Unified Jobs MCP Server

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the no-account requirement, inline wallet payment model, and 402 flow, but it does not clearly state whether calling this tool itself is free/read-only or whether it can initiate payment, leaving a meaningful side-effect ambiguity despite the tool's zero-parameter nature.

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 main purpose, with the layer and price details following immediately. It is dense but mostly earns its length; a small amount of jargon reduces clarity slightly.

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, no-output-schema informational tool, the description adequately lists what is returned: metered layers, exact prices, pay-to address, and 402 flow explanation. The main remaining gap is explicit confirmation that the call itself does not transact and the expected return format.

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 are no parameter semantics to explain and the baseline is 4. The description appropriately focuses on returned information rather than parameter behavior.

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 resource: it returns the paid x402 rail details, including metered depth layers, exact USDC/Base prices, pay-to address, and 402 flow. It is clear what the tool provides, though the phrase "Return the paid x402 rail" is somewhat jargon-heavy and the tool is not explicitly differentiated from its 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?

Usage context is implied by "No account; an x402-aware client pays inline from the agent's wallet," which tells the agent this is for discovering premium payment details. However, there is no explicit when-to-use guidance, no exclusions, and no reference to alternatives or prerequisites beyond the payment client requirement.

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 scope (ATS platforms the feed auto-detects and normalizes) and cost (Free), which tells the agent this is a free read-only introspection call. It does not describe the return shape, whether the list is static, or auth requirements — modest gaps for a zero-parameter 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?

A single front-loaded sentence with no filler: verb, resource, scope qualifier, and cost. Nothing is redundant.

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

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

For a zero-param tool with no output schema, the description says what is enumerated and that it costs nothing. It could go slightly further by indicating what a returned entry looks like (platform name/identifier), but that is a small gap.

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

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

The tool takes no parameters, so the baseline is 4; there is nothing for the description to clarify. The description correctly implies no filtering input is needed.

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 (List) and resource (supported ATS platforms) plus the meaningful qualifier that these are the platforms 'this feed auto-detects and normalizes'. No sibling (search_jobs, resolve_company, enrich_preview, get_premium_access) is similar enough to require explicit differentiation, so the absence of sibling naming is minor.

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 statement of when to call this versus alternatives, and no prerequisites. The trailing 'Free' weakly signals that this is not gated like get_premium_access, but the agent must infer that this is a discovery/introspection call.

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

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

No annotations exist, so the description carries the full burden. It does useful work by disclosing the return shape {platform, token, via} and that the call is free, but it omits failure modes (unknown company, ambiguous platform), rate limits, and what 'via' actually signifies.

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: capability and input forms first, then the return shape and cost. Nothing is redundant and the key 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 one-parameter lookup with no output schema, the description supplies the return fields and the free-tier detail an agent needs to sequence it before paid enrichment. Only the unresolved-company behavior and the meaning of 'token'/'via' are left implicit.

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

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

Schema coverage is 100% and the single parameter is documented with matching examples ('bunq' / 'bunq.com'), so the description's 'bare slug or domain' mostly restates the schema. Baseline 3 applies; no extra syntax or normalization rules are added.

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: resolve which applicant-tracking system a company uses and its board token, plus the accepted input forms. It is clearly distinct from search_jobs and list_platforms, but it never mentions how it differs from enrich_preview or get_premium_access, which could plausibly overlap on company lookups.

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

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

Usage is only implied: 'from a bare slug or domain' tells you what to feed it, and 'Free' hints at a cost distinction against get_premium_access. There is no explicit statement of when to choose this over enrich_preview, nor what happens when resolution fails or returns nothing.

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

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

With no annotations, the description carries the full burden and does well: it discloses the keyless/no-auth model, that this is free while derived layers are metered, and that platform/board token are auto-detected, so the agent knows a bare slug is acceptable. It omits rate limits, pagination behavior beyond the per-company cap, and error/failure modes, which keeps it short of a 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?

Front-loaded with the core action, then platform coverage, return shape, and pricing in a logical order. Dense but nearly every sentence carries information; the platform enumeration and return-field list are long but justified by what they disambiguate.

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 enumerates the unified return fields (title, company, location, remote, url, source_platform, posted_at), so an agent knows exactly what comes back. With three well-documented parameters and a stated free/metered boundary, nothing material is missing.

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

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

Schema coverage is 100%, so baseline 3 applies. The description reinforces the auto-detection semantics for the companies parameter (bare slug or domain), but adds no format or constraint detail beyond what the schema already documents for maxPerCompany and includeDescription.

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 ('Fetch live, normalized open job postings') and bounds scope precisely (one or more companies, 7 named ATS platforms). An agent can distinguish it from siblings like resolve_company or list_platforms without opening either 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?

Clear context: use this to get actual postings, and it explicitly routes the agent to get_premium_access for derived layers and the 10-ATS hosted feed. It does not explicitly state when to use resolve_company or list_platforms first, so the alternative-selection guidance is incomplete rather than absent.

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