fred-mcp-server
Server Quality Checklist
Latest release: v0.2.2
- Disambiguation5/5
Each tool targets a distinct FRED resource (category, release, series, source, tag) or a specific operation on that resource. Descriptions clearly differentiate between similar tools like fred_category_children and fred_category_related, and fred_releases vs fred_releases_dates. No ambiguity.
Naming Consistency4/5Follows a consistent 'fred_{entity}_{action}' pattern, e.g., fred_category_children, fred_series_observations. Some minor deviations like fred_tags_series (entity-action order reversed) and fred_series_updates (no verb). Overall, very predictable and readable.
Tool Count4/533 tools is on the higher side but appropriate for the comprehensive FRED API being exposed. Each tool corresponds to a distinct endpoint, covering categories, releases, series, sources, tags, and geographic data. No unnecessary duplication.
Completeness4/5Covers the majority of FRED API functionality: search, metadata, observations, releases, categories, tags, sources, vintages, and geographic data. Minor gaps like missing regional data endpoints beyond geoFRED, but overall very comprehensive for economic data retrieval.
Average 3.2/5 across 30 of 33 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the return format ('dict with key 'sources''), but omits whether the operation is read-only, if it modifies state, pagination behavior, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), which is good, but it sacrifices informative content. It would benefit from a brief explanation of parameters or usage context while maintaining conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (though not shown), the description barely covers return format. It does not mention optional parameters, their defaults, or how to format dates. For a tool with three parameters and moderate complexity, the description is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description fails to explain any of the three parameters (release_id, realtime_start, realtime_end). With 0% schema description coverage, the description should compensate by describing each parameter's purpose and constraints, but it does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (Get) and resource (sources for a FRED release), distinguishing it from sibling tools like fred_release (which gets release metadata) and fred_release_series (which gets series within a release). However, it lacks any additional context such as what a 'source' represents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., fred_source). There is no mention of prerequisites, typical usage scenarios, or cases where this tool should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states return type (dict with key 'sources'), but does not disclose read-only nature, side effects, rate limits, or prerequisites. Lacks behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is very concise (two short sentences), but lacks structure and omits important details. Front-loads purpose, but too sparse to be informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool, description is incomplete. It fails to explain parameter roles, lacks context on realtime features, and does not elaborate on the return dict. Output schema presence helps but is not leveraged in description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but description does not explain any parameters. It fails to describe source_id (required) or optional realtime_start/end, leaving agents without meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets a specific source of economic data, which aligns with the tool name and indicates a single-source retrieval. However, it does not explicitly differentiate from sibling tools like fred_sources that list all sources, but the word 'specific' implies filtering by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. With many sibling tools, such as fred_sources for listing or fred_source_releases for a source's releases, missing context about when to choose each.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. Only states return format (dict with 'sources'), but lacks details on pagination, rate limits, data freshness, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise but too terse; missing crucial information. Could include parameter hints or output schema details while remaining short.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, no annotations, output schema exists but not described, and many sibling tools, the description is highly incomplete. Fails to explain pagination, sorting, or differences from similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and description mentions no parameters. All 6 optional parameters are undocumented, providing no meaning beyond the schema itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Get all sources of economic data', which is a clear verb+resource. Differentiates from 'fred_source' (singular) by implication of plural, but does not explicitly compare to siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'fred_source' or 'fred_releases'. Does not mention context such as filtering or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It only states return structure but no side effects, auth requirements, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with two short sentences. No wasted words, but could benefit from slightly more detail without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no annotations, and many sibling tools, the description is incomplete. It fails to explain parameters or provide usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and description provides no explanation of parameters. 'series_id', 'realtime_start', and 'realtime_end' are not described, leaving their meaning unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get the release for a FRED series' with verb and resource. However, it does not differentiate from siblings like 'fred_release' or 'fred_release_series', which have similar purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'fred_release' or 'fred_release_series'. The description lacks context for selecting the right tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states the tool 'gets' data (implied read), but does not disclose any behavioral traits such as pagination, default limits, or whether it returns all releases without filtering.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (two sentences) and front-loaded with the purpose. However, it is under-specified, sacrificing necessary information for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the extensive set of sibling tools and the complexity of the FRED API, the description fails to provide contextual completeness. It does not define what a 'release' is, how parameters affect results, or what the output schema contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides no explanation for any of the 6 parameters (e.g., realtime_start, limit, order_by). The agent must infer meaning solely from schema names and types, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Get all FRED releases') and the resource ('of economic data'), which is specific and distinguishes it from siblings like fred_release (single release) or fred_release_series (series of a release).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the many similar sibling tools (e.g., fred_release, fred_releases_dates). The agent receives no context about selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as pagination (limit/offset), sorting behavior, or the effect of realtime_start/end parameters. The only return format note is 'dict with key seriess'. No contradictions with annotations since none exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences covering purpose and return type. However, it could be more structured with bullet points, but no filler content exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 parameters, 0% schema description, no output schema details, and many related siblings, the description is incomplete. It does not explain the usage of optional parameters or the structure of the returned series data. The agent lacks information to invoke the tool correctly beyond the required tag_names.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description only adds context for tag_names (semicolon-delimited). Other parameters like realtime_start, realtime_end, exclude_tag_names, limit, offset, order_by, sort_order are not explained. The description adds minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and resource 'series matching all specified semicolon-delimited tag names'. It specifies that tags are semicolon-delimited. However, it does not differentiate from sibling tools like fred_series_tags or fred_series_search_tags, which likely perform similar retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, typical use cases, or when to prefer this tool over other tag-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states it returns metadata but doesn't disclose if it's read-only, any authentication needs, or side effects. Minimal beyond purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Short and to the point, with main purpose front-loaded. No wasted words, though it could be more structured with parameter description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers a simple metadata retrieval tool with one parameter. The output schema exists but description only gives a hint. With many siblings, more detail on when to use would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter series_id has zero description coverage in schema and no explanation in description. Agent is left to infer what series_id represents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves metadata for a geographic FRED series, listing included fields. It differentiates from siblings like fred_series (non-geographic) and geofred_series_data (data values). Could be more explicit about the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus the many sibling tools. No when-not-to-use or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only mentions the return type ('dict with key 'releases''), lacking details on required permissions, error handling, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (2 sentences) and front-loaded with the purpose, containing no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 7 parameters and no schema descriptions, the description fails to explain pagination (limit, offset), ordering, realtime dates, or any other context, making it highly incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 7 parameters, providing no additional meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Get') and resource ('releases for a source'), distinguishing it from siblings like fred_releases (all releases) and fred_source (source info).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states the return format but fails to mention whether the operation is read-only, what happens if no children exist, pagination behavior, or any rate limits. The lack of these details reduces transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two short sentences, with the purpose front-loaded. Every sentence provides necessary information without redundancy. It is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the three parameters with no descriptions and the sibling tools with similar names, the description is incomplete. It does not explain parameter usage, error states, or edge cases. While an output schema exists, the lack of parameter documentation leaves significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should explain the parameters. It only mentions 'category_id' implicitly via the tool name, and does not explain 'realtime_start' or 'realtime_end' at all. The description adds no meaning beyond the raw schema, leaving the agent uninformed about optional date filtering.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('child categories for a FRED category'). The verb and noun are specific and differentiate it from sibling tools like fred_category (gets a single category) and fred_category_related (gets related categories).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention when to avoid it, prerequisites, or compare it to sibling tools such as fred_category or fred_category_series. The agent is left to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only states the operation is a 'Get' (read) and returns a dict with key 'tags'. It does not disclose potential side effects, authentication needs, rate limits, pagination behavior, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two sentences) and front-loaded with the key purpose. However, it is too terse and lacks structure (e.g., sections for parameters, examples). It sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 10 parameters, no annotations, and an output schema that is only vaguely described ('dict with key tags'), the description is incomplete. It fails to explain common use cases, parameter interactions, or return format details beyond the key name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only hints at the 'tag_names' parameter ('semicolon-delimited tag names') but ignores all other 9 parameters (e.g., realtime_start, exclude_tag_names, limit). The description adds minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get tags') and the resource ('related to specified semicolon-delimited tag names'). It distinguishes this tool from siblings like 'fred_tags' (which lists all tags) and 'fred_series_search_related_tags' (which is for series). The format of input ('semicolon-delimited') is also specified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'fred_tags' or 'fred_series_search_related_tags'. There is no mention of use cases, prerequisites, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral details. It only mentions the return type (dict with key 'categories') but does not explain the optional realtime parameters, error conditions, or limits. This is insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that state the purpose and return type. No wasted words, and key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no schema descriptions, and an output schema, the description should explain all parameters and usage context. It fails to do so, notably omitting details about realtime_start and realtime_end which are standard in FRED API.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must clarify parameter meanings. It does not describe any of the three parameters, including the required series_id or the optional realtime_start/end, beyond their existence.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves categories for a FRED series, using a specific verb 'get' and resource 'categories'. It distinguishes itself from sibling tools like 'fred_category_series' (which gets series for a category) and others.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives. For example, it does not mention that this tool is for getting categories given a series, as opposed to fred_category_series which does the reverse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states that the tool returns a dict with key 'tags' but fails to disclose any behavioral traits such as rate limits, data freshness, authentication needs, or whether it is read-only. The description omits important context that an agent would need to use the tool safely.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief main sentence followed by an Args list and Returns line. It is concise and front-loaded. Minor redundancy (e.g., parameter names in Args lines) could be trimmed, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (11 parameters) and the presence of an output schema, the description adequately explains parameters but does not place the tool in the broader FRED context. It fails to explain how this tool differs from siblings or when it should be invoked. The return description is minimal but sufficient since the output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It provides brief explanations for each parameter (e.g., 'Search query to find series', 'Semicolon-delimited tag names'), adding meaning beyond the schema's types. However, some explanations like 'Start of real-time period' lack sufficient detail about the real-time period concept.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get related tags for a series search, filtered by specified tags,' which uses a specific verb and resource. However, it does not explicitly distinguish this tool from its sibling 'fred_related_tags' or other similar tools, but the context of 'series search' provides some differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists parameters in an Args section but provides no guidance on when to use this tool versus alternatives like 'fred_series_search_tags' or 'fred_tags'. There is no mention of prerequisites, limitations, or 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the burden. It only lists parameters and a return type, but does not disclose side effects, rate limits, authentication needs, or any behavioral traits beyond what is obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured as a Python docstring with an Args section, which is clear but somewhat verbose. It could be more concise, e.g., omitting obvious default explanations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, but the description does not elaborate on the return structure beyond 'dict with key ''tags'''. Given the tool has 5 parameters and many sibling tools, more context about tag relationships and usage limitations would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description lists parameters but adds minimal semantics beyond names and defaults. For example, 'order_by' has enum values in the schema but no explanation in the description. The parameter descriptions are essentially repetitions of the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the FRED tags for a series', specifying the verb 'Get' and the resource 'FRED tags for a series'. Among siblings like fred_category_tags and fred_release_tags, this tool is uniquely identified for series tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as fred_tags or fred_related_tags. There is no mention of use cases, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose behavioral traits such as read-only nature, potential rate limits, or data freshness. It only states return format, missing safety or performance context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear purpose statement followed by structured Args and Returns. It is well-organized and front-loaded, though slightly verbose with full parameter descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema existence, the description adequately covers purpose and parameters. However, it lacks behavioral notes and usage context, making it marginally complete for a tool with many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description's parameter docs add value by explaining date format and behavior. However, it does not specify what happens if both date and start_date are provided, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get cross-sectional regional data for a geographic FRED series', specifying the action and resource. It distinguishes from time-series tools like fred_series_observations, but is less distinct from geofred_regional_data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings. The description does not mention when to prefer this over geofred_regional_data or related tools, nor any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states the return type (dict with key 'categories') without mentioning whether it's a read-only operation, any side effects, or dependencies. This is insufficient for safe tool invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, with two sentences covering purpose and return type. However, it could be slightly more informative without being verbose, e.g., by acknowledging the realtime parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits parameter semantics and usage context. The tool has three parameters with no documentation, making it incomplete for an agent to use correctly without additional knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description provides no information about the three parameters (category_id, realtime_start, realtime_end). The agent gets no guidance on valid values or format, relying solely on the schema which lacks descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('related categories for a FRED category'). It effectively distinguishes from sibling tools such as fred_category (the category itself) and fred_category_children (hierarchical children).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by its name and purpose but provides no explicit guidance on when to use this tool versus alternatives like fred_category_children or fred_category_tags. No exclusion criteria or contexts are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It implies a read operation ('Get'), but does not state that it is read-only, mention required permissions, rate limits, or what happens with invalid inputs. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a concise docstring with a one-line purpose followed by a parameter list. Each line is relevant, and the structure is front-loaded. It avoids unnecessary verbosity while covering all parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, 0% schema descriptions, no annotations) and many sibling tools, the description adequately explains parameters and the return type, but lacks context on pagination, defaults, relationships between params, and how it differs from similar tag tools. An output schema exists but is minimally described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by explaining each parameter with a brief purpose and examples (e.g., 'series_search_text: Search query to find series (e.g., "GDP", "unemployment")'). It adds meaning beyond the schema's type definitions, though it lacks deeper relationships or usage patterns.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get the tags for a series search query', which clearly identifies the verb and resource. The purpose is distinct from siblings like fred_series (which returns series data) and fred_tags (which lists all tags), though it does not explicitly differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as fred_series_tags or fred_tags. There are no explicit context cues, exclusions, or recommendations for 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits such as data freshness, rate limits, or side effects. It only states the function and parameters, failing to add transparency beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear front-loaded sentence followed by parameter descriptions. It is concise without unnecessary words, though slightly verbose with full-sentence parameter listings.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data retrieval tool with 7 optional parameters and a simple output schema, the description covers the purpose and all parameters. It lacks background context on 'release dates' but is reasonably complete given the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter (e.g., 'realtime_start: Start of real-time period (YYYY-MM-DD).'). These explanations add meaningful context beyond the schema's type-only definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get release dates for all FRED releases,' specifying the verb and resource. It implicitly differentiates from sibling 'fred_release_dates' by including 'all,' but does not explicitly mention alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus siblings like 'fred_release_dates' or 'fred_releases.' There is no mention of prerequisites or 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states returns a dict with key 'tags', ignoring pagination, rate limits, or default behavior. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words, efficiently stating purpose and return. However, front-loads well but lacks detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters and many sibling tools, the description is incomplete. No explanation of pagination, ordering, real-time periods, or search text. Only basic return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate but only vaguely references filtering by name/group (covering tag_names and tag_group_id). It omits other parameters like search_text, limit, offset, order_by, etc.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get all FRED tags' with optional filtering by name or group, which is a specific verb+resource and distinguishes from siblings like fred_related_tags or fred_tags_series.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving tags with optional filters but does not provide explicit when-to-use, when-not-to-use, or alternative tools among the many siblings. No exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the return format ('dict with key 'categories'') but does not disclose any behavioral aspects such as whether it is read-only, side effects, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, but it could be slightly more structured. However, it efficiently conveys the core purpose and a key usage detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown) and multiple siblings, the description partially completes the picture by stating the return type. However, it lacks details on category metadata structure and fails to explain the purpose of date parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 3 parameters with 0% description coverage. The description only explains category_id's default for root but does not clarify the purpose of realtime_start and realtime_end, leaving their semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Get a FRED category' and specifies the resource. It distinguishes from siblings like fred_category_children by focusing on a single category retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage tip for the root category but does not explicitly guide when to use this tool over alternatives like fred_category_children or fred_category_related.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the return format (dict with key 'vintage_dates'), but with no annotations, it lacks details on error behavior, realtime date semantics, or parameter effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (two sentences), front-loaded with the action and resource, no redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits explanations for parameters like realtime_start/end, limit, offset, and sort_order, leaving significant gaps for a tool with 6 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about parameters. It does not compensate for the schema gap, providing zero semantic value beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('vintage dates / revision history for a FRED series'), distinguishing it from siblings like fred_series_observations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use versus alternatives; usage is implied by the purpose, but no exclusions or contextual advice are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose behavioral traits such as side effects, mutability, authentication needs, rate limits, or pagination behavior. The description repeats parameter info but adds no behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the core action, and structured as a docstring with a clear parameter list and return statement. Every sentence serves a purpose without extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, no annotations, and an output schema that exists but is not detailed, the description lacks depth. It does not explain filtering mechanics, pagination behavior, or the structure of the return value beyond 'dict with key seriess'. Edge cases and usage context are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists all parameters with brief explanations (e.g., 'category_id: FRED category ID'), adding format hints for some (like YYYY-MM-DD). However, many descriptions are minimal and add little beyond the parameter names. With 0% schema coverage, the description compensates partially but not richly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Get the series in a FRED category,' which is a specific verb+resource pair. It clearly distinguishes from sibling tools like fred_category (category details) or fred_series (general series operations).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose is implied by the name and first sentence, but there is no explicit guidance on when to use this tool versus alternatives. No when-not-to-use or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The 'Get' verb implies a read operation, and the return format is mentioned, but with no annotations, the description lacks explicit disclosure of safety, side effects, or permissions; minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with only two sentences, no fluff, and front-loaded with the purpose statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of many sibling tools and a simple parameter set, the description is nearly complete but missing parameter semantics and usage guidance reduces contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description does not explain the parameters (release_id, realtime_start, realtime_end) beyond their types in the schema, which is insufficient for correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Get) and resource (specific FRED release), distinguishing it from sibling tools like fred_releases (all releases) and fred_release_dates (release dates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool over alternatives such as fred_releases or fred_release_dates; usage is implied by name only, not clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the return format (dict with seriess key), but lacks details on side effects, authentication requirements, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Gets directly to the point with clear structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description provides some additional context on the return format. However, it lacks usage guidance and parameter details, making it minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters. Parameter names are self-explanatory, but the description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get metadata for a FRED series', specifying verb and resource. It distinguishes from sibling tools like fred_series_observations (observations) and fred_series_search (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention prerequisites or context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as side effects, authentication needs, rate limits, or pagination. It only states the return structure (keys 'meta' and 'data'), which is minimal beyond functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description uses a structured Args/Returns format with concise parameter lines. It is not verbose and each sentence serves a purpose, though it could be more front-loaded with the primary verb.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 5 required), the description is adequate but lacks details on error conditions, data limits, or what 'meta' contains. It references obtaining series_group, which is helpful, but overall completeness is moderate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds value beyond the input schema by providing examples for season ('SA', 'NSA'), units ('Dollars'), and aggregation_method ('avg', 'sum', 'eop'), and specifying date format (YYYY-MM-DD). However, some parameters like region_type and frequency lack examples, and transformation references another tool's codes without elaboration.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get cross-sectional regional data by series group.' This clearly identifies the tool's verb (Get), resource (cross-sectional regional data), and differentiates it from siblings like geofred_series_data (time series) and geofred_shapes (geographic shapes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that series_group can be obtained from geofred_series_group, providing a prerequisite. However, it does not specify when to use this tool versus alternatives like geofred_series_data or provide exclusions for certain inputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes parameter interactions and return format ('dict with key tags') but does not mention idempotency, safety (read-only), rate limits, or auth requirements. The tool appears read-only but this is not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear initial sentence and detailed Args/Returns sections. However, it is verbose; the parameter explanations could be more compact. The information about standard parameters like limit and offset could be omitted if schema covered them.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 12 parameters, two modes, no annotations, and a minimal output schema, the description covers parameter behavior, modes, and return structure. It lacks examples or error handling details but is sufficient for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add value. It provides an Args section explaining each parameter, including the special behavior of related_to and tag_names interaction. This adds significant context beyond the schema's type-only definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets tags for a FRED category or finds related tags. It identifies two modes based on the related_to parameter. However, it does not explicitly distinguish this from sibling tools like fred_tags or fred_related_tags, which also deal with tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the two modes (normal and related) and notes when related_to is set tag_names is ignored. However, it does not provide guidance on when to choose this tool over siblings that retrieve tags without category context, such as fred_tags.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. However, it only lists parameters and the return type (dict with key 'seriess'), omitting details like rate limits, authentication requirements, or side effects. The safety profile is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description follows a structured Args/Returns format, making it easy to scan. It is concise enough, listing parameters without redundancy, though it could be slightly tighter by not repeating the tool's name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (11 parameters, many optional) and the absence of annotations, the description covers all parameters and the return format. It could mention that the output schema exists, but that is not strictly required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description explains each parameter in plain language (e.g., 'FRED release ID', 'Start of real-time period (YYYY-MM-DD)') and clarifies dependencies for filter_variable and filter_value. This adds significant meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the series on a FRED release', specifying the verb (Get) and resource (series on a FRED release). This distinguishes it from sibling tools like fred_release (which gets release metadata) and fred_series (which gets series by ID), among others.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings. It does not mention alternatives or conditions for its use, such as when to prefer this over fred_release_series_tags or fred_release_tables.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only lists parameters and mentions the return dict, but does not disclose behavioral traits like rate limits, pagination behavior, or that it is a read operation. The real-time period parameters are mentioned but their significance is not explained beyond format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a brief intro followed by a bullet-point parameter list. It front-loads the purpose and avoids unnecessary words, though it could be slightly more concise by integrating parameter descriptions into a single sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 parameters, no annotations) and presence of an output schema, the description explains all parameters and the return structure. However, it lacks usage guidelines and behavioral details like timeouts or error handling, leaving some gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description compensates by explaining all 12 parameters with examples (e.g., 'search_text: Search query (e.g., "GDP", "unemployment rate").') and value constraints (e.g., 'search_type: "full_text" or "series_id"'). This adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search for FRED series by text', specifying the verb 'search' and the resource 'FRED series'. It distinguishes from sibling tools like fred_series (which retrieves a specific series by ID) and fred_series_search_tags (which searches tags).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for text-based searches but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not-to-use guidance is provided, such as noting that fred_series is better for known series IDs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It indicates the return format (dict with 'elements') and parameter purposes, but does not disclose traits like read-only nature, authorization needs, or error behavior. This is adequate but minimally informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured as a docstring with Args and Returns sections. It is concise with no extraneous text, though the first sentence could be slightly more front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (signal indicates true), the description needn't detail return values extensively. It covers the main parameters and return shape. However, it omits any mention of error handling or tree hierarchy nature, which would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds significant meaning beyond the schema. It explains element_id: 'Omit for the root,' include_observation_values: 'If true, include observation values,' and specifies date format for observation_date. This compensates for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get release table trees for a FRED release,' using a specific verb and resource. Among siblings like fred_release and fred_release_series, it clearly distinguishes itself by focusing on 'tables' as a tree structure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like fred_release_series. The description implies usage when one needs the table tree structure, but lacks exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavioral traits. It fails to mention that the tool is read-only, has rate limits, or any potential errors (e.g., invalid series_id). Although parameters are well-documented, behavioral context is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear one-sentence purpose followed by a parameter list. Each sentence adds value, though the parameter section is lengthy due to many options. No fluff, and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 parameters, no annotations, low schema coverage), the description covers all essential aspects: purpose, each parameter's meaning, valid values, and the return format. It includes output schema info, making it sufficiently complete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. The Args section provides thorough explanations for all 13 parameters, including enum interpretations (e.g., 'lin' for levels, 'chg' for change) and date formats. This adds significant meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get observations (data values) for a FRED series.' This is a specific verb+resource combination that clearly distinguishes it from sibling tools like fred_series (metadata) or fred_category (categories).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by describing what the tool does (retrieve data values), but it does not explicitly state when to use this tool over alternatives, nor does it provide exclusion criteria. Given the many sibling tools, explicit guidance would improve usability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes parameters and return type ('dict with key 'seriess'') but does not disclose potential side effects, rate limits, or error conditions. The read-only nature is implied but not confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, well-structured with clear sections for Args and Returns. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 7 parameters and lack of annotations, the description covers all parameters and return type. However, it could elaborate on pagination behavior (limit/offset) and default values, though defaults are null in schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, which it does thoroughly. Each parameter is explained with format details (e.g., YYYY-MM-DD, YYYYMMDDHhmm) and allowed values (e.g., 'macro', 'regional', 'all'), adding meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get recently updated FRED series,' which is a specific verb-resource combination. Among siblings like fred_series (get a specific series) and fred_series_search (search by criteria), this tool is uniquely about recently updated series.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives or provide exclusions. It implies usage for recent series updates but lacks guidance on 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits beyond basic functionality. It omits potential side effects, permissions, rate limits, or whether dates include future events.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with purpose, followed by a clear parameter list and return type. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters and no annotations or output schema, the description adequately covers purpose, all parameters, and return format ('dict with key release_dates'), making it complete for tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains each of the 7 parameters in the Args section, adding meaning beyond the schema which has no descriptions and only 0% coverage. This enables correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get release dates for a specific FRED release', using a specific verb and resource, and distinguishes from siblings like fred_release or fred_releases_dates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a release_id and need its dates, but provides no explicit guidance on when to use this tool versus alternatives like fred_releases_dates or fred_release.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the return format and the endpoint behavior, but does not explicitly state that the operation is read-only or any access requirements. Since no annotations are provided, it could have included more transparency about safety and idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a concise overview, followed by behavior explanation, a clear parameter list, and return type. Every sentence adds value, and the format is easy for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 12 parameters and two modes, the description covers all necessary information for correct invocation, including conditional behavior and return format. The presence of an output schema further justifies the minimal return description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 12 parameters are described with meaningful explanations, including format hints (dates as YYYY-MM-DD, semicolon-delimited lists) and inter-parameter dependencies (related_to overrides tag_names). This fully compensates for the 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves tags for a FRED release, with two distinct modes: getting all tags or using related_to for related tags. This distinguishes it from sibling tools like fred_tags that are not release-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use the related_to parameter versus tag_names, including that related_to overrides tag_names. However, it does not compare this tool directly to sibling tools like fred_related_tags, which might be a valid alternative for related tag queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It transparently discloses the data size issue for county-level shapes and specifies the return format (GeoJSON FeatureCollection). While it could mention rate limits or authorization, the given details are sufficient for safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise with three sentences plus arg/returns, front-loading the purpose and critical warning. No fluff or redundant information, every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 required param with enum, output schema present), the description covers all essential aspects: purpose, parameter meaning, performance warning, and return type. No gaps in understanding for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the shape parameter as 'Region type for shape boundaries', adding context beyond the enum values. Though not detailing each enum, the names are self-explanatory and the description provides minimal but adequate clarification, meeting the baseline for 0 params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get GeoJSON shape files for geographic region boundaries', using a specific verb and resource. It distinguishes itself from sibling tools by focusing solely on shape files for boundaries, which is unique among the fred and geofred tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance by warning that county-level shapes can be very large and advising to prefer state or broader region types when possible. However, it does not explicitly exclude alternative tools or specify when not to use this tool, leaving room for improvement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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