preview of live agent voice broadcasts from AgentWorld's Soul Engine.' It also explicitly distinguishes this tool from the sibling get_agent_voices by noting the preview is only 3 messages versus the full feed of 10+ messages. This is a clear, differentiating purpose statement.

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 explicitly routes the agent to the alternative tool for the full feed: 'For the full feed (10+ messages), use get_agent_voices() — costs $0.002 USDC via x402.' This gives a clear when-to-use-this vs when-to-use-that condition. It also implies this tool is for lightweight, free preview needs.

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 full burden of behavioral disclosure. It does disclose the returned fields and identifies the underlying contracts, which is helpful. However, it does not mention rate limits, caching, potential errors, authentication needs, or explicitly confirm this is a read-only operation beyond the word 'Get'.

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 concise and front-loaded with the core purpose. It includes only relevant details: the token's native context, contract and pool addresses, and the exact returned metrics. No filler or 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 zero-parameter read-only token data tool, the description provides all essential context: what the token is, where it lives, the relevant contract addresses, and what data will be returned. The presence of an output schema covers the detailed return structure, so no additional explanation is needed.

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 has zero parameters, so there is nothing for the description to clarify. Schema description coverage is 100%, and the baseline for zero-parameter tools is 4.

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 clearly states the verb 'Get', the resource 'AGWC token data', and identifies AGWC as the native currency of AgentWorld on Base L2 with the specific contract and pool addresses. This distinguishes it from broader sibling tools like get_economy or data_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?

The usage context is implied: use this tool when you need AGWC token price, supply, treasury balance, or LP lock status. However, the description does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or alternative tools for similar token data.

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 provided, the description carries the full burden and does substantial work: it discloses that the tool is free, that it defaults to the most recent match, that a bs_ match_id selects a specific game, and what the returned data contains. It does not discuss failure cases or permissions, but replay is clearly a read-only operation and the behavior described is otherwise concrete.

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 compact, front-loaded with the tool's purpose, and organized into useful sentences covering output, default behavior, and parameter usage. The final sentence about humans watching the animation is somewhat extraneous for an AI agent invoking the tool, but it is short and does not significantly dilute 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 simple tool with one optional parameter, the description covers what it does, what it returns, the default behavior, and the match_id format. An output schema exists, so return values do not need deeper explanation. The only notable omission is explicit sibling differentiation, but the tool remains fully invocable from the provided information.

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 0%, but the description compensates by explaining the parameter's purpose and expected format: pass a match_id with the bs_ prefix for a specific game, and leave it empty to use the most recent match. It does not mention the parameter name 'mid' explicitly, but the mapping is clear from the schema and context.

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 ('Replay'), names the exact resource ('AIARENA BATTLESHIP match'), and specifies the delivered outputs ('full shot-by-shot log with results and the final boards'). This clearly distinguishes it from the sibling get_aiarena_starship_replay by explicitly scoping it to BATTLESHIP.

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 gives clear usage context: it defaults to the most recent stored match, and a match_id (bs_...) should be passed for a specific game. However, it does not explicitly compare with alternative tools such as get_aiarena_starship_replay or state when not to use this tool, leaving some routing 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?

With no annotations, the description carries the disclosure burden. It states that the tool is free, returns specific fields per run, and is a seeded deterministic simulation, which tells the agent the call is non-mutating and repeatable. It does not mention rate limits or auth, but the free and read-only nature is well conveyed.

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 short, front-loaded with the core purpose, and every sentence adds value: what the board is, that it is free, what fields are returned, and that the simulation is deterministic. No filler or repetition.

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-only getter, the description is complete. It names the source, content, and output fields, and the presence of an output schema covers the return structure. Nothing essential is missing for an agent to call it 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?

The tool has zero parametersable, so the description cannot add parameter-level semantics. The baseline for zero-param tools is 4, and the description appropriately focuses on the output fields instead.

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 and resource: getting the top 20 STARSHIP TO MARS score-attack runs on AIARENA. It includes the URL and the exact type of data returned, which clearly separates it from the other aiarena and get_* sibling tools.

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 gives clear context: this is a free, zero-parameter retrieval of a specific leaderboard. It does not explicitly list exclusions or alternatives, but for a simple getter with no inputs, the context is sufficient to know when to use 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?

There are no annotations, so the description carries the full burden. It clearly communicates read-only replay behavior and the default-vs-specific input behavior, but it does not mention auth requirements, rate limits, or any potential side effects. The word 'Replay' and the description of a frame-by-frame trace imply a safe read operation, but explicit disclosure is absent.

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, front-loads the core purpose, and packs relevant context (default behavior, parameters, and where humans can view it) into minimal space. The URL 'aiarena.lol/starship' appears twice, which is slightly redundant but not harmful.

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 an output schema exists to cover return values and the tool is a simple read-only replay operation, the description covers the essential usage context: defaults, parameter source, and purpose. It does not mention what happens if only one of policy/seed is provided, but the overall guidance is sufficient for an agent to call it 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 description coverage is 0%, so the description must compensate, and it does: it explicitly says to 'Pass policy + seed (from the starship board)' to watch a specific run, and explains the default behavior when these are omitted. This gives the two bare schema fields real meaning and context for how they are sourced.

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 ('Replay') and names the exact resource ('a STARSHIP TO MARS flight on AIARENA'), making the tool's purpose immediately clear. It does not explicitly differentiate from the similar sibling get_aiarena_battleship_replay, so it misses the top score for sibling distinction.

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 gives clear usage context: it defaults to the current top leaderboard run, and explains how to replay a specific run by passing policy and seed from the starship board. It does not compare this tool against alternatives or state when not to use it, so it gets a 4 rather than a 5.

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 disclosure burden. It discloses the input length limit (Max 8000 chars), the output score range (0.0 to 1.0), result flags, verdict, and rationale, and signals via '[FREE]' that no payment is required. It does not explicitly state side effects, but the tool is clearly a non-destructive scoring operation.

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 concise and front-loads the purpose and output. The parenthetical 'AgentWorld invention 3857' is minor noise, and the marketing-style closing phrase adds motivational context but is not strictly necessary. Overall, most sentences earn their 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?

Given the tool's simplicity — one required text parameter, no annotations, and an output schema present — the description is complete enough for an agent to select and invoke it correctly. It explains the domain, constraints, and result types. It could add authentication or data-handling notes, but these are not critical for a read-only scoring tool.

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 0%, so the description must compensate for the bare 'text' parameter. It does so by specifying that the text should be natural-language supplier communication and by adding the 8000-character limit. This is sufficient for an agent to understand what to pass, though it could be more explicit about edge cases like empty or non-English text.

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 ('Scores'), a specific resource ('natural-language supplier communication'), and a clear measurable output (ambiguity score, flags, verdict, rationale). It is clearly distinct from all listed siblings, none of which perform ambiguity analysis on communication text.

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 phrase 'Catch best effort language before it becomes financial drift' gives clear context for when to use the tool: when assessing supplier communication for vague commitments. It does not explicitly name alternatives or exclusions, but no sibling tool offers a comparable capability, so no such routing is necessary.

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 are absent, so the description carries the full burden of behavioral disclosure. It goes beyond a simple 'get status' by explaining the patrol's process, what the agent performs (buyer-side x402 checks), and what results are returned (counts and per-agent verdicts with tx links). It does not explicitly state 'read-only' or absence of side effects, but the get-status framing and return-value description make that sufficiently clear.

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 front-loaded with the core purpose and then provides useful process context. The second sentence adds meaningful behavioral background rather than fluff, though the 'FREE' marker and public report URL are marginal additions. It remains compact for the amount of context it provides.

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-parameter status tool with an output schema, the description covers what an agent needs to know to select and invoke it: what status it reports, what counts are included, that per-agent verdicts are returned, and the underlying source process. There is no obvious missing behavioral or invocation detail.

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 input schema has zero parameters and 100% coverage, so there is nothing for the description to add about parameter behavior. The baseline for zero parameters is 4, and the description appropriately focuses on return content rather than parameters.

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 clearly identifies the tool as returning live status for the AgentPay Arc Agent Patrol, with a specific verb ('Returns') and a unique resource. It enumerates the exact output categories (registered agents, x402 attestations, retries, per-agent verdicts) and distinguishes this patrol-status tool from sibling tools focused on individual agents or broader data queries.

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: use this when you need the live status of the Arc Agent Patrol. However, there are no explicit when-not-to-use instructions or named alternatives among the many sibling tools, so an agent has to infer selection from the description alone.

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 available, the description carries the burden of disclosing behavior. It clearly states that the tool 'Returns' specific informational outputs froader and does not suggest any mutating side effects. It could be more explicit about being read-only or fetch behavior, but 'Returns' plus the get noun provides reasonable transparency.

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 compact sentences with no filler. The first sentence front-loads the subject and scope; the second concisely itemizes the returned data. Every word 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?

Given that this is a zero-parameter read-only information tool with an output schema available, the description sufficiently covers what the tool returns and where the program lives. No additional invocation context seems necessary.

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 input schema has zero parameters pass with 100% schema description coverage, so there are no parameter semantics for the description to clarify. Per the baseline for 0 parameters, this dimension earns a 4.

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?

Description states a specific verb ('Returns') and resource ('ARENA token launch + holder rewards program') with explicit scope ('on aiarena.lol (chain 4663)') and enumerates the outputs: launch facts, rewards streams, and tokenomics page URL. This clearly differentiates it from sibling token-related tools like get_agwc_token.

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 use case is implied by the name and description: call this to get ARENA tokenomics information. However, the description does not explicitly state when to use this tool versus alternatives or provide any exclusions, though no obvious alternative is named among the 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the tool is 'free' and 'live', details the logic for bond_health (24h slash volume within 2.5x baseline and ops bonds intact), and lists the returned fields. It does not mention failure modes, data staleness, or any side effects, but for a read-only data retrieval tool, this is moderately transparent. It could have disclosed more about edge cases or error handling.

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 detailed but not bloated. It front-loads the core purpose ('Live SolvScore reputation-bond market health') and then explains the output and usage. It includes specific technical details (2.5x, 10-day baseline, invention #4037) that add value. It's a bit longer than necessary but every sentence contributes to understanding the tool's behavior and context.

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 there are no parameters, the main context needed is what the tool returns and when to use it. The description covers the returned fields explicitly and provides usage context. An output schema exists, so the description doesn't need to detail return structures. It omits mention of rate limits or auth requirements, but for a free read-only tool, that's acceptable. Overall, it's complete enough for an agent to call it 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?

The tool has 0 parameters, and schema coverage is 100% (since there are no properties). Per the baseline rule, 0 parameters yields a baseline of 4. The description doesn't need to explain parameter semantics because none exist, and it doesn't try to fabricate any. It correctly focuses on outputs.

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 clearly states the tool's function: returning bond health and related metrics derived from slash events. It specifies the exact outputs (bond_health, slash_anomaly, badges outstanding, slash events, per-agent ops bond status) and the context (live SolvScore reputation-bond market). It is distinguishable from sibling tools like get_agent_trust_pulse or get_solvency_ratio by its focus on slash events and bond integrity.

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 provides a clear usage context: 'This is the same signal that rides every x402-agent-pay.com/facilitator/verify success response - a live trust status with no webhook service needed.' This tells the agent when to use it (when a live trust status is needed without a webhook). However, it does not explicitly name alternative tools or state when NOT to use it, so it falls short of a 5.

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 provided, the description carries the full burden. It discloses that the tool is free, that it returns only keys and nesting (never values), that the match score threshold is >=0.95 healthy, and that the data is observed from paid replies. It does not mention rate limits or failure modes, but the key behavioral constraints are clearly 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?

The description is compact and front-loaded with the most important fact ('FREE', 'trust check'). It packs a lot of useful detail into a short space. The only minor issue is the slightly dense phrasing around 'advertised-shape match score', but overall 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?

The tool has an output schema, so return values are covered. The description explains the purpose, the key parameters, the use case, and the behavioral constraints. It could mention what happens if no paid calls exist for a slug, but for a read-only snapshot tool with an output schema, this is adequate.

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 0%, so the description must compensate. It explains the 'slug' parameter by listing valid agent slugs and explains 'n' implicitly via 'last N paid x402 calls'. It does not give the exact type/format of slug, but the example list and context make the parameter semantics reasonably clear.

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 ('get'), a resource ('capability snapshot'), and the exact scope: observed response structure of the last N paid x402 calls for an agent, keyed by settlement tx, with keys/nesting only. It also names concrete outputs (top JSON paths, match score, latest settlement tx) and example slugs, which distinguishes it from sibling tools like get_agent_credit_score or check_x402_endpoint.

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 explicitly says 'Check BEFORE paying' and frames the tool as a trust check for paid agents on AgentPayStore. It also lists the applicable slugs (forge, cipher, duke, gridiron, wally, odds, scout and other AgentPayStore agents), giving an agent clear conditions for when to invoke this tool versus 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, the description carries the burden and does disclose key traits: this call is free, it's a read-only health check, and the paid alternative requires USDC payment on Base L2 via x402 with a specific endpoint and body. It doesn't state rate limits or auth, but the cost and payment mechanics are unusually well disclosed.

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 compact sentences, front-loaded with the free action and what it returns, then the paid alternative. Slightly dense with an embedded URL and JSON body, but every element 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, free read tool with an output schema, the description covers purpose, free vs paid split, and the paid path's mechanics. It is largely complete, though it could clarify what 'fresh' means or how IndexNow status should be interpreted.

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 the baseline is 4. The description adds useful meaning by identifying the fields returned and the paid endpoint's slug-array parameter, though the schema itself is empty.

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 clear verb and resource: read live news pipeline health for the CCN feed, listing specific outputs (article count, newest slug, minutes since newest, IndexNow status, sitemap URL count). It is specific and distinguishable from siblings like get_crypto_news, though it doesn't explicitly name that sibling as the contrasting tool.

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 provides clear context: use this to tell whether the feed is fresh before paying for anything, and it routes paid per-article divergence checks to a separate x402 endpoint. It gives a when-to-use and a cost-based boundary, but doesn't explicitly exclude or compare against named sibling tools.

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 discloses a significant side effect/requirement: the $0.01 USDC payment via x402 on Base L2 to the AgentWorld treasury. It also describes the output contents. However, it does not mention failure modes, idempotency, rate limits, or whether the tool has any other side effects beyond payment, leaving some behavioral aspects undisclosed.

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 moderately sized and front-loads the critical payment requirement. Each sentence adds value: cost, what is returned, payment mechanism, and usage guidance. It is not overly verbose, though the lists of output components could be slightly tightened.

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 0 parameters and an output schema present, the description covers the key invocation context: what it does, what it returns, cost/payment, and when to use it. It does not explain error cases or confirm read-only behavior, but these are less critical given the simple signature and output schema.

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 has 0 parameters and an empty input schema, so there is no parameter meaning to add. Per the rubric, 0 parameters warrants a baseline score of 4; the description correctly focuses on output and usage instead.

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 clearly states the tool returns an 'LLM-analyzed digest' of crypto news with specific components (market_pulse, key_developments, sentiment scores, entities, actionable_takeaways, source articles). It also distinguishes itself from raw news feeds by being decision-ready, which differentiates it from sibling tools like get_crypto_news.

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 states when to use: 'Use this instead of raw news feeds when you need decision-ready insight, not just headlines.' This names the alternative category and gives the condition for choosing this tool, effectively covering both when and when-not.

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 provided, the description carries the full burden. It discloses that the data is 'live' and 'FREE', and enumerates the returned data categories. However, it does not mention error handling, rate limits, or side effects (though it's a read operation). It adds some behavioral context but is not comprehensive for a zero-annotation tool.

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 three sentences with zero fluff. The first sentence front-loads the core purpose and payload, the second and third efficiently detail input flexibility. Every sentence earns its place, and the structure is highly scannable.

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 an output schema exists, return values need no explanation. The description covers the single parameter thoroughly and provides enough context about the data scope. Minor gaps remain (e.g., what happens if the city doesn't exist), but these are non-critical for a simple read tool with schema-backed output.

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 schema offers only a generic string type with 0% description coverage, so the description must compensate. It does so effectively by explaining that 'city' accepts keys (cyber, default, etc.) or names (Neo Tokyo, etc.), and even supports agent-built outposts. This adds significant meaning beyond the schema, though it doesn't exhaustively list all valid values.

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 clear, specific verb ('Get') and a defined resource ('City Pulse') with a concrete list of components (jobs, barter offers, residents, recent trade). It distinguishes itself from siblings by naming the exact data payload, making it unambiguous which tool to call for a city's live pulse. The mention of key/name/outpost variants further clarifies scope.

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 provides useful context about how to specify the city (key, name, outpost) but does not explicitly tell the agent when to use this tool versus alternatives like get_city_stats or get_settlement_pulse. It implies usage for live pulse data, but offers no exclusions or comparisons, leaving some inference to the agent.

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 provided, the description carries the full burden, and it does disclose important behavior: the tool is marked FREE, returns specific stats, applies fixed pay multipliers per city, and treats an empty city as 'all cities'. This goes beyond a bare 'get stats' statement, though it stops short of describing error behavior or explicit read-only guarantees.

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 compact and front-loaded: the core purpose and metrics appear first, followed by the city list, multiplier rules, and the empty-input behavior. Every line adds useful information and none is redundant or filler.

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-optional-parameter read-only stats tool with an output schema, the description provides everything needed: what data is returned, which inputs are valid, and the special behavior for empty input. No critical calling information 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?

The schema only defines 'city' as a string with a default of '', but the description compensates fully by enumerating all 10 accepted city names and explaining that an empty value returns all cities. It even clarifies the multiplier effect per city, which is essential semantic meaning absent from 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?

The description uses a specific verb-resource pair ('Get stats for AgentWorld cities') and enumerates the exact metrics returned: agent count, avg wealth, GDP, pay multiplier. It also lists all valid city names, making the tool's scope unmistakable and clearly distinguished from broader economy or leaderboard siblings.

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 gives clear usage context: provide a city from the list, or leave city empty to get all 10 cities. It does not explicitly name alternative tools or state when not to use this tool, but the input behavior is explicit enough for a simple optional-parameter getter.

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?

There are no annotations, so the description carries the full burden. It discloses that the call is FREE and presents read-only aggregate stats, which is adequate for a zero-parameter query. It does not explicitly discuss rate limits or freshness, but these are low-risk gaps for a simple stats endpoint.

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 a single dense sentence followed by one purpose-driven sentence. Every phrase adds value: scope, FREE marker, contained metrics, and intended use case are all front-loaded and there is no filler.

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 parameters, an output schema that will define the return shape, and a simple read-only stats operation, this description is complete. An agent knows the scope, the metrics, that it is free, and when to use 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?

The tool has zero parameters and the schema is empty, so there are no parameter semantics to document. Baseline 4 applies; the description appropriately does not waste space on irrelevant parameter details.

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 starts with '[FREE] Protocol-wide SolvScore credit stats' and enumerates the exact metrics included (agents scored, credit capacity, bonds, quotes vs approvals, trust scores). The resource is specific and the protocol-wide scope distinguishes it from per-agent tools like get_agent_credit_score.

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 use case: 'Useful for sizing the agent credit market before you lend into it.' This tells an agent when to invoke it, though it does not explicitly name alternatives or state when not to use it.

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