agent-economy-data

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

No annotations, so the description carries the burden. 'Number of' plus the day-bucketing implies a safe read-only aggregation, and the max-365 cap is a useful limit disclosure. It does not say what the response looks like (a date→count series?), whether empty days are included, or whether any auth/quota applies.

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 sentence, front-loaded with the metric, then granularity, then the window bound. Nothing 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 single-optional-param analytics tool with no output schema, the definition covers purpose and the window constraint but leaves the return shape ambiguous (per-day buckets, ordering, zero-filled days). An agent can call it, but cannot anticipate the result structure.

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 the single parameter, and it does: 'days' is the lookback window with a documented ceiling of 365; the default of 30 is in the schema. Only the zero/negative edge case is left unstated.

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 metric (number of new servers) with an explicit granularity (per UTC day) and scope (last N days), which implicitly distinguishes it from the cumulative sibling new_servers_count_since. It never names that sibling, but the per-day vs. aggregate framing is clear enough to pick correctly.

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?

'For the last N days (max 365)' implies trend/historical use and gives a hard bound, but there is no statement of when to use this instead of new_servers_count_since or registry_totals, and no exclusions or prerequisites. Usage is only inferable.

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 burden; it does disclose the key behavior that results are counts only, not server records, and that grouping is by namespace type. It omits whether counts cover the current snapshot or all history, and says nothing about authentication or result shape beyond the grouping key.

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 fragments, front-loaded with the resource and grouping dimension, and the 'counts only' qualifier is useful. The telegraphic style is efficient though slightly under-specified rather than 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?

For a no-parameter stat tool with no output schema, the description covers what is counted and how it is grouped, but leaves open the temporal scope (snapshot vs cumulative) and the exact shape of returned keys. That is a real, if 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 zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description implicitly confirms no filtering options exist.

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 output: server counts grouped by namespace type, with a concrete clarifying example (io.github vs own domain). It distinguishes itself reasonably from the count/total siblings by implying a categorical breakdown, though it never names an alternative.

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 use this versus registry_totals or daily_new_counts, no mention of scope (all-time vs snapshot), and no exclusions. The agent must infer usage from the sibling names alone.

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

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

No annotations are provided, so the description carries the burden. It usefully discloses the date format (YYYY-MM-DD), inclusive semantics ('on or after'), and the aggregate return nature ('Counts only'), but says nothing about permissions, failure on malformed dates, or the exact shape of the grouped result for a 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?

A single sentence, front-loaded with the core action and scope, with no filler. Every clause (date semantics, grouping dimension, counts-only) adds information.

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

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

For a simple one-parameter aggregate tool with no output schema, this is nearly complete: it covers what is counted, the date boundary semantics, and how results are split. The only gap is the precise response representation (e.g., map keyed by namespace type), which is reasonably inferable.

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 one parameter exists and the schema gives it no description (0% coverage). The description compensates partially by specifying the required YYYY-MM-DD format and that the date is an inclusive lower bound, which is genuinely useful information not present in 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?

States a specific verb+resource: counts servers first published on or after a given date, split by namespace type. 'Counts only' clarifies the aggregate nature, which helps distinguish it from sibling tools like spec_changes_since or daily_new_counts, 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?

There is no explicit guidance about when to use this instead of daily_new_counts or registry_totals. The phrase 'Counts only' implies an aggregate query, but the agent must infer that from the description rather than being told when this tool is the right choice.

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

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

No annotations are provided, so the description carries the burden; it does disclose the shape of the result by enumerating the count categories, which is genuinely useful. However it says nothing about whether the totals reflect the latest snapshot, whether they are cached, or how to check snapshot freshness, which matters given the sibling snapshot_info 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 sentence that front-loads the resource and then enumerates the aggregates; nothing is padded. It is arguably too terse for a tool with no annotations and no output schema, but it wastes no words.

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

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

Because there is no output schema and no annotations, the description is the only source of information about return values, and it does list the count categories. It stops short of describing the response structure or snapshot currency, leaving a real gap for a zero-parameter aggregate 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?

The tool takes zero parameters, so there is no parameter semantics to explain; the baseline of 4 applies. The description correctly implies no filtering or scoping options are available.

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

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

The description names the resource (the registry snapshot) and the specific aggregates returned (unique servers, status, transport, package-type counts), which is more than a restatement of the name. It does not explicitly contrast itself with siblings like daily_new_counts or new_servers_count_since, but the 'totals of the snapshot' framing is distinct enough to infer.

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 reach for this tool versus daily_new_counts, new_servers_count_since, or namespace_types, all of which compute counts over related data. The agent is left to infer that this one gives current whole-snapshot aggregates, and there are no exclusions or prerequisites given.

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 disclosure burden, and it discloses almost nothing: no read-only confirmation, no error behavior, no indication of how the snapshot is selected (there are no parameters, so 'this snapshot' is unexplained). One clause about the payload is insufficient for a tool with zero structured metadata.

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 short sentence with no filler, and the subject (what the snapshot contains) is front-loaded. It is efficiently sized but borders on under-specification rather than tightness.

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 is the only source of return-shape information, and it only gestures at three fields without structure or format. Combined with an unexplained implicit snapshot selection, an agent cannot reliably predict what calling this returns.

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

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

The tool takes zero parameters, so the baseline is 4. Nothing in the schema needs explaining, though the description never resolves how the target snapshot is scoped without any input.

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

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

The description names the resource (a snapshot) and the three things it reports (contents, date, source), which is more than a restatement of the name. But there is no verb and no differentiation from the sibling tools (daily_new_counts, registry_totals, spec_changes_since), so it reads as a vague 'info about X' rather than a precise operation.

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 instead of the sibling aggregate/count tools, nor any prerequisite or exclusion. The agent must infer usage entirely from the name.

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

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

No annotations are provided, so the description carries the burden. It usefully discloses that the output is a summarized interpretation ('in our own words') with source links and warns that the 'Summary may be incomplete,' which is meaningful behavioral context. It does not state authentication needs, rate limits, or exact return structure.

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 compact, front-loaded statement of resource, scope, output style, and the incompleteness caveat. Every phrase carries useful information and there is no filler.

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

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

For a simple one-parameter retrieval tool with no output schema or annotations, the description adequately explains what is returned and flags the main reliability caveat. It stops short of clarifying whether the result is a list of changes versus prose summary, or timezone handling for the date.

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

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

Schema description coverage is 0%, so the description must compensate for the single parameter. It does so by giving the expected date format (YYYY-MM-DD) and the inclusive semantics ('on or after'). It does not address timezone or invalid-input behavior, keeping it short of 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?

The description names a specific resource (MCP and A2A specs) and a clear temporal scope (changes on or after a date), plus what kind of output to expect (own words with source links). It does not explicitly say 'returns' or name a sibling as a contrast, but the purpose is clear enough for an agent to distinguish it from the count/totals 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 is implied by the resource and date filter, but there is no explicit when-to-use guidance, no when-not-to-use conditions, and no alternative tool named. The sibling tools are statistically different, so misuse risk is low, but the description leaves selection reasoning to inference.

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