fred-treasury-macro-data-mcp

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

Annotations already declare readOnlyHint=true. Description adds detail on returned fields and parameter behavior (e.g., 'recent' as a special value, security_type options). Does not mention potential side effects or rate limits, but read-only nature reduces need.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is very concise: one-line summary followed by a numbered list of parameters. No unnecessary words, front-loaded with key information.

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

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

For a read-only data retrieval tool with 4 optional parameters and no output schema, the description covers purpose, parameters, and output fields. No obvious gaps given the tool's simplicity and annotations.

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

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

Input schema has 0% description coverage (no property descriptions). The description compensates fully by explaining each parameter: auction_id_or_recent can be 'recent' or CUSIP, security_type lists valid strings, days_back and limit with defaults and meanings.

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

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

Description clearly states the tool returns 'Treasury auction results' with specific metrics (stop-out yield, bid-to-cover ratio, etc.). It distinguishes from siblings like get_upcoming_treasury_auctions (future auctions) and get_treasury_yield_curve (yield curve) by focusing on historical results with specific fields.

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

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

Description provides context on when to use: for historical auction results, and mentions 'recent' for latest auctions. Does not explicitly exclude other tools, but the specific output fields and parameter options imply appropriate use cases.

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

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

Annotations already declare readOnlyHint and openWorldHint. The description adds context: parameter defaults and examples. No contradictions. It could mention rate limits or error handling but is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with a clear purpose, followed by an Args section that lists parameters succinctly. Every sentence adds value with no waste.

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

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

For a simple data retrieval tool, the description covers parameter semantics and usage. It does not describe return format, but that is acceptable given no output schema. Slight gap in completeness but overall strong.

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

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

Schema coverage is 0%, but the description fully compensates by explaining series_id with 9 examples, start_date and end_date with formats and defaults. This adds critical meaning beyond the schema.

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

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

The description explicitly states 'Fetch a FRED economic data series' with a clear verb and specific resource, followed by concrete examples (CPI, GDP, etc.). It effectively distinguishes from sibling tools which are about auctions and treasury.

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

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

The description implies when to use (for any FRED series) through examples and defaults, but lacks explicit 'when-not-to-use' or alternatives. Given distinct siblings, it's clear, but not exhaustive.

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

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

Annotations already provide readOnlyHint=true, indicating no side effects. The description adds value by enumerating the exact data returned (list of economic indicators), which goes beyond the annotation. No contradictory behavior is mentioned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: first states the tool's essence, second lists return data, third explains design intent. It is front-loaded and every sentence adds value without redundancy.

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

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

Given no parameters and no output schema, the description completely specifies what the tool returns with a clear list. It distinguishes from siblings, and the context is sufficient for an agent to decide to use it. Annotations cover safety.

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

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

There are no parameters, and schema coverage is 100% (trivial). The description does not need to add parameter semantics but provides context on the tool's purpose, which is sufficient. Baseline for 0 params is 4.

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

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

The description clearly states the tool returns a combined macro snapshot including specific data points (10Y yield, yield curve, CPI, unemployment, fed funds rate, auction results). It distinguishes itself from siblings by being a 'one-call combined' tool, with siblings focusing on individual data sources like auction results or FRED series.

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

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

The description explicitly states the tool is 'designed so an LLM can answer what's the macro picture right now?' with one call, implying usage context. However, it does not explicitly state when not to use it or name alternatives, though sibling tools are implied for specific data needs.

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

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

Annotations indicate readOnlyHint and openWorldHint. The description adds context about the data being a 'par yield curve' for specific maturities and explains default date behavior. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence followed by an Args block, with no wasted words. Purpose is front-loaded.

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

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

The tool has no output schema, but the description lists maturities, implying the return will include those points. It could mention the return format (yields), but the name 'yield curve' makes it reasonably clear.

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

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

The schema provides no description for the 'date' parameter (0% coverage). The description explains it expects ISO date format and defaults to the most recent business day, adding critical meaning.

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

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

The description explicitly states 'Full US Treasury par yield curve' and lists all maturities. It clearly distinguishes from siblings which cover auctions, FRED series, macro dashboard, and upcoming auctions.

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

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

The description implies usage for yield curve data but does not explicitly state when to use or not use sibling tools. However, siblings are sufficiently different in domain, making implicit differentiation adequate.

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

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

Annotations already provide readOnlyHint=true and openWorldHint=true, which cover the safety profile. The description adds parameter details but no additional behavioral traits like caching or pagination. Since annotations carry the burden, a 3 is appropriate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two clear sentences plus a parameter list. No wasted words. The main purpose is front-loaded.

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

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

Given no output schema, the description could mention what the returned data contains (e.g., dates, details). But for a simple calendar tool, parameter info is sufficient. Completeness is adequate but not exceptional.

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

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

Schema description coverage is 0%, so the description must compensate. It lists allowed values for security_type and specifies default and max for days_ahead, adding meaning beyond the schema's type and default fields.

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

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

The description clearly states it retrieves an auction calendar of upcoming treasury securities, with specific parameters. The title in annotations further clarifies. Sibling tools are distinct (auction results, yield curve, etc.), so no confusion.

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

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

The description implies usage for viewing upcoming auctions, but lacks explicit when-to-use or when-not-to-use guidance. However, sibling tool names are sufficiently different to indicate context.

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