Oxaide — Singapore company research for AI agents

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

Annotations already declare the mutation profile (readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false). The description adds real value beyond them: immediate job-id return, the ~15m email turnaround for the quote, pricing tiers, and the payment prerequisite.

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, front-loaded with the action and immediate return, then timing/pricing, then the prerequisite. Every sentence carries distinct, non-redundant 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?

No output schema exists, yet the description covers the return (job id), the follow-up artifact (emailed quote), cost tiers, and the hard dependency on pay_audit. Annotations cover the safety profile, and 100% schema coverage handles parameters.

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

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

Schema description coverage is 100%, so the schema already documents brief, email, and source with context (delivery is email-first, refunds route to email). The description adds no parameter-level detail beyond that, 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 ("Create a private research job (Oxaide)") and adds the immediate outcome ("Returns a job id immediately"). It is clearly distinguishable from get_audit/list_audits by verb, though it does not explicitly name those 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?

Explicitly states the prerequisite workflow: "Pay with pay_audit before any work starts," naming the sibling tool and the ordering constraint. It provides clear context but no explicit when-not-to-use or exclusion criteria.

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

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructiveness. The description adds value beyond that by revealing the specific data returned (status, pricing, payment state, delivery state) and by framing the tool as a polling mechanism, which is useful behavioral context for an agent.

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 contain all essential information: what the tool returns and when to use it. No filler or redundancy; information 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 simple single-parameter getter with strong annotations, the description is largely sufficient. It covers purpose, return fields, and usage timing. A minor gap is not distinguishing from get_audit_result, but the field list provides enough differentiation for 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 coverage is 100%, and the parameter 'id' is already well-described as the job id returned by create_audit with format brief_xxx. The description does not add further param-specific meaning, so the baseline of 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?

The description states a specific verb ('Get'), a single resource ('one job'), and the exact fields returned (status, quoted tier/price, payment state, delivery state). This clearly differentiates it from siblings like list_audits (plural), create_audit (creation), and pay_audit (payment), and the title reinforces 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 explicitly says 'Poll after create_audit', giving clear temporal context for when to invoke the tool. It does not explicitly name alternatives or exclusion cases (e.g., when to use get_audit_result instead), 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context beyond annotations: the result is a markdown summary, and files are delivered asynchronously via email and status page. No contradiction with annotations.

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?

One clean sentence with the core action front-loaded and a compact parenthetical clarifying the expected result. No wasted words or redundant restatement of 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 single-parameter, read-only tool with full schema coverage and annotations, the description is largely complete: it names the resource, the output format, and the delivery mechanism. The main gap is not explicitly explaining when the delivered pack becomes available or how this tool relates to get_audit.

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

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

Schema coverage is 100% and the single required parameter 'id' is already described as 'Job id'. The description does not add extra parameter-level detail, which matches the baseline for fully documented 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 uses a specific verb ('Get'), a specific resource ('delivered answer/pack for a job'), and concrete content details ('markdown summary; files arrive by email + status page'). It clearly identifies a retrieval operation and distinguishes this from a generic audit fetch.

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 via the word 'delivered' and the mention of email/status-page delivery, suggesting it is for retrieving a completed result. However, there is no explicit guidance about when to use this tool versus siblings like get_audit, nor 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: admin_token must match the server MCP_ADMIN_TOKEN and is disabled when unset, plus an explicit statement that the tool is never public. This goes beyond the annotations.

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 compact sentence that front-loads the action and restriction. It is efficient and free of filler, though the terminology mismatch ('jobs' vs 'audits' vs 'Briefs') slightly detracts from structural clarity.

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

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

For a simple list tool with two parameters and no output schema, the description covers auth and access scope but does not describe the return format or clarify what 'jobs' refers to. The terminology ambiguity leaves some gaps, though the annotations handle the safety profile.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds meaning for admin_token by specifying it must match the server token and is disabled when unset, which is more detail than the schema's 'Admin token (MCP_ADMIN_TOKEN)'. This extra semantic context justifies 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?

The description states 'Admin only: list recent jobs', which is a clear verb and resource, and the admin restriction helps distinguish it from public tools. However, the term 'jobs' conflicts with the tool name 'list_audits' and the title 'List recent Briefs (admin)', creating terminology inconsistency that prevents a perfect 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?

The description gives access context ('Admin only', 'Never open to the public') and the token requirement, but it does not explain when to use this tool versus siblings like get_audit or get_audit_result. Usage is implied rather than explicitly contrasted with alternatives.

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

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: the lookup is free and instant, and the data comes from a monthly register snapshot (staleness), plus an explicit statement of what is excluded. It stops short of auth or rate-limit detail, so a 4 rather than 5.

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

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

Two sentences, front-loaded with the return scope before the limitation and the routing instruction. Every clause earns its place: capability, data source, exclusion, and alternative tool with its argument template.

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

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

There is no output schema, so the description compensates by enumerating the returned fields and stating the data source. For a single-parameter read tool whose annotations carry the safety profile, nothing needed to call it correctly is missing.

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

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

Schema description coverage is 100% and the single parameter already carries an example UEN format, so the schema does the heavy lifting. The description names the UEN but adds no syntax, format, or validation meaning beyond what the schema provides, making the baseline 3 correct.

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 (lookup) and resource (Singapore entity by UEN) and enumerates exactly what is returned: registered name, status, entity type, registration date. It also distinguishes itself from the ownership-chain path via create_audit, so an agent can separate it from its siblings without opening a 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?

Explicitly gives the when-not and the alternative: officers and shareholders are NOT in the free snapshot, and the ownership chain requires create_audit with a specific query string. It even supplies the exact argument pattern ('Ownership of <name> (<uen>)'), removing all inference.

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

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

Annotations describe the operation as readOnly=false/openWorld=true/idempotent=false, and the description harmonizes with that by disclosing the two-phase payment flow and the critical rule that work starts only after payment is verified AND settled. It also explains what each method returns and the header/meta requirement for settlement — substantial behavioral context beyond annotations.

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 front-load the core action and then pack the payment flow details efficiently. There is no filler, and every clause adds operational 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?

Despite having no output schema, the description states what each method returns and gives the settlement steps an agent must take. Combined with the schema's id and method definitions, an agent has enough information to drive the payment flow 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 covers 100% of parameters, giving the baseline 3. The description adds meaningful method semantics: stripe returns a Stripe Checkout URL and x402 returns v2 payment requirements on Base, plus which method is default. 'id' is not elaborated beyond the schema's 'Quoted job id,' but the schema already covers 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?

Description opens with 'Pay a quoted job,' a specific verb+object that clearly identifies the operation. It then distinguishes between stripe and x402 payment paths, and the name/title align with the action.

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: pay only a 'quoted job,' and use stripe vs x402 based on desired payment method. It explains the two-step settlement for x402, but no sibling tool is a payment tool, so there are no explicit when-not-to-use 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?

Adds concrete behavioral facts beyond annotations: ~5 min turnaround, delivery by email + status page, the authorization model (pack_id possession authorizes the redeem), and the email-match constraint. Annotations already cover safety (readOnlyHint=false, idempotentHint=false), so this useful operational context earns credit. Minor gap: no details on failure modes if pack is exhausted.

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

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

Three compact sentences, front-loaded with the action and its key constraints. Slightly dense with parenthetical pricing/time info, but all of it earns its place for an agent deciding whether it can call this 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?

Covers what the tool does, prerequisites, cost model, timing, and the fallback path. No output schema, but the description states delivery via email + status page. Missing only edge-case behavior (e.g., what happens when the pack runs out), which is minor.

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 baseline is 3, but the description adds meaning beyond the schema: pack authorization semantics ('Possession authorizes the redeem'), the email-match rule, and the ~5 min delivery window tied to 'email'. This supplements the schema's terse definitions.

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: 'Run one prepaid registry ping', with scope, duration and delivery method. It clearly distinguishes itself from the audit-oriented siblings (create_audit, get_audit_result, etc.), which it does not overlap with.

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 prerequisites: needs a pack_id from a ping-pack purchase, delivery email must match purchase email, and gives the alternative path ('No pack? POST /api/brief/ping-pack first') with a pricing link. This is exactly the when-you-need-what an agent 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?

Annotations already declare the mutation/non-idempotent/open-world profile, and the description adds real context on top: the payment-gated activation flow and the Stripe checkout return (cards + PayNow). It does not cover what happens on repeat calls or renewal after the 12 months, so it falls short of full 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?

Two sentences, front-loaded with the action, scope, and cost, then the return/activation behavior. The price enumeration is dense but each entry is decision-relevant, so little is wasted.

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

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

With no output schema, the description carries the return burden and does so ('Returns a Stripe checkout URL... activates on payment'), plus all three required inputs are named. Missing only post-payment behavior details such as renewal or failure handling.

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 baseline is 3. The price-per-plan list adds useful meaning for the 'plan' parameter, but its labels ('business-name', 'IPOS-filing') do not match the schema's enum values ('trademark', 'ipos-watch'), which introduces mild ambiguity rather than clean added semantics.

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 ('Start a prepaid 12-month Watchtower watch') with scope, pricing tiers, and what is produced. It is unmistakably distinct from siblings like create_audit, pay_audit, or lookup_ownership without needing their schemas.

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 states prerequisites ('Needs the target + delivery email') and the activation condition ('activates on payment'), which implies when it applies. However, it never contrasts itself with plausible alternatives (e.g., pay_audit for payment, create_audit for one-off checks) or states 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.