finance-agent

Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct resource and action: fetching data, summarizing cashflow, and managing goals, notes, rules, and nicknames are all clearly separated. No two tools appear to overlap in purpose, and the list/add/upsert/get pairs are well delineated.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern (e.g., list_goals, add_plan_note, get_balances). The verbs vary (list, get, add, upsert, summarize, setup) but the pattern is uniform and predictable, with no mixed casing or style deviations.
Tool Count5/5
With 15 tools, the server is well-scoped for a finance planning assistant. Each tool contributes to either data retrieval or memory management, and no redundant or unnecessary tools are present. The count falls comfortably within the ideal 3-15 range.
Completeness3/5
The set covers reading live financial data, summarizing cashflow, and managing goals, notes, rules, and nicknames, but lacks any delete/remove operations for these mutable resources. Users can add or update but not delete plan notes, category rules, or goals, creating potential dead ends and making the lifecycle incomplete.
Average 3.7/5 across 15 of 15 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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{
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  "maintainers": [
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  ]
}
```
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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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'create or update' without detailing that an existing id would trigger an update, what fields are overwritten, whether any side effects occur, or any error conditions. No behavioral traits beyond the bare operation 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 a single concise sentence with no unnecessary words, front-loading the purpose effectively. However, it is so brief that it leans toward under-specification rather than refined conciseness, losing a point for not including any structural cues or supplementary context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an upsert tool with 7 parameters, no annotations, and no output schema, this description is severely incomplete. It omits how existence is determined, what happens to optional fields like notes or due_date, the format of the response, and any constraints on values. The minimal description is inadequate for the tool's complexity.
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?
Schema description coverage is 0%, meaning the description adds no meaning to any of the 7 parameters. It does not mention id, title, status, amounts, due_date, notes, or any parameter-specific semantics. The description fails to compensate for the lack of schema-covered parameter details.
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's function: 'Create or update a financial goal' with examples like debt payoff and savings targets. This is a specific verb+resource combination that effectively conveys the core purpose, though it does not explicitly differentiate from sibling tools or mention the upsert semantics beyond the phrase 'create or update'.
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 list_goals. It does not state prerequisites, when to choose create vs update, or when to prefer a different tool. The only implied usage is that you'd use it to manage goals, but no explicit or contextual guidance is given.
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 command but does not disclose whether this is a safe read operation, any authentication requirements, rate limits, or return behavior. 'Fetch' implies read-only but not explicitly stated.
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 concise sentence that front-loads the action. No unnecessary words.
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 parameterless fetch tool, the description is minimal but sufficient to understand the action. However, it lacks usage guidance and does not mention any prerequisites or side effects, making it less complete than ideal for a production tool.
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 zero parameters, so the baseline is 4. The description adds context by noting the command includes '--all', indicating it retrieves all holdings without filtering. This clarifies there are no parameters to set.
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 'Fetch investment holdings' which is a specific verb+resource, and it names the underlying plaid command. It is distinct from sibling tools like get_balances and get_transactions, whose purposes are different.
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. It simply describes the command without specifying context, exclusions, or alternative tools.
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 of behavioral disclosure. It only says 'save', which indicates a write operation but does not clarify whether this creates, updates, or overwrites an existing nickname. It also does not disclose return values, error conditions, or idempotency, leaving the agent without critical behavioral expectations.
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 is direct and to the point. It includes a helpful example without any extraneous content. Every word earns its place.
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 the tool has four parameters, no output schema, and no annotations, the description is incomplete. It lacks information about return values, the upsert semantics (create vs. update), and the purpose of optional parameters. The agent cannot fully anticipate the tool's behavior from this description alone.
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?
The description explains account_id and gives examples for nickname, but it does not mention the optional 'notes' or 'institution_hint' parameters at all. With schema description coverage at 0%, the description must compensate for all parameters, and it fails to do so for half of them. This leaves the agent unsure of their purpose.
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 action ('Save a nickname') and target ('account_id'), with concrete examples ('Chase checking', 'Amex BCE'). This distinguishes it from the sibling tool 'list_account_nicknames', which is for reading nicknames, not saving them.
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 when to use this tool – when needing to assign or update a nickname for an account. It does not explicitly mention the 'upsert' behavior or contrast with listing, but the purpose is clear enough to infer the appropriate context. No exclusions or alternatives are stated, but the context is straightforward.
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 carries the full burden of behavioral disclosure. It only states that it saves a note, without mentioning whether it overwrites existing notes, appends, requires auth, or has any side effects. The phrase 'so future chats keep context' gives a purpose but no operational 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 front-loads the action and resource, followed by a concise purpose. Every word earns its place, with no filler or repetition.
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?
The tool is simple with only two parameters, but the description lacks behavioral transparency (e.g., overwrite behavior) and does not mention return values, which would be expected given no output schema. It is minimally viable but has clear gaps.
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 50% (month is described, content is not). The description does not clarify the content parameter or add format/meaning beyond what the schema already provides. It implicitly references month but adds no semantics for content.
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 action (Save), the resource (planning note), and the scope (for a month), making it easy to distinguish from sibling tools like list_plan_notes. The purpose clause 'so future chats keep context' further clarifies its intent.
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 when to use the tool (to persist planning context across chats), but it does not explicitly mention alternatives or when not to use it. The context is clear but exclusions are absent.
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 must disclose behavioral traits, but it only says 'Fetch transactions', which implies a read operation. It does not mention output format, pagination, potential performance impacts, or any side effects, leaving the agent underinformed about what to expect.
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 sentence with no filler, front-loaded with the action and scope. It is concise and immediately conveys the tool's purpose without unnecessary details.
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?
No output schema and sparse annotations put the burden on the description to explain what the tool returns, but it says nothing about return structure, ordering, or behavior. Given the tool has 4 parameters and represents a data-fetching operation, the description is too thin to be fully actionable.
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?
Schema descriptions cover 75% of parameters (item_id, start_date, end_date) with format and default info. The description's 'date range' and 'across all linked Items' reinforce but do not add beyond the schema; the 'count' parameter remains undocumented in both schema and description, so the added value is minimal.
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?
Description clearly states the action (Fetch), resource (transactions), and scope (date range, all linked Items), which distinguishes it from sibling tools like get_balances, get_liabilities, and get_investments. The inclusion of 'via Plaid CLI' and 'across all linked Items' adds specificity without ambiguity.
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 clear context on when to use this tool: when you need transactions within a date range across all linked items. It stops short of naming alternatives or explicit when-not-to-use advice, but the context is unambiguous enough for an agent to select it appropriately.
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?
With no annotations, the description carries full burden. It discloses the core matching logic and the assignment action. However, it does not state whether the rule applies retroactively to existing transactions, whether duplicate rules are allowed, or if there are any side effects beyond future categorization, leaving some opacity.
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 one concise sentence, front-loaded with the action and includes the essential condition. No wasted words or redundancy.
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 2-parameter tool, the description covers purpose and rule behavior sufficiently, but it omits potential edge cases like rule conflicts, retroactivity, and output/confirmation. The absence of annotations and output schema requires more context than provided.
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?
Schema coverage is 0%, so the description must compensate. It explains the role of match_text (substring to match) and category (value to assign), which adds relational meaning beyond parameter names. However, it lacks format examples, case sensitivity, or validation rules.
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 action (Add a categorization rule) with a specific condition-action logic: if merchant/name contains match_text, assign category. This defines the exact resource and behavior, distinguishing it from sibling list_category_rules.
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 context (adding a rule when you want transactions with a certain merchant/name substring categorized), but it does not explicitly mention alternatives or when not to use it. It provides the rule's triggering condition, but no guidance about updating or removing rules or comparing with listing tools.
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 must disclose behavioral traits. It only states 'Fetch', implying a read-only operation, but does not explicitly confirm safety, mention authentication/consent requirements, or describe any side effects or limitations. The reference to the Plaid command adds implementation context but not behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no redundant words. The verb is front-loaded and the description is easily scannable.
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?
The description adequately conveys the tool's purpose for a simple read operation, but lacks detail about the returned liability details, any pagination or limits, or how it differs from related tools. Given no output schema, a bit more detail would improve completeness.
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 schema has zero parameters, so the baseline is 4. The description adds no parameter-specific semantics, but the tool requires no input, and the mention of `--all` suggests it retrieves all liabilities by default, which aligns with the empty 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 uses a specific verb 'Fetch' and a clear resource 'credit/loan liability details', distinguishing it from sibling tools like get_balances or get_transactions. The phrase 'via `plaid liabilities --all`' reinforces the scope.
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. The description only states what it does, leaving the agent to infer usage from the tool name. There is no mention of exclusions or alternative tools.
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 burden. The verb 'list' implies a read-only operation, and 'saved...across chats' indicates persistent storage. However, it does not explicitly state side-effect free behavior or reveal return format/ordering. It adds some context beyond the tool name but lacks explicit safety confirmation.
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 is concise and front-loaded. It contains no unnecessary words and effectively communicates the tool's purpose.
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 one optional parameter and no output schema, the description covers the essential purpose and persistence nuance. It is complete enough for an agent to understand when to use it, though it could mention the optional filtering behavior or return value, but that is not essential given the schema coverage.
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?
The input schema has 100% coverage for the lone 'status' parameter, which is described as an optional filter. The tool description does not mention the parameter, but the schema already documents it adequately. Baseline 3 is appropriate as the description adds no extra 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 clearly states the tool lists saved financial goals, with a specific verb ('List') and resource ('saved financial goals'). The phrase 'the agent should remember across chats' adds important context distinguishing it from simple listing by indicating persistence/memory. It differentiates from sibling tools like 'upsert_goal' (which creates/updates) and 'list_plan_notes' (which lists notes).
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 context: use when the agent needs to recall financial goals that should persist across conversations. However, there is no explicit when-to-use or when-not-to-use guidance, nor mention of alternatives. The context is clear but not elaborated.
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 for behavioral disclosure. It does not mention whether the operation is read-only, what response format is returned, or how edge cases (e.g., no nicknames exist) are handled. The word 'List' implies a read, but this is not explicitly stated.
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, clean sentence that front-loads the action ('List') and the object ('human-friendly nicknames'). There is no filler or redundant information, making it highly efficient.
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 tool has no parameters and no output schema, the description should ideally explain the return shape. The description indicates it lists nicknames but does not specify whether it returns an array of nicknames, a mapping from account_ids to nicknames, or what happens when no nicknames exist. This is a moderate gap for an otherwise simple tool.
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 zero parameters, and the schema coverage is 100% (empty object). The description adds no parameter-specific information, but none is needed; the baseline for zero parameters is 4, and the description clarifies what the tool lists without referencing parameters.
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 uses the specific verb 'List' and identifies the resource as 'human-friendly nicknames for Plaid account_ids,' making the tool's function immediately clear. This also distinguishes it from the sibling tool 'upsert_account_nickname', which handles creating/updating nicknames rather than reading them.
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 the tool is for retrieving nicknames, and the presence of sibling tools like 'upsert_account_nickname' suggests when to use this read operation versus a write operation. However, there is no explicit 'when to use' or 'when not to use' statement, so it falls short of a 5.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the core behavior (listing notes) and adds context ('saved from prior conversations'), but does not mention the optionality of the month parameter, result ordering, or possible side effects. For a read-only list operation, this is basic but not comprehensive.
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, front-loaded sentence with no unnecessary words. It is concise, direct, and immediately conveys the tool's purpose.
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?
The tool has one optional parameter and no output schema. The description explains the overall function but does not clarify how the month parameter affects results or what content is returned in each note. For a simple tool, this is adequate but has gaps that require inference from the schema.
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?
The schema fully describes the single 'month' parameter with format 'YYYY-MM' (100% coverage). The description adds no additional meaning beyond the schema, so the baseline score of 3 is appropriate.
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 uses a specific verb 'List' with a clear resource ('monthly planning notes') and source ('saved from prior conversations'). It clearly distinguishes itself from sibling tools like 'add_plan_note', which performs the opposite action.
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 a retrieval use case for notes persisted from previous conversations. It does not explicitly name alternatives or exclusions, but the context is clear enough for a simple list tool, and the sibling relationship to 'add_plan_note' provides implicit 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?
With no annotations, the description must carry the full transparency burden. 'Explain' clearly indicates a non-mutating, informational tool, but it does not disclose the output format (e.g., text, structured data) or any side effects. For such a simple tool, the behavioral disclosure is minimal but 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?
The description is a single, concise sentence that is front-loaded with the verb and subject, containing no unnecessary words or filler. It perfectly matches the conciseness ideal.
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 zero-parameter, no-output-schema help tool, the description is nearly complete. It names the two components being explained and the relationship. It could add a note about its intended audience or whether it includes setup steps, but given the simplicity, it covers the essential aspects.
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 zero parameters, so the schema is empty and there is nothing to explain in the description. Per rubric, 0 parameters baseline is 4, and no further info 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 tool's purpose with a specific verb ('Explain') and a well-defined subject (how banking and planning memory work together). It distinguishes itself from all sibling tools, which are data-focused operations, while this is an educational/explanation tool.
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 when the agent or user needs to understand the integration between Plaid CLI and this MCP, but it does not explicitly say 'use this when' or mention any exclusions or alternatives. Since there are no sibling tools with similar purpose, the guidance is implicit but not fully explicit.
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?
With no annotations, the description is the only source of behavioral disclosure. It adds useful context about using 'Plaid CLI data + local category rules', but it does not explicitly state that the operation is read-only, mention prerequisites beyond local rules, or describe edge cases like missing data.
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 two-sentence description is concise and front-loaded: the first sentence states the core function and data sources, the second provides a use case. No redundant phrasing.
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 simple 2-parameter tool and no output schema, the description adequately covers what it does and when to use it, referencing its data dependencies. However, it could be more detailed about the returned summary structure or period boundaries, but this is not critical for a straightforward summarize tool.
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?
The schema already covers both parameters with format descriptions (YYYY-MM-DD), and the description's 'for a period' only restates the general role of the date range without adding new constraints or examples. Thus, it complements but does not enrich 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 uses the specific verb 'summarize' with a defined resource ('inflow/outflow and category spend') and temporal scope ('for a period'), distinguishing it from sibling tools like get_transactions or list_goals. It clearly conveys what the tool computes and the data sources involved.
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 phrase 'Use for monthly planning' provides a clear, actionable context for when this tool should be selected, but it does not explicitly contrast with alternative tools (e.g., when to prefer get_transactions for detailed line items).
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?
With no annotations, the description carries the burden of behavioral disclosure. 'Fetch' and 'live' indicate a read-only, real-time operation, and 'all linked Items' clarifies scope. However, it omits potential latency, authentication requirements, or whether results are cached, which are minor gaps for a simple read tool.
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 with no redundancy. It front-loads the action ('Fetch live balances') and adds the command for clarity, making it highly efficient.
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 tool with no parameters and no output schema, the description is fully complete: it states what is fetched, the scope, and the underlying CLI command. Sibling tools cover distinct domains, so no ambiguity remains.
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 zero parameters, so the schema fully covers input. The description correctly adds no parameter-specific details, and the baseline for a zero-parameter tool is 4.
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 uses the specific verb 'Fetch' with the clear resource 'live balances for all linked Items,' distinguishing it from siblings like get_transactions or get_liabilities. The scope is explicit and unambiguous.
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 clearly implies when to use this tool (when you need balances for all linked items) but does not explicitly state alternatives or when not to use it. The context is clear from the scope, but no direct comparison to siblings is 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?
No annotations are provided, so the description carries the full burden. The verb 'List' implies a read-only operation but does not disclose additional behavioral details such as whether the rules are returned in a specific order, what happens when no rules exist, or whether there are any side effects. The description is adequate but minimal.
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, concise sentence that directly states what the tool does and its purpose. There is no unnecessary information, and the structure is easy to parse.
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 (no parameters, no output schema), the description fully covers what the agent needs to know: what is being listed and why it matters (cashflow summarization). It also appropriately situates the tool within the broader feature set.
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 zero parameters, and schema coverage is 100% (vacuously). The description adds no parameter-specific information, which is appropriate since there are no parameters. Baseline for zero-parameter tools is 4.
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 lists 'merchant substring → category rules' with the specific context of being used for cashflow summarization. The verb 'List' identifies a read operation, and the resource is precisely defined, distinguishing it from sibling tools like add_category_rule.
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 the tool is for viewing rules that influence cashflow summarization, but it does not explicitly state when to use it versus alternatives or mention any exclusions. There is no guidance on when not to use this tool or how it relates to sibling tools such as add_category_rule.
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 present, so the description carries the full burden. It adds useful context about the Plaid CLI and environment (Trial/Production) but does not describe return format, pagination, or any access limitations. For a read-only list operation, this is adequate but not rich.
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 with two clauses, both earning their place: the first states the core function, the second gives usage preference. No wasted words.
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 zero-parameter list tool, the description covers purpose and a key contextual preference. It does not describe the output format, but given no output schema exists, some detail could be added. However, the simplicity of the tool makes this 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 tool has zero parameters and schema coverage is 100% vacuously. With no parameters to document, the description needs no parameter semantics; baseline 4 is appropriate.
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 a specific verb ('List') and resource ('Plaid Items linked via the Plaid CLI'), with environment context (Trial/Production). It clearly distinguishes itself from local connect DB alternatives, even if not explicitly comparing to sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance to prefer this tool over 'any local connect DB,' naming an alternative and stating a preference. Lacks explicit when-not-to-use conditions, but the context is clear enough for a simple listing tool.
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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