BlinkHub Wire

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 implies a read-only operation and discloses the shape of the returned information (plan, quota, usage), but says nothing about auth requirements, rate limits, or whether quota values are per-key or per-account. Adequate but with clear 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?

A single front-loaded sentence that names the actor (API key), the primary payload (plan, quota), and the secondary datum (usage). Every clause earns its place with zero 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?

With zero parameters and no output schema, the description's only remaining obligation is to sketch what comes back, which it does reasonably (plan, monthly quota, consumed amount). It is complete enough to invoke correctly, though the exact return fields and their units remain unspecified.

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 of 4 applies. There is no parameter syntax an agent could get wrong, and the description adds no parameter detail because none exists to explain.

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 ('Show') and a concrete resource (the API key's plan, monthly quota, and consumed amount). The resource is entirely disjoint from the sibling tools (articles, markets), so an agent can distinguish it without opening schemas, though no sibling is named 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?

Usage is only implied: an agent can infer this is the tool to call when it needs billing/quota information. There is no explicit statement of when to use it, no prerequisites (e.g., 'requires a valid API key'), and no exclusions or 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 full burden and does well: it discloses the metered cost ('counts 1 toward the monthly quota; re-reading is free') and a compliance obligation (the required copyright line must be included). It does not cover auth/account requirements, which the account_status sibling hints may be relevant.

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 most decision-relevant fact (quota cost) in parentheses, then lists args and returns compactly. Every sentence earns its place with 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?

With no output schema, the description compensates by enumerating the return payload (headline, body, source agency, time, original link, copyright line). Combined with the quota and parameter details, an agent has everything needed to call and use the result.

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 and it does: it enumerates the allowed market values (us, kr, gb, eu, nz, au) that are absent from the schema, and explains that id must come from search_articles. Nothing needed to call the tool correctly is missing.

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

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

States a specific verb+resource ('Get the full text of one article') and scopes it to a single article, which cleanly separates it from the plural search_articles sibling. It even names search_articles as the provenance of the id, so the agent knows the relationship between the two 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?

Implies the workflow search_articles -> get_article by stating the id comes from search_articles, and the quota note signals that calls should not be wasted. It stops short of explicitly saying when NOT to use it (e.g. use search_articles for headline lists), so it is clear context rather than full 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?

No annotations are supplied, so the description carries the full behavioral burden. It usefully discloses the shape of an entry (language, content, license terms), and "List" implies a safe read, but it says nothing about authorization requirements, whether the full set is returned unpaginated, or how often it changes.

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 preamble or filler; the resource comes first and the payload detail follows. Nothing to trim.

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 parameters, no annotations, and no output schema, the description is the only source of return-value information, and it does name the key fields (language, content, license terms). It is nearly complete for a no-arg lister, missing only staleness/authorization 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 tool takes zero parameters, so there is nothing for the description to disambiguate and the schema is effectively complete. Baseline 4 applies; no parameter-level gap exists.

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?

Specific verb ("List") plus a concrete resource ("markets (countries/regions)") and an enumeration of what each entry carries (language, content, license terms). It is clearly distinguishable from its siblings (account_status, get_article, search_articles) by subject matter alone, though the description never explicitly contrasts itself with 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?

Usage is only implied: an agent can infer this is the discovery call for market/region identifiers, but there is no explicit statement of when to call it, when not to, or which sibling to prefer for other lookups. No prerequisites or follow-up routing are 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?

No annotations are provided, so the description carries the full burden and does well: it discloses the zero-quota cost model, that Korean-market articles require Korean keywords, and the exact matching semantics (every word must appear in headline, summary, or source agency). It does not cover auth requirements, rate limits beyond quota, or failure modes, hence a 4 rather than 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?

The purpose and cost model are front-loaded in the first sentence, and the parameter block is terse with no filler. The Args-style formatting is docstring-flavored rather than prose, but every line earns its place, including the return-fields note.

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 still enumerates returned fields (headline, summary, source agency, publish time, id) and routes to get_article for full text. Combined with full parameter coverage and no annotations to rely on, nothing an agent needs to invoke this 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 0%, yet the description compensates fully: it enumerates market values (us, kr, gb, eu, nz, au), explains query matching and the empty-query default, gives the since format (YYYY-MM-DD) and inclusive semantics, and states the limit range (1-30). Every one of the four parameters is documented 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?

States a specific verb and resource ('Search recent government press releases in one market') with explicit scope, and distinguishes itself from get_article by noting the latter is for full text. An agent can tell what this tool returns without opening the schema.

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

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

Points to list_markets for valid market codes and get_article for full article bodies, and explains that an empty query returns the latest articles. It also notes the tool is free and does not consume quota, which helps an agent choose it over metered siblings. It stops short of stating when not to use it, but the context is clear.

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