Moltbound Sandbox

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 usefully discloses the sandbox-only constraint and the need for fictitious data, but it does not explain what approval actually does, whether a notification is sent, what permissions are required, or what happens after the request.

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-loads the main action and precondition. The phrase 'After the human linked you and you quoted' is slightly awkward but does not waste space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a multi-step approval tool with no annotations, incomplete parameter documentation, and no output schema, the description is too thin. It omits the semantics of approval, the roles of job_id and bid_id, and what the agent should expect after 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?

Only session_token has a schema description; job_id and bid_id are undocumented, yielding 33% coverage. The description mentions 'one quote' but adds no explicit meaning for bid_id, job_id, or how the session token relates to the flow beyond the vague precondition.

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: asking the human to approve one quote, with the precondition that the human has linked and a quote exists. It is clear what the tool does, but it does not differentiate the tool from related siblings such as moltbound_human_sim_approve or moltbound_consent_link.

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 a clear usage context: use this after the human has linked the agent and after a quote has been produced. It does not state when not to use it or name alternative approval-related tools, so there is room for ambiguity in multi-tool workflows.

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: idempotency behavior (returns the existing purchase_id), binding to a specific quote and agent, a 15-minute expiry, and two named failure modes. The SANDBOX warning about fictitious data is a behavioral constraint an agent cannot infer elsewhere.

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 that front-load the precondition and the time limit, then pack idempotency and error semantics without padding. The SANDBOX warning is short and clearly demarcated.

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 mutation with no annotations and no output schema, the description covers timing, idempotency, failure modes, and return value (purchase_id) well. The remaining gap is the undocumented origin of consent_request_id, which an agent would still need to trace through sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%: session_token has a schema description pointing at moltbound_start_session and moltbound_human_sim_verify, but consent_request_id is bare in both schema and description. The description adds conceptual context about what the approval is bound to (quote, agent) but never explains where consent_request_id comes from or how it maps to the approving flow.

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 ('complete the fictional purchase') plus the exact precondition (human approval) and the 15-minute window. It establishes that this is the terminal step after approval, which cleanly separates it from siblings like moltbound_approval_request or moltbound_human_sim_approve.

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 names the trigger ('after the human approved on Moltbound's website (or via moltbound_human_sim_approve)') and the alternative approval path. It also indirectly states when not to call, since misuse paths are enumerated with the exact error strings consent_used and consent_expired.

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

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

With no annotations, the description carries the full burden. It usefully discloses that a code is handed to the human and that the approval is passkey-based and fictional-only, but says nothing about code lifetime, what state changes on approval, what to do afterward (poll_grant?), or required permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with the core action front-loaded and no filler. The sandbox warning is short and relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no annotations, and the description omits the result shape (presumably a code/URL) and the downstream step for checking approval. For a 4-parameter linking tool in a multi-step flow, that leaves the agent guessing about next actions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 25% — only session_token is documented. The description mentions no semantics for max_price, service_id, or jurisdiction, so three of four parameters remain unexplained in both schema and 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 states a specific action (issue a linking code) and its purpose (human passkey approval of a purchase), which is clear enough to distinguish from a plain quote or status tool. It does not explicitly contrast with close siblings like moltbound_approval_request or moltbound_request_grant, leaving overlap ambiguity.

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 call this versus moltbound_approval_request, moltbound_request_grant, or moltbound_human_sim_approve, nor any prerequisites beyond the implicit session_token. The sandbox note is a safety constraint, not usage 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 the burden and does add genuinely useful disclosure: the operation is simulated sandbox work, and results come back sorted cheapest first. It is silent on state effects (does requesting a quote create a persisted record?), cost, idempotency, and — critically — whether results arrive immediately or must be fetched via moltbound_quote_status, which its sibling list implies is a real concern.

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-loaded with the purpose and ordering behavior, then sandbox constraint last — good ordering with no filler. The closing "Do not enter real personal details" largely repeats the preceding SANDBOX clause, costing one redundant sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an unannotated, output-schema-less tool with nested parameters, the description should say what a successful call yields and whether follow-up polling is required. It covers the sandbox and ordering angles but stops short of the quote lifecycle, which is the piece an agent most needs in order to chain the next call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline 3 applies. "Pass parameters directly for any of the 20 services" usefully signals that service fields may be sent as top-level keys, but the schema's risk_profile description already says exactly that, so the description mostly restates structured data rather than extending it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource combination ("Request simulated quotes") and adds two distinguishing properties: results are ordered cheapest first, and coverage spans 20 named services. It never mentions the close sibling moltbound_quick_quote or moltbound_quote_status, so the agent must open schemas to tell this apart from those.

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 real usage constraint (SANDBOX, fictitious data only) that governs how to call it, and tells the agent to pass per-service fields directly. But it offers no when-to-use/when-not guidance against siblings like quick_quote or quote_status, leaving the main routing decision 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. 'Inspect' weakly implies a read, but it says nothing about whether a grant_token is required for access, whether status is fresh or cached, whether it mutates anything, or what happens on an invalid/expired grant.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with the action front-loaded and the safety caveat second. Slightly wasteful in that the sandbox warning is generic, but nothing is padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description only loosely hints at the returned fields ('status and approved'). For a two-parameter, unannotated lookup sitting among several similar grant/poll tools, the agent is missing return shape, auth expectations, and sibling differentiation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50% — grant_id is undocumented in the schema and the description adds nothing about it, nor about the optional grant_token. The description must compensate for that gap and instead addresses neither 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?

States a specific verb and resource: inspect the status and approved fields of an active data grant. An agent knows what it retrieves, but nothing distinguishes it from the sibling moltbound_poll_grant, which presumably reads similar state.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no prerequisites, and no mention of the obvious alternative (moltbound_poll_grant) or of moltbound_request_grant/revoke_grant as adjacent steps. The only conditional text is a sandbox data warning, which is a constraint rather than usage direction.

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 meaningful traits: no billing occurs, the target is a sandbox, and fictitious data only is permitted. It omits mutation semantics — whether the approval is idempotent, whether it consumes or invalidates the consent request, and what happens on token/code failure.

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 action and its target come first, with constraints in short trailing clauses; every sentence carries actionable information. Minor redundancy in repeating the sandbox idea ('sandbox consent_request_id' then 'SANDBOX: use fictitious data only') keeps it from a 5.

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 mutation tool with no annotations and no output schema, the safety profile and auth paths are covered. Still missing are the return/failure behavior and the lifecycle effect of approving a consent request, leaving an agent unsure of what to expect after the call.

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%, yet the description compensates well by explaining the two authentication paths and their mutual exclusivity: 'human_sim_token (or email + code)', plus identifying consent_request_id as the object being approved. It still lacks format details such as where the token or code originates, so not a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Approve'), a specific resource ('sandbox consent_request_id'), and a specific mode ('email-only simulated human mode'), so an agent can tell it apart from moltbound_human_sim_start and moltbound_human_sim_verify by the approve action. It never names those siblings explicitly, so differentiation is inferential rather than explicit.

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?

'email-only simulated human mode' implies this is the approval step of the simulated-human flow, and 'Never billable' sets expectations for when it is safe to call. However, it never states prerequisites such as needing a consent_request_id from moltbound_approval_request or moltbound_consent_link, nor does it say when NOT to use this variant.

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 the outward side effect (an email with a 6-digit code is sent) and the sandbox restriction, but says nothing about code expiry, rate limits, failure behavior for invalid emails, or whether a session token is created. That is partial disclosure for a stateful initiation 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?

Two sentences, front-loaded with the mode name and the core action, closing with the safety constraint. Slightly dense with stacked parentheticals, but no wasted text.

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?

A 6-parameter, 0%-coverage, no-annotation, no-output-schema tool needs considerably more explanation than this. The description omits the verification hand-off (presumably moltbound_human_sim_verify), what happens to the optional session_token and capability/service scoping, and what a successful call yields.

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% across 6 parameters, so the description must compensate and it does not. Only 'email' is implicitly explained; agent_name, capability (quote_only vs quote_and_bind), service_id (default '*'), jurisdiction, and session_token are never mentioned, leaving defaults and enum semantics entirely opaque.

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 concrete verb and resource: sends a 6-digit verification code to an email address to initiate simulated-human mode. It conveys the mechanism (email-only, no browser passkey), but it does not distinguish itself from siblings like moltbound_start_session or name moltbound_human_sim_verify as the follow-on 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 sandbox-only constraint ('use fictitious data only') is a genuine usage condition, but it's about data safety rather than tool selection. There is no guidance on when to pick this versus moltbound_start_session or how it relates to moltbound_human_sim_verify / moltbound_human_sim_approve.

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 does useful work by naming the returned tokens and the default mandate scope ('*' = all 20 services), plus the sandbox safety constraint. It omits side effects, token expiry/lifetime, error/retry behavior, and whether verification is idempotent, which matters for a verification step an agent may retry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the action and the returns, then the sandbox warning. No filler, though the return-value sentence is slightly dense.

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 7-parameter verification tool with no annotations and no output schema, the description should explain capability/jurisdiction/session_token semantics. It compensates only for return values and the sandbox constraint, leaving most invocation-critical parameters undocumented.

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 7 parameters, and the description only touches 'code' and 'email'. agent_name, capability, service_id, jurisdiction, and session_token are entirely unexplained — notably the quote_only vs quote_and_bind enum, which materially changes what the agent is authorized to do.

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: verify the 6-digit email code issued by moltbound_human_sim_start. It explicitly names the sibling that precedes it and outlines what comes back (session_token, mandate_id, human_sim_token). It doesn't distinguish itself from moltbound_human_sim_approve, but the pairing with the start tool is clear.

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 the sequence by referencing moltbound_human_sim_start as the source of the code, and adds a sandbox usage constraint (fictitious data only). It never states when to use this versus the other human_sim/approval siblings or what to do on failure.

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 add real context: it enumerates what each service entry contains (partner counts, descriptions, required fields) and imposes a sandbox rule ('use fictitious data only. Do not enter real personal details'). It never explicitly states read-only behavior or failure modes, but 'List' plus the data constraint covers the key risks for a zero-param 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?

Two short sentences, front-loaded with the scope and counts before the use-case question and the sandbox caveat. Every clause carries information; nothing is repeated from the schema or restates 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 zero-param, no-annotation, no-output-schema discovery tool, the description supplies returned-field expectations, result size, and the sandbox constraint, which is close to complete. Only the routing signal versus the quote-fetching siblings 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 tool takes no parameters, so baseline 4 applies; there is nothing for the description to disambiguate. The description instead documents the shape of what comes back, which partially substitutes for the absent output schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List all 20 services across 9 categories') and quantifies the result set, which is more informative than a generic 'list services'. It doesn't explicitly contrast itself with siblings such as moltbound_get_quotes or moltbound_quick_quote, so the agent must infer the discovery-vs-fetch 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 quoted trigger 'What sort of quotes can you provide?' gives a concrete entry scenario for using this tool. However, no when-not-to-use condition or named alternative is provided, so the boundary against the quote-oriented siblings stays implicit.

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

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

With no annotations, the description carries the full burden. 'Poll' hints at repeated calls but gives no interval, timeout, or terminal-state behavior, and no return shape (pending/approved/denied). The sandbox warning about fictitious data is useful context but does not cover the tool's operational 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?

Two tight sentences with the core action front-loaded and no filler. The sandbox note is separate and clearly demarcated, though it sits oddly in a description without more operational 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?

No output schema and no annotations, so the description should explain what polling yields and how to interpret pending versus resolved states, plus the source of link_id/poll_secret. These are missing, leaving an agent under-informed for a two-param workflow step.

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 explain both required params. It names link_id and poll_secret but adds no meaning: where they originate, their format, or how poll_secret is obtained. Naming alone adds nothing beyond the schema's property names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: 'Poll for human approval of a data grant.' An agent understands the operation. However, it does not differentiate from close siblings like moltbound_grant_status or moltbound_approval_request, leaving ambiguity about why one polls versus checks status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to choose this over moltbound_grant_status, moltbound_approval_request, or moltbound_consent_link. The only usage-like statement is that it takes link_id and poll_secret, with no preconditions, ordering, or exclusions stated.

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

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

No annotations are present, so the description carries the full burden. It does disclose the polling contract, the terminal state, the return field, and the sandbox restriction on data — useful context. It omits what happens on an invalid/expired purchase_id, whether polling is rate-limited, and what a non-terminal response looks like.

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 with the operation, exit condition, and return value front-loaded; the SANDBOX warning is short and earns its place. Minimal waste, though it could be denser by folding the return value into the first sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description must do more, and it does state the key return field and the polling termination rule. It leaves error/empty-state behavior and the origin of purchase_id unaddressed, which matters for a two-required-parameter polling 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 only 50%: session_token is documented in the schema, but purchase_id has no description anywhere. The prose merely restates 'by purchase_id' and does not say its format, where it comes from (e.g., quick_quote / get_quotes), or what to do if it is unknown, so the description fails to compensate for the 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?

Names a specific verb+resource (poll the status of a purchase, keyed by purchase_id) and states the terminal condition ('bound') plus the payload returned (policy_number). That is enough to separate it from moltbound_quote_status / moltbound_grant_status / moltbound_poll_grant, though it never explicitly says so.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Poll ... until bound' implies the repeated-call pattern and its exit condition, which is genuine usage guidance. But there is no explicit statement of when to prefer it over the several sibling status tools, nor any prerequisite about how a purchase_id is obtained.

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 reasonably well: it discloses the sandbox-only constraint, the auto-default fill behavior including the asymmetric rejection rule for car insurance driver fields, and the Protected Mode prerequisite. It omits what the call produces (a quote? a quote id?) and whether it has side effects or is repeatable, which for a quote-initiation tool would be valuable.

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 in the first sentence, followed by conditional parameter notes and a compact safety warning. Slight redundancy with the schema's own sandbox note, but every clause carries 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 six-parameter tool with nested free-form risk_profile and no output schema, the description never explains what comes back or how the result connects to moltbound_quote_status, moltbound_get_quotes, or the purchase flow. Input semantics are covered; the post-call picture is not.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents every parameter, including the enum and the risk_profile escape hatch. The description restates the auto_default and grant_token semantics found in the schema rather than adding new interpretation, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('One-shot quotes across any service') and enumerates the three accepted input modes (prompt, partial fields, full risk profile). It does not explicitly distinguish itself from siblings like moltbound_get_quotes or moltbound_quote_status, so an agent must infer that this tool initiates a quote rather than retrieves one.

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 conditional guidance for two parameters ('When auto_default is true...', 'Pass grant_token for Protected Mode') and points to moltbound_requirements for field shapes. However, it never states when to choose this tool over moltbound_get_quotes or moltbound_quote_status, so routing among siblings is left 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 must carry the full behavioral burden. It discloses that the tool polls until complete and shows quotes to the human, plus a sandbox warning, but omits critical details like timeout behavior, whether it blocks or returns intermediate status, error handling, and authentication requirements beyond the session token.

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 efficiently lists optional parameters. It is slightly dense but well-structured, with every sentence contributing useful information, including the important sandbox warning.

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 complexity (8 parameters, no output schema, no annotations), the description covers purpose, filtering, and a sandbox warning, but lacks operational details: how job_id is obtained, what 'show the human' entails (e.g., return format), and what happens if the job never completes. It is adequate but leaves clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 13%, but the description compensates by listing enum values for sort and cover, and naming the optional filters (partner, max_deductible, max_price, limit). It does not explain job_id or session_token fully, but the added semantics for most parameters are substantial.

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 core action: poll a quote job until complete and show quotes to the human. It distinguishes itself from job-creation tools by emphasizing polling and human selection, but does not explicitly name alternatives like moltbound_get_quotes or moltbound_quick_quote.

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 after starting a quote job, with job_id and session_token. However, there is no explicit guidance on when to use this versus moltbound_get_quotes or moltbound_quick_quote, nor are there any when-not-to-use 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 burden, and it does disclose two important behaviors: the return (8-character user_code + verification URL) and that approval is a human passkey step, which implies the call is non-terminal. It omits whether the request expires, what happens when approval is denied, and that it creates a pending grant that must be polled — significant gaps for a mutation tool with zero annotation coverage.

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-loaded with the action and the immediate return value, then the sandbox caveat. The sandbox warning takes two short sentences for one point, minor redundancy, but nothing is padding at the sentence level.

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 six-parameter mutation with no annotations, no output schema, and 17% schema coverage, the description should explain the remaining parameters and the next step in the approval flow. It leaves the caller without enough to fill in or follow up on the request.

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 only 17% — just the 'service' parameter is documented, with examples like car_insurance. The description adds nothing about fields, purpose, reusable, jurisdiction, or expires_in_days, leaving five of six parameters unspecified in both structured fields and prose.

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 ('Request a scoped data grant for an agent'), which is materially different from the revoke/status/poll siblings. It does not explicitly name which sibling to use instead, so an agent must infer the relationship to moltbound_approval_request and moltbound_consent_link.

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 a real usage constraint ('SANDBOX: use fictitious data only') but no tool-selection guidance: it never says when to choose this over moltbound_approval_request or that moltbound_poll_grant / moltbound_grant_status are the follow-up steps. Usage context is implied by the mention of human passkey approval, not stated.

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

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses a sandbox constraint and warns against real personal data, but it does not clarify whether the operation is read-only, what authentication means beyond the schema, or what the result looks like.

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 brief and front-loads the purpose, followed by an important sandbox warning and usage note. It is efficiently sized, though the first sentence is slightly vague.

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 low-complexity tool with full schema coverage and no output schema, the description is adequate but incomplete. It covers the sandbox constraint and service_id usage, but leaves return behavior and session_token context to the 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?

Schema description coverage is 100%, so both parameters are already documented. The description adds the detail that service_id can inspect any of the 20 services, but does not add meaningfully more semantics 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 implies this tool returns the fields needed to request a service, but it never states the action clearly with a precise verb and resource. It mentions service_id can inspect any of the 20 services, which helps, but does not distinguish the tool from siblings like moltbound_list_services.

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 guidance is limited to passing service_id to inspect services. There is no explicit when-to-use guidance, no exclusions, and no comparison against related tools such as moltbound_list_services or moltbound_get_quotes.

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. 'Revoke' implies a mutation, but it doesn't say whether revocation is reversible, whether the grant_token is consumed or invalidated, what permissions are required, or what happens to in-flight polls. The sandbox note adds environment context but no behavioral detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with the action front-loaded and the sandbox caveat secondary. No wasted wording, though the sandbox line is generic boilerplate that doesn't advance understanding of this specific tool.

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?

A mutation tool with no annotations, no output schema, and half its parameters undocumented needs to explain reversibility, authorization, and expected result. The description supplies none of that, leaving an agent unable to predict the consequences of calling 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 50%: grant_token is documented in the schema, but grant_id is completely undocumented in both places. The description says nothing about parameter format, sourcing, or the role of the token in authorization, so it fails to compensate for 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?

States a specific verb and resource: 'Revoke an active data grant on behalf of the user'. This clearly separates it from moltbound_request_grant and moltbound_grant_status, though it doesn't name any sibling 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?

No guidance on when to revoke versus when to use moltbound_grant_status, moltbound_poll_grant, or moltbound_request_grant to inspect or create grants. The only extra sentence is a sandbox notice, which is a constraint, not usage 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 at all, the description carries the full burden and does disclose genuinely useful traits: sandbox-only, fictional partners, simulated quotes, no real purchase, US-only, and a requirement to relay a notice to the human. It omits what the session actually produces (session identifier?), its lifetime, and any rate or auth constraints, so the behavioral picture 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 block "SANDBOX: use fictitious data only. Do not enter real personal details." appears verbatim twice, and "TEST ONLY"/sandbox framing is restated three times. The one actionable instruction (relay the notice) is buried in the middle rather than 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 session-entry tool with three parameters, no annotations, and no output schema, the description should explain what a session is, what it returns, and what the agent does next. Instead it spends nearly all its length on legal disclaimers and leaves the operational model undefined.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33% — service_id is documented in the schema, while agent_name and jurisdiction are bare. The description adds nothing about agent_name and only implicitly touches jurisdiction via "United States only," so it does not compensate for 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 opening clause "Start an anonymous TEST-ONLY quote session" gives a specific verb and resource, but the purpose is then buried under disclaimers. It never distinguishes itself from siblings like moltbound_quick_quote, moltbound_get_quotes, or moltbound_human_sim_start, so an agent cannot tell which session/quote entry point to pick.

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?

"Relay the notice to your human, then continue" is a procedural instruction, not a when-to-use rule. There is no guidance on when this should be called instead of quick_quote or human_sim_start, no prerequisites, and no indication of what to do after the session starts.

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