Mortgage Rates Today MCP

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description adds real value on top: the external Freddie Mac data dependency for defaults, the built-in year-over-year comparison, and the explicit exclusion of taxes, insurance and PMI. It does not mention latency or failure behavior if the external rate fetch fails, which keeps it from a 5.

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

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

Three tight sentences ordered output-first, then default behavior, then scope caveat. The opening sentence is slightly elliptical (no explicit verb) but nothing is wasted.

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

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

With no output schema, the description correctly states what is returned and what is excluded, and it explains the defaulting and comparison logic for the two optional rate parameters. An agent has enough to call it correctly without guessing at semantics.

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 100%, so the schema already documents rate and compare_rate defaults, term_years default of 30, and units for loan_amount. The description reinforces the default behavior and clarifies that the comparison is against the year-earlier average, but adds little beyond the structured 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 names the concrete outputs (monthly principal and interest, total interest) for a fixed-rate loan, which clearly distinguishes this from the rate-lookup siblings. The calculating verb is implied rather than stated, and no sibling is named explicitly, so it falls short of a 5.

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?

It usefully explains the default path: omit rate and it uses this week's Freddie Mac average, with an automatic year-earlier comparison. However, there is no explicit guidance on when to use this tool versus get_mortgage_rates_today or get_mortgage_rate_on_date, nor 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.

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

Annotations already cover readOnly, idempotent, non-destructive and open-world, so the safety bar is low; the description still adds real context by disclosing the upstream source (Freddie Mac PMMS), the return shapes, the derived high/low/change over the range, and the default window. It does not state units (rate in percent), whether weeks with no survey are omitted, or how the frequency default escalates past 3 years (that detail sits only in the schema).

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 sentences, no filler, with the core resource and output capability front-loaded and the default behavior placed last where it belongs. Every clause carries new 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?

With no output schema, the description must carry return-value burden, and it does: it names the row shapes and the aggregate fields. Minor gaps remain around units and handling of gaps or empty ranges for a 4-parameter, all-optional tool, but nothing an agent needs to invoke it correctly is missing.

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

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

Schema description coverage is 100%, so the baseline would be 3; the description earns the bump by tying start/end dates to the computed high, low and change over the range and by clarifying that the 30/15 term selects a fixed-rate product family and that frequency controls row size. It adds framing rather than syntax detail, which is appropriate given the schema documents formats and enums.

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?

Names a specific resource (Freddie Mac PMMS 30-year / 15-year fixed averages) and a specific operation (history between two dates), and immediately states the output shapes: weekly rows or monthly/annual averages with high, low and change. This scope cleanly separates it from the point-in-time siblings get_mortgage_rate_on_date and get_mortgage_rates_today without needing to name them.

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

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

The range-based framing plus the stated default ('last 52 weeks of the 30-year rate') makes it clear this is the tool for trends and aggregates rather than a single quote, which implicitly routes the agent away from the on-date and today siblings. It stops short of explicitly naming those alternatives or stating 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.

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld), so the description's job is to add context — and it does: it identifies the source series (Freddie Mac PMMS), the fact that these are weekly averages rather than daily quotes, the exact coverage window (1971-04-02 to today), and which rate products are included. It does not state how a mid-week date resolves to a weekly reading, which is the one behavioral detail still missing.

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

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

A single sentence that front-loads the resource and provenance, then the coverage window. The parenthetical about 5/1 ARM and points is the only compression, and it carries real information rather than filler.

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

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

For a one-parameter read tool with full annotation coverage and no output schema, the description covers source, products, and valid date range — enough to call it correctly. The remaining gap is edge-case behavior (dates outside the range, non-publication days) and any hint about the return shape, though the latter is a minor concern given the tool's simplicity.

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?

With one parameter at 100% schema coverage, the baseline is 3, and the description earns a bump by supplying the valid domain (1971-04-02 to today) that the schema's pattern alone does not constrain. The YYYY-MM-DD format itself is already in the schema and is not duplicated.

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?

Names a specific resource (Freddie Mac PMMS 30-year and 15-year fixed rates, plus 5/1 ARM and points), a specific scope ('in force on a date'), and the data provenance. It stops short of naming the sibling tools (get_mortgage_rates_today, get_mortgage_rate_history), so the differentiation is only implied by the singular 'on a date' phrasing.

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

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

Usage is implied rather than stated: a single required date plus 'in force on a date' signals point-in-time lookup, and the sibling names make the today/history alternatives guessable. There is no explicit 'use this instead of X when Y' routing, and no note about what happens for a non-publication day or a date before 1971-04-02.

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 cover readOnly/openWorld/idempotent/non-destructive, and the description adds meaningful context beyond them: data is fetched live from freddiemac.com at call time (network dependence and freshness), it is a weekly average rather than real-time quotes, and it applies only to well-qualified conventional purchase borrowers nationally. It does not discuss latency, caching, or failure behavior when the source is unreachable.

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

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

One dense but well-ordered sentence: source and scope first, then the enumerated return fields, then the borrower caveat. With no output schema, the field enumeration is load-bearing rather than redundant, and there is no filler.

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

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

Returns are well specified despite the absence of an output schema, and the source, cadence, and borrower scope are all stated. The only gap is coverage boundaries — it is not stated that other products (ARMs, FHA/VA, 30-year jumbo) or non-national geographies are out of scope, which an agent might otherwise assume.

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

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

The tool takes no parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The closing scope note correctly sets expectations that this is a national average rather than a quote for a specific borrower or state.

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

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

The description names a specific data source (Freddie Mac PMMS), specific resources (30-year and 15-year fixed mortgage rates), and a temporal scope ('latest ... today', 'read at call time') that separates it from get_mortgage_rate_history and get_mortgage_rate_on_date. An agent can tell exactly what this returns without opening a schema.

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

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

Usage is only implied: the 'latest ... today' framing and 'next expected release' hint at a current-rates use case, but the description never states when to prefer this over the sibling history or on-date tools, nor any exclusions. The routing must be inferred from the temporal framing alone.

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