Monarch Money MCP Server

by jamiew

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.4.0
Disambiguation4/5
Most tools have clearly distinct purposes, but there is some overlap among spending analysis tools (analyze_spending_patterns, get_spending_summary, get_cashflow, get_complete_financial_overview). While descriptions differentiate them, an agent might still struggle to choose the right one without careful reading.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with lowercase and underscores (e.g., analyze_spending_patterns, create_transaction, get_accounts, update_transaction_splits). No mixed conventions or unexpected styles.
Tool Count4/5
21 tools is slightly above the typical range, but each serves a distinct purpose in the personal finance domain. The count feels justified given the breadth of features (accounts, transactions, budgets, categories, analysis).
Completeness4/5
The tool surface covers most core personal finance operations: account management, transactions with CRUD and splits, budgets, categories, and various analyses. Missing are deletion endpoints (e.g., delete account/transaction) and investment transaction details, but these are not essential for common workflows.
Average 3.8/5 across 21 of 21 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 7 commits in the last 12 weeks
- Last stable release on June 30, 2026
- 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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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?
The description adds 'historical' context beyond annotations, but fails to disclose other behaviors such as pagination, time range constraints, or rate limits. Annotations already declare readOnlyHint true, so safety is covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. No front-loading of key details beyond the basic purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters and an output schema, the description is insufficient. It does not explain return values or parameter behavior, leaving significant gaps for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage and the tool description does not explain any parameter semantics (e.g., date formats, meaning of account_id). All three parameters are left undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves historical account balance data, using a specific verb and resource. It distinguishes from sibling tools like get_accounts (current balances) by specifying 'historical'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like get_accounts or get_transactions. The description does not mention prerequisites or exclusions.
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 aligns with annotations (not read-only, not destructive), but adds no additional behavioral details such as duplication handling or side effects. Annotations already indicate basic safety profile, but description does not enrich beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short and front-loaded, making it quickly readable. However, it sacrifices essential details for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 3 required parameters and a presumably existing output schema, the description provides no context about side effects, constraints, or return values. It is insufficient for an agent to use correctly without extra inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fails to add any meaning to the three required parameters. No parameter details or examples are provided, leaving the agent with only field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and resource ('manually tracked account'), making the purpose immediately understandable. It distinguishes from sibling tools as it is the only creation tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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, nor any prerequisites or context. It simply states the action without explaining scenarios.
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?
The description does not disclose that this is likely a network-triggering, potentially slow, and rate-limited operation. Annotations are all false, so no safety hints are conveyed beyond the description, which 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose without extraneous words. It is front-loaded and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and an output schema, the description is minimally adequate. However, it lacks context about side effects, expected duration, or when results are available, which is needed given the imperative nature of 'refresh'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage, the schema fully documents the absence of parameters. The description adds no parameter information, meeting the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'refresh' and the resource 'account data from financial institutions', indicating it triggers a data sync. It distinguishes from sibling tools like 'get_accounts' which likely retrieve cached data without initiating a refresh.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like 'get_accounts' or 'create_manual_account'. The description does not mention prerequisites, timing, or whether it should be called sparingly.
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?
Annotations already declare readOnlyHint=true, so the agent knows it is safe. The description adds value by detailing that the tool 'combines multiple data sources' and produces forecasts, budget analysis, and account usage patterns, which are not implied by the annotation alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and uses bullet points for clarity. However, the 'Args' section is redundant with the schema and could be removed to reduce length. Every sentence serves a purpose, but the structure is not maximally tight.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to detail return values. It covers the key analytical aspects (trends, forecasts, budget performance, account usage). No critical gaps are apparent for a read-only analytical tool, though it could mention any limits on data scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 restates the parameter names and defaults (already in schema) but adds little additional meaning. For example, it says include_forecasting is 'whether to include spending forecasts', adding no nuance beyond the parameter name. The description does not explain valid ranges, formats, or effects.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'intelligent spending pattern analysis with trend forecasting' and lists specific insights (monthly trends, account usage, budget performance, forecasts). This distinguishes it from simpler siblings like get_spending_summary, though it could be more explicit about its comparative advantage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 get_spending_summary or get_cashflow. It lacks explicit when-to-use, when-not-to-use, or alternative recommendations, leaving the agent to infer context.
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?
Annotations already provide readOnlyHint=true, so the description adds some value by mentioning natural language date support and aggregation grouping. However, it does not elaborate on aggregation details, performance, or data scope, which would further enhance transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences and a bullet list for parameters. Every element adds value, though the bullet list could be integrated more tightly into the main text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present (though not shown), the description need not detail return values. However, it does not specify what aggregations are computed (e.g., total spending, averages) or include any caveats, leaving some gaps for a tool with three parameters and no required inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description compensates by explaining that start_date and end_date support natural language and that group_by accepts 'category', 'account', or 'month'. This adds significant meaning beyond the bare schema types, though it could mention defaults and optionality.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets an intelligent spending summary with aggregations, specifying the verb and resource. However, it does not distinguish this tool from siblings like analyze_spending_patterns or get_cashflow, which may also provide spending summaries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. The description only explains what the tool does, not when it should be chosen over siblings like get_complete_financial_overview or analyze_spending_patterns.
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?
Annotations provide readOnlyHint=true. Description adds that it returns a JSON string and supports natural language dates, which is useful context. However, it doesn't disclose pagination, limits, or default behavior beyond basic retrieval.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Relatively concise but includes an 'Args' section that partially duplicates schema information. The natural language hint is valuable. Could be more front-loaded without the structured list.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and the tool is simple (2 optional params), the description is adequate but lacks defaults, ordering, and scope (e.g., returns all budgets or only filtered?). Missing context on what happens with no dates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description carries the full burden. It explains both parameters (start_date, end_date) with purpose and natural language support, significantly adding meaning beyond the schema's minimal type info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retrieve budget information with flexible date filtering', specifying the action (retrieve), resource (budgets), and distinctive feature (date filtering). It stands out from siblings like 'set_budget_amount' (write) and 'analyze_spending_patterns' (analysis).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs. other budget-related tools like 'set_budget_amount' or 'analyze_spending_patterns'. No when-not-to-use or alternative recommendations.
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?
Annotations already declare readOnlyHint=true, so the description adds no extra value. It is not contradictory.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at 4 words, front-loaded, and no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema and no parameters, the description is adequate; could hint at usage context but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; baseline of 4 for zero-parameter tools applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves scheduled recurring transactions, distinguishing it from sibling tools like get_transactions which likely retrieves all transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like get_transactions or get_spending_summary.
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?
Annotations already indicate idempotentHint=true and destructiveHint=false, so the description's claim of setting an amount is consistent. However, the description adds no further behavioral context (e.g., whether it overwrites or adjusts existing budgets, permission requirements, or side effects), relying entirely on annotations for transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core action efficiently. However, it is overly brief and could afford to include parameter hints without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with an output schema, the description is adequate but lacks parameter semantics and usage context. It does not explain how the amount is interpreted (e.g., currency, decimal places), which is necessary for correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does 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 beyond their names. The agent receives no guidance on valid values, formatting, or meaning of 'category_id' and 'amount'. This is a significant gap for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Set budget amount for a category.' uses a specific verb ('set') and clearly identifies the resource ('budget amount') and scope ('for a category'), effectively differentiating from sibling tools like 'get_budgets' and 'analyze_spending_patterns' which are read or analysis operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for setting budget amounts, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The context from sibling tools provides some differentiation, but the description itself offers no usage guidance.
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?
Annotations already declare readOnlyHint=true and openWorldHint=false, covering the safety profile. The description adds that the tool returns portfolio holdings, which is consistent but does not disclose additional behavioral traits such as data freshness, pagination, or required permissions. The low burden from annotations keeps this at a 3.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using two short sentences plus an 'Args' block. It front-loads the key purpose and immediately clarifies the parameter. Every sentence earns its place with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, read-only operation, output schema present), the description is nearly complete. It explains the parameter meaning and purpose. The presence of an output schema means return details are handled elsewhere, so the description does not need to elaborate. Minor improvement could mention that holdings are for investments, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 0% description coverage, placing the full burden on the description. The description explains that 'account_id' is the ID of the investment/brokerage account, which adds meaning beyond the raw schema. For a single parameter, this is sufficient, though more detail on format or validation would improve it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves investment portfolio data (holdings) for a brokerage account, using a specific verb ('get') and resource ('holdings'). It distinguishes itself from siblings like 'get_account_history' or 'get_accounts' by specifying 'holdings' and 'brokerage account', leaving no ambiguity about its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 what cases it is suitable for, nor does it exclude any scenarios. Given the many sibling tools (e.g., get_account_history, get_accounts), the agent needs explicit direction to select correctly.
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?
Annotations already declare readOnlyHint=true, so the description's 'Retrieve' aligns. No additional behavioral details (e.g., what 'linked' means) are added beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence of 5 words, front-loading the action and resource with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, clear annotations, and an existing output schema, the description is adequate for a straightforward list tool, though it could mention response scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. The description adds no parameter info, but none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and the resource 'all linked financial accounts', distinguishing it from siblings like get_account_history or get_account_holdings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not specify when to use this tool versus alternatives, nor does it mention any context or exclusions.
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?
Annotations already indicate readOnlyHint=true and openWorldHint=false, so safety is clear. The description adds that it combines multiple API calls and reduces round-trips, but the term 'deeper insights' is vague. No additional behavioral traits beyond annotations are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with the core purpose in the first sentence. The second sentence adds moderate value but contains marketing language ('intelligent batch tool', 'deeper insights') that could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, the description does not need to detail return values. It sufficiently explains the tool's scope and the single parameter. However, it lacks mention of any prerequisites or limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description bears full responsibility for explaining the single parameter. It provides examples of valid period values ('this month', 'last month', etc.), adding meaning beyond the schema's basic definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to get a complete financial overview including accounts, transactions, budgets, and cashflow. It distinguishes itself from sibling tools by highlighting its batching capability, using specific verbs and resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining comprehensive data in one call, but lacks explicit guidance on when not to use it or alternatives. Given many sibling tools exist for individual data, it would benefit from specifying trade-offs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description details pagination, date auto-defaults, natural language date support, verbose vs compact output modes, and internal parameter handling (e.g., converting account_id to list). This fully discloses 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with headings but is very long, containing a large reference section on transaction fields that could be streamlined. While detailed, it sacrifices conciseness, especially for a tool with 13 parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity and the absence of an output schema (only indicated as present), the description covers parameters, output fields, and examples thoroughly. It omits error handling and edge cases (e.g., exceeding limit max), but overall provides a comprehensive picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates extensively by explaining each parameter's purpose, default values, data types, and special behaviors (e.g., 'converted to list internally', 'auto-default to today'). It even includes common filter examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch transactions with flexible date filtering and smart output formatting,' specifying the verb and resource. It distinguishes from siblings by focusing on filtering and output formatting, but does not explicitly differentiate from 'search_transactions' or other related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides filtering examples but no explicit guidance on when to use this tool versus alternatives like 'search_transactions' or 'get_complete_financial_overview'. It lacks when-not-to-use scenarios or tool selection criteria.
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?
Annotations already declare readOnlyHint=true, so the description adds no additional behavioral context beyond the date filtering flexibility. It does not contradict annotations and adds minimal extra information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the main purpose, and uses a clear Args structure. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional params), the presence of annotations (readOnlyHint) and an output schema, the description adequately covers the return format (JSON string) and usage context. No significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides meaningful semantics for both parameters including natural language support examples (e.g., 'last month', 'this year'). This compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Analyze cashflow data with flexible date filtering', which uses a specific verb and resource. This distinguishes it from sibling tools like get_transactions or analyze_spending_patterns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for cashflow analysis with date filtering but does not explicitly state when to use vs alternatives or when not to use. It provides clear context but no exclusions.
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?
Annotations already provide readOnlyHint: true, so the description adds no additional behavioral context. However, the description is consistent and does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One short, front-loaded sentence with no extraneous information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless list tool with an output schema, the description is complete enough. It tells the agent exactly what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so the description does not need to detail them. The schema coverage is 100%, meeting the baseline without additional description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get linked financial institutions' uses a specific verb ('Get') and resource ('linked financial institutions'), clearly distinguishing it from sibling tools that focus on accounts, transactions, or budgets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does 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. While the purpose is clear, the description lacks context about prerequisites 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=false. The description adds behavioral context: it returns the current split legs, and for un-split transactions, 'splits' is empty. This goes beyond the annotations by clarifying the return shape in edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear statement of purpose, an example, and separate Args/Returns sections. It is slightly verbose but every sentence adds value. Could be trimmed slightly, but overall effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, read-only, output schema exists), the description is complete. It explains the concept, the single parameter, and the return structure including the empty case. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage for the parameter, but the description explicitly documents 'transaction_id: ID of the transaction to inspect'. This compensates for the schema gap by adding meaning to the single required parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the split legs of a transaction.' It explains what splitting is with a concrete example ('Target run that is part groceries, part household'), making the intent unmistakable. It also contrasts with sibling tools like 'update_transaction_splits' by focusing on retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but does not explicitly state when to use it versus alternatives. It implies usage when you need to inspect existing splits, but there is no mention of when not to use it or which sibling tools (e.g., update_transaction_splits) are appropriate for modifications.
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?
Annotations declare readOnlyHint=false, so the agent knows this is a write operation. The description adds value by explaining the update_balance parameter's effects, confirming it mutates account balance when true. It also mentions the return format (JSON string). However, it does not explicitly state that the operation is not idempotent, which matches the idempotentHint=false annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening line and bullet-style parameter explanations. Every sentence adds value, though the update_balance explanation could be slightly condensed without losing meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters and an output schema (declared), the description covers the creation action, all parameter meanings, return type, and a key behavioral option (update_balance). Missing aspects include validation or error scenarios (e.g., invalid account_id), but the description is still fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does 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's meaning, format, and constraints. For example, amount is described as 'positive for income, negative for expense', date as 'YYYY-MM-DD', and update_balance with use cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Create a new manual transaction,' which is a specific verb-resource combination. This clearly distinguishes it from sibling tools like update_transaction or get_transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides contextual guidance on when to set update_balance to True vs False based on account type (synced vs manual). However, it does not explicitly tell the agent when to use this tool over other transaction-related tools, such as syncing or importing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond annotations: clarifies that empty strings are ignored for merchant_name, notes can be cleared with empty string, and lists read-only fields (plaidName, account, etc.). It details side effects and constraints, which is critical since annotations only provide high-level hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections (Args, Field Editability, Returns, Common Use Cases) and bullet points. Every sentence adds value, and the key information is front-loaded. Despite length, it remains organized and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no schema descriptions, output schema present), the description covers all necessary aspects: parameter behaviors, edge cases, read-only fields, and example use cases. It is complete and leaves no ambiguity for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by providing detailed explanations for each parameter, including examples, field differences (notes vs. merchant_name), and behavioral notes (e.g., empty string behavior). This adds substantial meaning beyond the schema's type definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Update an existing transaction' and lists all updatable fields. However, it does not explicitly differentiate from sibling tools like 'update_transactions_bulk' or 'create_transaction', which could cause ambiguity for an agent deciding which tool to use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides common use cases and field editability details, but does not give explicit guidance on when to use this tool versus alternatives (e.g., create_transaction for new transactions, update_transactions_bulk for batch updates). The usage context is implied but not contrasted.
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?
Annotations already declare readOnlyHint=true, confirming a safe read operation. The description adds behavioral context by detailing the two output formats (compact vs. full) and their use cases, going beyond the annotation's minimal information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear Args/Returns structure. Every sentence adds value, no fluff. It is appropriately front-loaded with the core purpose, and the parameter details are well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with an output schema, the description covers the essential behavior and parameter semantics. It does not mention if categories are filterable or how they relate to transactions, but these are not critical given the tool's narrow scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates by exhaustively explaining the single 'verbose' parameter: its default, both output modes, their structure, and when to use each. This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'List all transaction categories.' This is a clear verb+resource combination. It distinguishes itself from sibling tools (e.g., get_transactions, get_budgets) by focusing specifically on categories, which no other tool covers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance for the verbose parameter, explaining when to use each mode (e.g., compact mode for lookups, full mode for details). However, it does not include explicit when-to-use or when-not-to-use context relative to alternatives, though the tool's uniqueness makes this less critical.
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?
Annotations indicate readOnlyHint=true, consistent with the search operation. The description adds behavioral details: 'Returns compact results by default (use verbose=True for full details).' No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening sentence, followed by details and an Args section. While moderately long, every part adds value; could be slightly more concise but effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 14 parameters, zero schema description coverage, and an output schema, the description covers all parameter semantics, return format ('JSON with search_metadata and matching transactions'), and default behaviors. Completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description provides extensive parameter explanations: lists all 14 parameters, explains 'query' as search term, describes 'verbose' behavior, and notes natural language support for dates ('last month'). This adds significant value beyond bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search transactions by text using Monarch Money's built-in search.' It lists fields searched (merchant names, descriptions, notes) and distinguishes itself from get_transactions by noting it accepts the same filters plus a search query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating it accepts all get_transactions filters plus a search query, suggesting use when text search is needed. However, it does not explicitly state when not to use or name alternatives beyond get_transactions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare idempotentHint=true and destructiveHint=false, and the description adds rich behavioral context: full replacement behavior, amount summing constraint, sign convention, default merchant, and return structure. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening, bullet-style argument list, example, and return info. It is appropriately sized for the complexity; each sentence adds value. Slightly verbose but not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two parameters, no nested objects, and an output schema, the description covers purpose, behavior, parameter details, constraints, example, and return values. Nothing essential is missing for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully documents both parameters: transaction_id (required) and splits (complete set with amount required, sign convention, optional fields). An example clarifies usage. This compensates fully for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates, replaces, or removes splits on a transaction. It specifies the verb (create/replace/remove) and resource (splits). However, it does not explicitly differentiate from sibling tools like update_transaction or get_transaction_splits, though the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (to replace splits or remove them with an empty list) and provides detailed argument semantics. It lacks explicit when-not-to-use guidance or alternatives (e.g., use get_transaction_splits to read), but the sibling list gives context.
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?
Beyond annotations (idempotentHint=true, etc.), it discloses parallel execution and return format (JSON with results per transaction). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with sections, front-loaded purpose, no fluff. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, the description succinctly covers the return value. All relevant aspects are addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the description fully explains the JSON structure, required/optional fields, types, format, and provides an example.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Update multiple transactions in a single call' and contrasts with the sibling tool update_transaction, distinguishing it effectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly notes efficiency over calling update_transaction multiple times, implying when to use it. Lacks explicit when-not-to-use, but context is clear.
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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