terminal

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

No annotations are provided, so the description carries the burden of disclosure. It reveals the scope of the output (coverage, corpus size, verification method) and adds useful domain context ('signed, source-bound'). However, it doesn't state the expected response format, whether it is a static text summary, or any limitations.

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, tightly written sentence with front-loaded identification and meaningful specifics. Every phrase earns its place, and there is no filler or repetition.

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 parameterless informational tool, the description covers the essential context: what DTA is, its key attributes, and the expected content topics. It lacks an explicit statement of the return shape or a direct 'use this when...' note, but overall it is sufficient for an agent to call the tool 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?

The tool has zero parameters and an empty input schema, so there is nothing for the description to explain. The baseline of 4 is appropriate because no parameter semantics are 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?

The description clearly identifies the resource (DTA/dta.mn) and frames the tool as an informational overview covering its coverage, corpus size, and verification. It does not use an explicit action verb like 'returns' or 'describes,' but the intent is unambiguous. It doesn't explicitly distinguish itself from the data-access siblings, though its meta/about nature is evident.

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 implies this is a starting point for understanding DTA before querying data, but it provides no explicit guidance on when to use this tool versus the sibling tools like search_series or get_datum. There are no stated exclusions or alternative routing 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?

No annotations exist, so the description carries the burden. It discloses the returned data composition, including a cryptographic signature and verification recipe, which is useful behavioral context. However, it does not state side effects, error behavior, permissions, or whether the operation is strictly read-only.

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 dense sentence that front-loads the tool's purpose and then lists the returned items. Every phrase adds value, there is no repetition or fluff, and the structure is easy to scan.

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 read-oriented tool with no annotations or output schema, the description covers the essential input and output composition. It stops short of detailing return structure, error conditions, or how the verification recipe should be used, but an agent can correctly invoke the tool with the provided information.

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% and the schema only gives shortid as a string. The description adds meaning by indicating shortid is the lookup key for a single observation, but it provides no format, constraints, or example. It compensates partially but not fully for the missing schema description coverage.

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' and a clear resource: a single signed observation's passport keyed by shortid. It enumerates the returned contents (value, vintage, source URL, schema, Ed25519 signature, verification recipe), which distinguishes it from sibling tools that deal with panels, movers, or series.

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 explicit guidance is given about when to use this tool versus alternatives. The description implies use when a shortid is available, but it does not mention when not to use it, nor does it point to siblings like search_series or get_movers for broader retrieval 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?

With no annotations, the description carries the behavioral disclosure burden. It does disclose that the result is a 'signed movers:v0 snapshot' and that ordering is by delta z-score, which is useful. However, it does not mention whether the data is live or cached, what the return shape looks like, or any rate/access constraints, though as a read-only getter the risk is modest.

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?

Single sentence, front-loaded with the key concept, and contains no filler. 'Today's biggest movers across the archive' immediately conveys scope, while the parenthetical adds precision about the snapshot and ranking metric without bloating the definition.

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 parameterless tool, the description is sufficient to know what the tool conceptually returns and how it is ordered. However, since there is no output schema, the description does not fully specify the returned item structure, so an agent cannot precisely anticipate field names or types. This is a clear gap, but not a severe one for such a simple 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 input schema has zero parameters, so there is nothing for the description to add about parameter meaning. The baseline for a parameterless tool is 4, and the description enriches context by explaining the snapshot and ranking criteria, which is more than the schema alone provides.

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 identifies the resource ('today's biggest movers across the archive') and the key aspect of the data ('ranked by delta z-score'). It lacks an explicit verb like 'list' or 'get,' but the tool name and phrasing make the purpose obvious. It does not explicitly distinguish itself from get_datum or get_panel, though the movers snapshot concept is sufficiently unique.

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 implies this tool is for retrieving today's movers, but it gives no explicit guidance about when to choose it over siblings such as search_series or get_datum. There are no stated conditions, exclusions, or alternatives, leaving the agent to infer usage from the name and phrasing 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?

With no annotations, the description is the sole source of behavioral context. It usefully discloses latest-vintage semantics, the point tuple shape, and the shortid linkage, but it says nothing about error behavior, ordering, missing values, authentication, or rate limits.

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 dense sentences front-load the core behavior and follow with the output format. There is no filler or redundant restatement of 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?

There is no output schema, so the description must convey the return shape; it provides the point tuple but not the full response container. It also omits failure modes and behavior for invalid or duplicate codes, leaving moderate gaps for a tool with only two 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?

The description clarifies that 'codes' means up to 8 series codes, supplementing the bare schema, while the limit parameter is already defined in the schema with default and maximum values. It does not explain accepted code formats or how 'latest vintage' interacts with the limit 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?

The description clearly identifies a time-series retrieval tool for up to 8 series codes and specifies the per-point format. It references get_datum but does not explicitly distinguish when to use this tool versus get_movers or search_series, so it stops short of full sibling differentiation.

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 phrase 'up to 8 series codes' implies batch use and the pointer to get_datum suggests a follow-up workflow, but no explicit when-to-use or when-not-to-use guidance is provided. An agent must infer the relationship between this tool and its siblings.

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 transparency burden. It discloses the result limit (up to 15 series) and the presence of codes, but it does not describe the return format, potential error cases, or whether the operation has any side effects. Since it is a search function, the lack of side-effect disclosure is acceptable, but the description could be more detailed about output 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 two concise sentences with no redundant information. It efficiently conveys the tool's purpose, scope, and output without unnecessary elaboration.

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?

The description provides sufficient context for an agent to understand what the tool does, what it returns, and how it fits into a larger workflow (use with get_panel). It does not specify the exact output schema or edge cases, but given the simplicity of the tool and the absence of an output schema, the description is adequately complete.

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 description of the only parameter 'q' is highly informative: it specifies that it is a substring with a minimum length of 2 characters and provides multiple examples in both English and Mongolian. This goes well beyond the schema's basic type definition and makes the parameter's semantics completely clear.

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 action (search), the resource (series catalog), and the search criteria (by code or name in English or Mongolian). It also mentions the return of up to 15 series with codes, which differentiates it from other tools like get_panel and supports its intended downstream use.

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 implies usage by stating it returns codes for use in get_panel, giving clear context for when to employ this tool. It does not explicitly mention alternatives or when not to use it, but the purpose is specific enough to guide appropriate use.

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