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

The description adds value beyond annotations by noting deterministic calculation and that aggregations use the complete fetched period. It does not contradict the readOnly, idempotent, or non-destructive hints. More detail on error handling or data limits would be beneficial.

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

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

Two sentences, no fluff. The first sentence clearly states the core function and options; the second adds a critical behavioral detail. Highly efficient.

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

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

While the description covers the main purpose and grouping, it omits explanations for budget_id and include_transfers, and does not mention return structure (though output schema exists). More details on required parameters and result format would improve completeness.

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

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

Schema description coverage is 0%, so the description must compensate. It explains group_by enum values and implies date range parameters, but budget_id and include_transfers are left unexplained. Partial coverage leaves gaps for a 5-parameter tool.

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

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

The description clearly states the tool calculates income, spending, and net totals over an inclusive date range, grouped by category, payee, account, week, or month. This distinguishes it from siblings like ynab_list_transactions and ynab_compare_spending_periods.

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

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

The description implies usage via the grouping and date range options but does not explicitly state when to use this tool versus alternatives like ynab_compare_spending_periods or ynab_list_transactions. No when-not-to-use guidance is provided.

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

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

Annotations already indicate idempotent and non-destructive. Description adds safety confirmation and return value. No contradictions.

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

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

Extremely concise: two sentences plus usage line. Front-loaded with core purpose. No wasted words.

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

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

Given zero parameters and simple operation, description covers purpose, safety, usage, and return. Completeness is sufficient.

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

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

No parameters, baseline 4 as per guidelines. Description notes 'Args: (none)' which aligns with schema.

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

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

Description explicitly states it clears in-memory caches, emphasizing safety and no data modification. Clearly distinguishes from sibling tools that manipulate YNAB data.

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

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

Provides explicit guidance on when to use: after external YNAB changes or to free memory. Lacks explicit when-not scenarios 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.

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint, so safety and idempotency are clear. The description adds 'deterministically' which reinforces idempotency, and 'complete spending periods' clarifies scope. No contradictions exist. Additional context like data sources or side effects is not needed given annotations.

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

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

The description is a single sentence that conveys all essential information without redundancy. It is front-loaded with the action and outcome, making it easy to scan. Every word adds value.

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

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

Given the tool's complexity (5 parameters, nested objects, output schema exists), the description covers the core purpose and outcome. However, it omits details like the necessity of complete historical periods, handling of missing data, or default behavior for budget_id. The presence of an output schema mitigates the need for return value documentation. Overall, it is nearly complete for a comparison tool.

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

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

Schema description coverage is 0%, meaning the description does not explain any parameters. While the schema itself is well-defined with required fields and enums (group_by, period_a, period_b), the description should at least mention the grouping options or the purpose of 'include_transfers' to compensate for the lack of parameter documentation. The rubric requires compensation when coverage is low (<50%), and the description fails to provide it.

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

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

The description clearly states the tool's function: 'Compare two complete spending periods and calculate total and per-group differences.' It uses a specific verb ('compare') and resource ('spending periods'), and the result type is clearly defined ('differences'). This distinguishes it from sibling tools like 'ynab_analyze_spending' (general analysis) and 'ynab_compare_transactions' (transaction-level comparison).

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

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

The description implies use when needing to compare two complete spending periods across groups. It does not explicitly state when not to use it or mention alternatives, but the tool name and sibling context (e.g., ynab_compare_transactions) provide clear differentiation. The phrase 'deterministically' hints at reproducibility, which is useful.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral detail by specifying the return structure: 'comparison report with matched, unmatched_bank, unmatched_ynab transactions'. This goes beyond annotations without contradicting them.

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

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

The description is concise with a single-line purpose and a clear bullet-like list of parameters. It is front-loaded and free of fluff. However, it could be more compact by integrating the parameter list into structured documentation, but overall it is efficient.

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

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

Given 12 parameters, nested csv_format object, and an output schema, the description should cover key behavioral aspects like matching logic, tolerances, and format auto-detection. It only mentions the return report and a subset of parameters, leaving many details unexplained. This is insufficient for a tool of this complexity.

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

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

Schema description coverage is 0%, so the description must compensate. It explains only 5 of 12 parameters (budget_id, account_id, csv_file_path/csv_data, statement_start_date, statement_date) via the docstring, omitting debug, csv_format, amount_tolerance, auto_detect_format, date_tolerance_days, enable_chronology_bonus. This is a significant gap for a complex tool.

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

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

The description clearly states the verb 'compare' and the resources 'bank CSV transactions' with 'YNAB transactions', with the explicit goal to 'find missing or mismatched entries'. This distinguishes it from sibling tools like ynab_list_transactions or ynab_get_transaction, as it is the only comparison tool.

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

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

The description explains when to use the tool (for comparing bank CSV data against a YNAB account) and provides usage context (optional budget_id, required account_id, etc.). It does not explicitly state when not to use or name alternatives, but given the sibling list, this is the sole comparison tool, so no exclusion is needed.

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

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

Annotations already indicate mutation (readOnlyHint=false) and non-destructiveness. The description adds the preview/execute pattern with dry_run and confirmation_token, which is critical behavioral context for safe usage. It also notes default values and optionality, adding value beyond annotations.

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

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

The description is well-organized: a one-line summary, structured Args/Returns/Examples sections, and a separate safety note. Every sentence adds value with no redundancy or fluff.

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

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

Given 6 parameters, limited schema descriptions, and available output schema, the description covers all necessary aspects: purpose, parameters, return value, examples, and the preview/execute workflow. It is complete for an agent to use effectively.

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

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

Schema coverage is only 17%, but the description compensates by explaining each parameter's meaning, allowed values (e.g., type enum), defaults, and optionality. It also provides examples and clarifies the role of confirmation_token in the safety note.

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

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

The description clearly states 'Create a new account in a YNAB budget.' The verb 'create' and resource 'account' are specific, and it distinguishes from sibling tools like ynab_create_transaction by focusing on account creation.

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

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

The description includes examples and a preview/execute pattern, but it does not directly compare this tool to alternatives (e.g., when to create an account vs. a transaction). No explicit exclusions or when-not-to-use guidance is provided.

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

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

Annotations show it is not read-only, not destructive, not idempotent. The description adds the preview workflow with confirmation_token and mentions proportional tax allocation. It does not contradict annotations. The write safety preview mechanism is explained, which is valuable beyond the annotations.

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

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

The description is well-structured with a purpose sentence, a parameter list, usage guidance, return info, and a safety note. It is somewhat lengthy due to the parameter list but each element serves a purpose. Could be slightly more concise but remains clear.

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

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

Given the complexity (14 params, nested categories, tax allocation), the description explains the purpose, workflow, and preview mechanism. It mentions the return includes transaction with subtransactions and receipt_summary. However, it does not detail the tax allocation algorithm, but this is likely acceptable. Output schema exists, reducing the need for return details.

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

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

Schema description coverage is only 7% (only confirmation_token has description). The description provides explicit type, requirement, and meaning for all 14 parameters (e.g., budget_id: 'Budget UUID. Omit to use the default budget.'). This fully compensates for the low schema coverage, adding significant value.

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

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

The description clearly states it 'Create[s] a split transaction from itemized receipt data with proportional tax allocation.' It distinguishes from the sibling tool 'ynab_create_transaction' by specifying that this is for receipt-based tax allocation, while the sibling is for generic manual splits.

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

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

Explicitly says 'Use this helper when you have receipt line items and want tax allocated across categories automatically. For generic manual split transactions without receipt/tax logic, use "ynab_create_transaction" with "subtransactions".' This provides clear when-to-use and when-not-to-use with an alternative.

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

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

The description adds behavioral context beyond annotations by detailing the write safety preview mechanism. Annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true) are not contradicted. It does not specify idempotency guarantees for the execute step, but the preview-token pattern implies safe retry.

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

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

The description is extremely concise with only two sentences, the first stating purpose and key parameter advice, the second explaining the critical preview workflow. Every sentence adds value with no wasted words.

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

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

Given the tool's complexity (14 parameters, 3 required, output schema exists), the description is incomplete. It omits required parameters, frequency enum details, date format, and output behavior. The open world hint is not explained. The output schema may compensate, but the description fails to guide the agent on required vs optional fields or error handling.

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

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

Schema description coverage is only 29%, but the description adds crucial context for amount fields (prefer amount_decimal) and confirmation_token (short-lived, from preview). However, many parameters (date, memo, payee_id, etc.) remain undocumented in both schema and description, leaving gaps.

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

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

The description clearly states the tool's function: 'Create a recurring scheduled transaction.' It distinguishes itself from sibling tools like ynab_create_transaction (one-time) and ynab_create_receipt_split_transaction through the focus on recurring transactions. The purpose is specific and unambiguous.

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

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

The description provides explicit guidance on using amount_decimal over amount_milliunits and explains the two-step preview-execute workflow. It advises calling without confirmation_token to preview, then executing with the token. However, it does not contrast with one-time transaction tools or explicitly state when not to use this tool.

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

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

Annotations show readOnlyHint=false, destructiveHint=false, idempotentHint=false. The description adds that the tool creates a transaction, supports a preview-with-execution flow, and returns account_balance. It also explains that import_id is intentionally omitted for normal use. No contradictions.

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

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

The description is thorough but well-structured: a brief intro, a parameter list with clear formatting, usage notes, examples, and safety instructions. Every section adds value, though it could be slightly more concise by grouping related options.

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

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

Given the tool's complexity (17 parameters, multiple amount methods, splits, preview flow), the description covers the main use cases, safety, and alternatives. The output schema exists so return values are not needed. A few missing details (e.g., subtransaction max items) are minor.

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

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

Schema coverage is low at 24%, but the description provides detailed explanations for each parameter including preferred amount methods, deprecation, subtransaction structure, and the confirmation_token flow. This adds significant semantics beyond the schema's minimal descriptions.

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

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

The description clearly states it creates a single transaction in YNAB. It distinguishes from the sibling tool for receipt splits and specifies the scope (single transaction, not batch or splits). The verb 'Create' and resource 'transaction' are precise.

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

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

Explicitly says to use subtransactions for manual splits and references ynab_create_receipt_split_transaction for receipt data. Mentions write safety (preview with confirmation_token). However, it does not mention the batch sibling ynab_create_transactions for multiple transactions, missing a clear when-not-to-use.

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

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

Description details the two-step commit process, dry-run behavior, and duplicate detection, adding significant context beyond annotations. No contradiction with readOnlyHint=false, destructiveHint=false, idempotentHint=false.

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

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

Well-structured with Args, Returns, Examples, and Write safety sections. Every sentence adds value; it is front-loaded with the main purpose and concise for the complexity.

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

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

Given the tool's complexity, the description covers batch limits, validation, safety, and return summary. Output schema exists, so return values are documented. No gaps for agent decision-making.

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

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

Despite low schema coverage (25%), the description explains all top-level parameters (budget_id, transactions, dry_run, confirmation_token) and distinguishes amount variants. It adds meaning for the confirmation_token workflow and duplicate detection, though some transaction sub-fields rely on schema.

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

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

The description clearly states it creates 1–100 transactions in a single batch with duplicate detection and dry-run support. It distinguishes itself from siblings like ynab_create_transaction (single) and ynab_create_receipt_split_transaction by specifying batch size and features.

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

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

Provides explicit when-to-use context: batch creation, dry-run validation, duplicate detection via import_id. Includes a 'Write safety' section explaining the preview-commit pattern, guiding agents on safe invocation.

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

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

Annotations already indicate destructive and idempotent behavior. The description adds the crucial two-phase commit pattern (preview then execute) with 'Write safety' and explains the short-lived token, providing valuable behavioral context beyond annotations.

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

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

Two sentences, no filler. The first sentence states the purpose, the second explains the essential two-step process. Every word earns its place.

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

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

Given the destructive, idempotent nature and the preview safety mechanism, the description covers all necessary context. The existence of an output schema further reduces the need to describe return values. The description is complete for this tool's complexity.

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

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

Schema coverage is low (25%), but the description compensates by explaining the roles of dry_run and confirmation_token through the preview/execute flow. It does not describe budget_id or scheduled_transaction_id, but those are typical for a delete operation.

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

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

The description clearly states the action ('Delete a scheduled transaction') and the resource, directly matching the tool name. The two-step preview/execute pattern distinguishes it from sibling tools like update or create.

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

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

The description explicitly guides the user to call without confirmation_token to preview first, then execute with the returned token. This provides a clear workflow but does not explicitly mention when not to use the tool or compare with alternatives, though the purpose is distinct.

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

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

Beyond annotations (destructiveHint), the description adds the irreversible nature, error handling, and the preview workflow. This adds value, though the idempotentHint is not explicitly addressed.

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

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

The description is well-structured with clear sections (purpose, args, returns, errors, write safety). It is concise, front-loaded, and every sentence adds value.

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

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

Given the presence of an output schema and the tool's complexity, the description covers purpose, parameters, errors, and workflow. It omits details like idempotency but is sufficient for a destructive tool with preview.

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

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

The description explains budget_id, transaction_id, and dry_run, but does not list confirmation_token in the Args section, even though the schema includes it. Schema coverage is low (25%), so description partially compensates.

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

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

The description clearly states the tool deletes a transaction from YNAB and emphasizes irreversibility. It uses specific verb+resource, and 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.

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

The description provides guidance on the two-step preview-execute workflow using confirmation_token, but does not compare to sibling tools like ynab_delete_scheduled_transaction, leaving potential ambiguity.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the description's addition of health, cache, etc., provides context but doesn't significantly expand on behavioral traits. No contradictions.

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

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

The description is concise, starting with a clear one-line purpose followed by a well-structured parameter list. Every sentence adds value without redundancy.

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

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

Given 7 optional boolean parameters, one enum, and the existence of an output schema, the description covers the essential purpose and parameter meanings. It is complete for a diagnostic tool, though no output schema details beyond 'diagnostics object'.

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

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

Schema description coverage is 0%, but the description lists all parameters with their purpose, defaults, and for response_format, the enum values. This adds substantial meaning beyond the empty schema descriptions.

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

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

The description specifies the verb 'Get' and the resource 'comprehensive diagnostic information about the MCP server', listing categories (health, cache, delta, security). This clearly distinguishes it from sibling tools like ynab_clear_cache or data retrieval tools.

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

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

The description implies usage for diagnostics but provides no explicit when-to-use, when-not-to-use, or alternatives. Sibling differentiation is implicit through the tool's unique function, but no guidelines are given.

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

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

Annotations already declare readOnly, idempotent, non-destructive. Description adds value by specifying return format (file_path, transaction_count, file_size_kb) and error conditions. It does not reveal file overwrite behavior, but given idempotentHint, it's not critical.

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

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

Organized with clear sections (Args, Returns, Examples, Errors), front-loaded with the core action. No superfluous text, though a slightly more succinct phrasing could be used. Earns a 4 for structure.

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

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

Despite having an output schema, the description fails to cover over half of the input parameters. With 7 parameters and no schema descriptions, the description should be more thorough. Only returns and one error case are mentioned, leaving significant gaps.

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

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

Schema coverage is 0%, so description must compensate. Only 3 of 7 parameters (budget_id, account_id, since_date) are described, leaving type, minimal, filename, and category_id undocumented. This is a significant gap for an agent to invoke the tool correctly.

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

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

The description clearly states it exports transactions to a local JSON file, with specific verb 'Export' and resource 'transactions for a budget'. It distinguishes from sibling tools like ynab_list_transactions or ynab_get_transaction by emphasizing file persistence.

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

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

Provides examples and error handling ('No default budget set' → run ynab_set_default_budget first), but lacks explicit guidance on when to choose this tool over alternatives like ynab_list_transactions for in-memory data. Usage context is implied but not fully differentiated.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds return fields including cached and cache_info, and lists possible errors, providing useful context beyond annotations.

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

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

Well-organized with clear sections: brief purpose, Args list, Returns, Errors. Each sentence is informative without unnecessary fluff.

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

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

Given the presence of an output schema and annotations, the description covers all needed aspects: parameter details, return fields, error cases, and default behavior. No gaps for a read-only get operation.

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

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

Schema description coverage is 0%, but the docstring explains all 3 parameters: budget_id (optional, default budget), account_id (required), response_format (optional, enum with default). This fully compensates for missing schema descriptions.

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

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

Description clearly states 'Get details for a single account including current balance,' which is a specific verb+resource. It distinguishes from sibling 'ynab_list_accounts' which lists all accounts.

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

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

Provides clear context: optional budget_id with default budget behavior, required account_id, and error guidance for 'No default budget set' and 'Account not found'. No explicit 'when not to use' or comparison to alternative tools, but sufficient for its purpose.

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

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

Annotations indicate readOnly, idempotent, non-destructive. The description adds further behavioral details: mentions the return fields explicitly and describes an error case. No contradictions.

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

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

The description is well-structured with clear sections (Args, Returns, Examples, Errors), front-loaded with the one-line purpose. Every sentence adds value and is concise.

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

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

Given the output schema exists, the description still provides complete context: input, output, error handling, and example. For a simple get tool, it covers all necessary information.

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

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

With 0% schema description coverage, the description compensates fully: it explains both parameters (budget_id as UUID, response_format with enum and default) and adds context beyond the schema.

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

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

The description clearly states 'Get summary information for a specific YNAB budget', using a specific verb and resource. It distinguishes from siblings like ynab_list_budgets by focusing on a single budget. The title annotation reinforces this.

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

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

The description provides an example linking to ynab_list_budgets and mentions error handling. However, it does not explicitly state when not to use this tool versus alternatives, though the name and sibling context make it clear.

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

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds value by disclosing that results are for the 'current month', detailing the return fields (id, name, budgeted, activity, balance, goal_type, etc.), and explaining error conditions. This goes beyond what annotations convey.

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

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

The description is well-structured with a clear one-line purpose, bulleted args, a returns line, and error list. It is front-loaded and concise, though the docstring style (Args:, dashes) is slightly verbose for a function description.

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

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

Given the tool's simplicity (3 params, no nested objects) and the presence of an output schema (not shown but signaled), the description covers the key aspects: current month scope, return fields, and error handling. It is largely complete, though it could mention that activity is the month-to-date activity.

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

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

Schema description coverage is 0%, but the description compensates by explaining each parameter: budget_id (UUID, optional to use default), category_id (UUID), response_format (enum default 'markdown'). This adds practical meaning though it could be more precise (e.g., UUID format).

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

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

The description clearly states 'Get current month details for a specific budget category' with a specific verb and resource. It distinguishes from siblings like ynab_list_categories (which lists many) and ynab_get_month (which gets a full month) by focusing on a single category's details.

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

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

The description provides basic usage hints like omitting budget_id to use default and lists errors that guide troubleshooting (e.g., requiring ynab_set_default_budget first). However, it lacks explicit guidance on when to use this tool instead of alternatives like ynab_list_categories or ynab_get_month, and does not mention prerequisites beyond the default budget.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context about returning default_budget_id (null if not set) and has_default, which aligns with annotations. No contradictions.

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

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

Description is very concise: two sentences plus a Returns line. No unnecessary words, front-loaded with core purpose.

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

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

Given the tool's simplicity (one optional parameter) and presence of an output schema, the description sufficiently explains the return value structure. No gaps.

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

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

The only parameter is response_format, which is fully defined in the schema with enum and default. The description repeats this without adding extra semantics. Schema coverage is 0%, but the description does not compensate meaningfully.

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

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

The description clearly states 'Get the currently configured default budget ID', which uses a specific verb 'Get' and identifies the resource 'default budget ID'. Among siblings like ynab_get_budget and ynab_list_budgets, this tool is distinct.

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

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

No guidance on when to use this tool versus alternatives, nor any prerequisites or caveats. The description simply states what it does without contextual usage advice.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds value by specifying the return structure (month, cached, cache_info) and caching behavior. It does not disclose any additional side effects, but the existing annotations cover safety well.

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

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

The description is well-structured with clear sections: purpose sentence, Args, Returns, Examples, Errors. It is concise with no redundant information, front-loaded with the main purpose, and every sentence adds value.

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

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

Given the complexity (3 params, output schema exists), the description covers all necessary aspects: parameter details, return fields, caching, error handling, and an example. The existence of an output schema reduces the burden, and the description still provides a summary of return fields.

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

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

With 0% schema description coverage, the description fully explains all three parameters: budget_id (optional UUID, defaults to default), month (required, YYYY-MM-DD format with first day example), and response_format (optional, enum with default). This adds significant meaning beyond the schema's types and patterns.

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

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

The description clearly states the tool gets full budget data for a specific month including all category balances. It uses a specific verb ('Get') and resource, and distinguishes itself from siblings like ynab_list_months or ynab_get_category by focusing on the monthly summary with all categories.

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

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

The description provides usage context like optional budget_id (default budget) and month format, and error handling (no default budget). However, it lacks explicit guidance on when to use this tool over siblings (e.g., ynab_get_budget vs this), and does not specify when not to use it.

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

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

Annotations already cover readOnly, idempotent, non-destructive. Description adds caching behavior and error conditions (default budget, not found), which go beyond annotations.

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

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

Front-loaded with purpose, uses structured bullet points for args/returns/errors. Every sentence adds value with no redundancy.

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

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

For a simple retrieval tool, covers inputs, outputs (field list), errors, and caching. Output schema exists but description still mentions return fields.

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

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

Schema has 0% description coverage, but description fully explains all parameters: budget_id (optional, default), payee_id (required), response_format (enum, default markdown). Compensates completely.

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

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

States 'Get details for a specific payee'—a specific verb and resource. Clearly differentiates from sibling 'ynab_list_payees' which lists all payees.

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

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

Provides clear context: use by payee_id, optional budget default, response format choice. Includes error handling guidance but no explicit when-not or comparison to alternatives.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe read operation. The description adds no additional behavioral context beyond 'Get', which 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.

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

The description is one short sentence with no unnecessary words, perfectly concise and front-loaded with the core purpose.

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

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

Given the tool has 2 parameters, no param descriptions, and an output schema is present but not explained, the description lacks completeness. It does not specify that it returns the full scheduled transaction object or mention budget_id.

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

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

Schema description coverage is 0%, and the description does not explain any of the parameters (budget_id, scheduled_transaction_id). The user must infer meaning from property names alone, which is insufficient.

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

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

The description clearly states the verb 'Get', the resource 'one scheduled transaction', and the method 'by ID', distinguishing it from siblings like ynab_list_scheduled_transactions and ynab_get_transaction.

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

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

The description does not provide any guidance on when to use this tool vs alternatives like ynab_list_scheduled_transactions or ynab_create_scheduled_transaction. It lacks explicit context for usage.

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

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

The description adds value beyond annotations: it discloses caching behavior (returns cached, cache_info), details the response structure, and explains error conditions. Annotations provide readOnlyHint, idempotentHint, and destructiveHint, which are consistent. No contradictions.

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

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

The description is compact and well-structured: a one-line purpose, then Args list, Returns, and Errors sections. Each sentence is necessary and informative. No extraneous text.

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

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

Given the annotations and output schema (implied), the description lists all return fields, including subtransactions and caching info, which is comprehensive. It also covers error handling and optional parameter behavior, making it fully adequate for an agent to use without ambiguity.

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

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

Despite 0% schema coverage, the description fully explains each parameter: budget_id can be omitted for default budget, transaction_id is required, response_format has enum options with default 'markdown'. It adds meaning beyond the schema by defining default behavior and error messages.

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

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

The description clearly states 'Get full details for a single transaction by ID' immediately. The verb 'get' and resource 'single transaction' specify the action and scope, distinguishing it from siblings like ynab_list_transactions (list multiple) or ynab_update_transaction (modify). It is specific and unambiguous.

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

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

The description provides usage context by listing the required and optional parameters with explanations, and includes error conditions with corrective actions (e.g., run ynab_set_default_budget if no default budget). Although it does not explicitly say when not to use it, the purpose and sibling names imply that for listing multiple transactions or for other operations, other tools are appropriate.

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

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

Beyond annotations (readOnlyHint, idempotentHint), the description discloses error conditions (UNAUTHORIZED) and return details (user id), adding meaningful behavioral context.

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

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

The description is short, well-structured with clear sections (description, args, returns, errors), and every sentence adds value.

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

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

Given the simplicity of the tool (1 optional parameter, read-only), the description covers purpose, parameter, return, and errors completely, despite an available output schema not shown.

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

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

The description fully explains the single parameter (response_format), including its optional nature, default value, and enum options, compensating for 0% schema description coverage.

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

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

The description clearly states the tool retrieves information about the authenticated YNAB user, with a specific verb and resource. It uniquely identifies the tool among siblings as the only one for user info retrieval.

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

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

The description provides no guidance on when to use this tool versus alternatives or when not to use it, lacking explicit usage context or exclusions.

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

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

Annotations already declare readonly, idempotent, non-destructive. The description adds behavioral details: pagination (limit, offset, has_more), caching info, and error conditions, going beyond annotations.

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

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

Well-organized with Args, Returns, Examples, Errors sections. Purpose stated first. Every sentence adds value. Concise yet comprehensive.

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

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

Given sibling tools, annotations, and presence of output schema (mentioned in description), the description covers return structure, pagination, caching, and errors adequately.

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

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

Schema coverage is 0%, but description compensates by documenting all 4 parameters with types, defaults, constraints, and examples (e.g., budget_id optional, limit exclusiveMin 0, offset min 0, response_format enum).

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

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

Clearly states 'List all accounts for a budget.' Verb and resource are specific, and it differentiates from siblings like ynab_get_account and ynab_list_budgets.

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

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

Includes error guidance (e.g., 'No default budget set' suggests ynab_set_default_budget) and examples for pagination. However, no explicit when-not-to-use compared to alternatives like ynab_get_account.

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

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

The description adds behavioral context beyond annotations: it discloses caching behavior, return structure (budgets[], cached, cache_info), and a specific error (UNAUTHORIZED). Annotations already indicate read-only and idempotent, so the description complements these well without contradiction.

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

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

The description is concise and well-structured, using clear headings for args, returns, examples, and errors. Every line adds value with no wasted words.

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

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

Given the tool's simplicity (one optional parameter, read-only), annotations, and existence of an output schema, the description is complete: it covers purpose, parameter, return format, example usage, and error handling. No gaps are evident.

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

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

With 0% schema coverage, the description compensates by explaining the single parameter response_format, including its enum values and default. This adds meaning beyond the schema, which only defines the property without description.

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

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

The description clearly states the tool lists all YNAB budgets for the authenticated user, using a specific verb and resource. It distinguishes from siblings like ynab_get_budget by specifying 'all budgets', making its purpose unambiguous.

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

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

The description implies usage for listing all budgets but does not explicitly state when to use this tool versus alternatives like ynab_get_budget for a single budget. No exclusions or alternatives are mentioned, relying on 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.

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

Annotations (readOnlyHint, idempotentHint) indicate safe operation. Description adds behavioral context: pagination behavior (has_more, next_offset), caching (cached, cache_info), and default budget dependency. No contradictions.

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

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

Well-structured: one-purpose sentence followed by a clean docstring format with Args, Returns, Examples, Errors. Every sentence adds value without verbosity.

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

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

Covers pagination, default budget, response format, caching, error cases, and return fields. Despite output schema existing, description adds comprehensive context with examples and error handling.

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

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

Schema coverage is 0%, but the description fully documents all 4 parameters: budget_id (optional, default), limit (default 50), offset (default 0), response_format (enum, default 'markdown'). Also explains return fields beyond schema.

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

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

The description clearly states 'List all budget categories for a budget with pagination,' specifying the verb (list), resource (budget categories), and scope (pagination). It distinguishes from sibling tools like ynab_get_category (singular) and other list tools.

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

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

Provides explicit guidance: omit budget_id for default budget, pagination examples (limit=50, offset=50), and error handling ('No default budget set' → run ynab_set_default_budget first). Does not explicitly say when to avoid but is clear enough.

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

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

Annotations already mark the tool as read-only and idempotent. The description adds valuable context such as pagination behavior, caching fields (cached, cache_info), and response structure beyond annotations.

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

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

Structured with clear sections (Args, Returns, Examples, Errors). Every sentence serves a purpose, no redundancy. Front-loaded with the core action.

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

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

Covers pagination, error recovery, response fields, and examples. With an output schema present, the return field descriptions are sufficient. No gaps for correct tool invocation.

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

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

Schema coverage is 0%, but the description fully documents each parameter with types, defaults, and examples (e.g., limit default 50, response_format enum choices). This compensates completely for the schema's lack of descriptions.

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

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

The description clearly states 'List summary data for all budget months with pagination', using a specific verb and resource. It distinguishes from sibling 'ynab_get_month' which retrieves a single month.

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

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

Provides examples for common use cases and error handling (e.g., 'No default budget set' → run ynab_set_default_budget). However, it does not explicitly contrast with alternatives like ynab_get_month.

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

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral context: pagination parameters, return fields (including cache_info), and error handling, going beyond what annotations provide.

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

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

The description is well-organized into Args, Returns, Examples, and Errors sections. Every sentence adds value, no redundancy. It is appropriately sized for the tool's complexity.

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

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

Given the presence of an output schema, the description still provides comprehensive information: all parameters, return structure, pagination details, and error handling. Examples cover common use cases, making it complete for agent invocation.

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

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

Schema coverage is 0%, so the description fully documents all 4 parameters. It explains budget_id as optional UUID, limit and offset with defaults and constraints, and response_format with enum values 'json' or 'markdown', adding meaning beyond the schema.

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

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

The description explicitly states 'List all payees for a budget with pagination,' using a specific verb and resource. It clearly distinguishes from sibling tools like ynab_get_payee (single payee) by focusing on listing all payees with pagination.

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

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

The description includes examples for pagination and an error section advising to run ynab_set_default_budget if no default budget is set. It provides clear guidance on usage, though it does not explicitly contrast with alternative tools like ynab_get_payee.

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

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

Annotations already declare readOnly/ idempotent/ openWorld hints; description adds behavioral info about delta caching, pagination, and currency format (decimal and milliunits) without contradicting annotations.

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

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

Two concise sentences front-loading the core action and key features; no wasted words.

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

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

Given output schema exists and annotations cover safety, description covers listing, pagination, caching, and currency formatting; missing note on optional budget_id but still clear enough.

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

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

Schema coverage is 0%; description only implies pagination via 'limit' and 'offset' but doesn't explain budget_id or detail parameter semantics beyond the schema.

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

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

Description specifies 'List scheduled transactions' with unique features (delta caching, pagination) and distinguishes from siblings like ynab_list_transactions and ynab_get_scheduled_transaction.

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

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

No explicit guidance on when to use vs alternatives; mentions pagination/caching but doesn't state when not to use or contrast with sibling tools like ynab_get_scheduled_transaction.

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

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds details like pagination, caching (cached, cache_info), and error conditions (e.g., no default budget). It 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.

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

The description is well-structured with clear sections (Args, Returns, Examples, Errors) and front-loaded with the purpose. It is somewhat lengthy due to 9 parameters, but each sentence adds value.

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

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

Given 9 parameters, no required params, output schema presence, and no nested objects, the description covers all necessary aspects: optional params, pagination, error recovery, and alternative tools for large results. It is complete.

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

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

Schema description coverage is 0%, but the description's 'Args' section explains every parameter in detail beyond the schema (e.g., defaults, format, behavior). For instance, it clarifies that budget_id is optional and defaults to the user's default budget.

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

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

The description clearly states the tool's purpose: list transactions for a budget with optional filtering and pagination. It distinguishes itself from sibling list tools by focusing on transactions and specifying filtering capabilities.

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

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

The description provides clear usage context, including examples and error handling (e.g., 'No default budget set' → run ynab_set_default_budget). It mentions alternatives for large results (ynab_export_transactions) but does not explicitly contrast with other transaction tools.

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

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

Annotations indicate non-read-only and idempotent behavior. The description adds critical behavioral context: the write safety mechanism requiring a preview first, the default dry_run=true, and the confirmation_token pattern. This transparency goes beyond the structured annotations.

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

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

The description is somewhat lengthy but well-structured: a clear opening sentence, followed by organized parameter descriptions, return value outline, examples, and safety notes. Every section adds value, though slight tightening could improve conciseness.

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

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

Given the tool's complexity (17 parameters, output schema, nested objects), the description is comprehensive. It covers parameter semantics, return format (narrative + JSON), usage examples, and the unique confirmation_token workflow. The presence of an output schema reduces the need to detail return values, but the description still provides useful context.

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

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

With only 6% schema description coverage, the description compensates thoroughly by explaining most parameters in detail. For example, it clarifies that statement_balance should be negative for liability accounts, and explains the sign_convention options. This adds substantial meaning beyond the schema definitions.

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

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

The description clearly states the tool's purpose: 'Guided account reconciliation: match bank CSV transactions to YNAB, detect discrepancies, and optionally execute bulk create/update/unclear operations.' This provides a specific verb and resource, distinguishing it from siblings like ynab_create_transaction or ynab_export_transactions.

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

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

The description offers extensive usage guidance, including the two-phase preview-execute workflow via confirmation_token, dry_run defaults, and write safety. While not explicitly contrasting with alternatives, the explanation of when to preview vs. execute is clear and actionable.

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

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

Annotations provide idempotentHint, destructiveHint, readOnlyHint. The description adds value by specifying validation against the YNAB API, the return fields (success, default_budget_id, cache_warm_started), and the error case. This complements the annotations without contradiction.

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

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

The description is concise, uses clear sections (Args, Returns, Examples, Errors), front-loads the main purpose, and every sentence adds value without redundancy.

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

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

The tool is simple with one parameter and clear returns. The description covers input, output, error handling, and usage example. It could mention persistence scope (e.g., session or permanent) but overall is adequate given the tool's simplicity and presence of an output schema (though not shown).

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

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

The input schema only defines budget_id as a string with minLength. The description adds critical semantic info: it is a UUID (format), required, and validated against the YNAB API. It also includes an example referencing ynab_list_budgets for obtaining the UUID.

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

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

The description clearly states the tool's purpose: 'Set a default budget so other tools don't require budget_id every call.' It uses a specific verb (set) and resource (default budget) and implicitly distinguishes from siblings like ynab_get_default_budget and ynab_list_budgets.

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

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

The description explains the benefit of using this tool (reducing need to pass budget_id in other calls) but does not explicitly state when not to use it or mention alternatives. The context suggests setting a default is optional, but no exclusion criteria are given.

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

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

Adds significant behavioral context beyond annotations: two-step preview-execute pattern, error messages, and return values (updated category). No contradiction with annotations.

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

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

Front-loaded with purpose, well-organized with args, returns, examples, errors, and safety. Every sentence adds value without redundancy.

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

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

Covers all aspects: purpose, all parameters, usage examples, error handling, and security. Output schema exists, so return values need not be fully detailed. Annotations provide additional context.

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

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

Description explains each parameter meaning, relationships (e.g., budgeted_decimal vs milliunits), deprecation, and defaults, compensating for 43% of parameters lacking schema descriptions.

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

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

The description clearly states 'Update the budgeted amount for a category in the current month,' using a specific verb and resource, and distinguishes it from sibling update tools (e.g., for transactions).

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

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

Provides clear context for use, including examples, error handling, and write safety (preview then execute). However, it does not explicitly compare to alternative tools like ynab_get_category or other update tools.

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

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

Annotations already indicate a write operation (readOnlyHint=false) that is idempotent and non-destructive. The description adds the critical behavioral detail of the preview-commit safety mechanism, which goes beyond what annotations provide.

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

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

The description is only two sentences long, with the first sentence stating the purpose and the second explaining the key safety pattern. Every word contributes value without any fluff.

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

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

Given the tool's complexity with 15 parameters, the description provides the essential preview-commit guidance but lacks clarity on the dry_run parameter's role and does not cover common use cases or return information beyond the output schema.

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

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

Schema description coverage is only 27%, and the description does not explain individual parameters such as date, memo, dry_run, or payee_id. The only parameter mentioned is confirmation_token in context, which is insufficient to compensate for the low coverage.

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

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

The description explicitly states 'Update selected fields on a scheduled transaction,' using a specific verb and resource that clearly distinguishes it from create, delete, get, and list tools among siblings.

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

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

The description outlines a clear preview-commit pattern: call without confirmation_token to preview, then with token to execute. This provides strong guidance on when to use each variant, though it does not explicitly mention when not to use the tool or compare to alternatives.

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

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

Beyond annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false), the description reveals a critical two-step workflow (preview then confirm) via confirmation_token and dry_run, and states it returns 'updated transaction with updated_balance', providing complete behavioral context.

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

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

The description is well-structured with a clear opening, a parameter list (though not formalized), and separate notes on returns and write safety. It is slightly verbose but front-loaded and every sentence adds value.

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

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

Given 16 parameters and the presence of an output schema, the description covers the unique workflow, parameter guidance, and return value. It is sufficiently complete for an agent to use correctly, though it omits some parameter details like flag_color.

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

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

With only 25% schema coverage, the description compensates thoroughly, explaining each parameter's role and preferences (e.g., amount_decimal is preferred, amount is deprecated), and clarifies the confirmation_token workflow, adding essential meaning beyond the schema.

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

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

The description clearly states 'Update fields on an existing YNAB transaction', providing a specific verb (update) and resource (existing transaction), which distinguishes it from sibling tools like create, delete, or update multiple transactions.

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

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

The description includes explicit write safety instructions: preview without confirmation_token then execute with the token, but does not provide when-not-to-use or contrast with alternatives.

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

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

Annotations provide readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds significant behavioral context: batch limit 100, dry-run preview, confirmation_token flow, amount alternatives, and returns summary. No contradiction with annotations.

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

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

The description is concise: a brief opening sentence, a structured args list, returns, an example, and a write safety note. Every sentence adds value with no redundancy.

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

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

Given the tool's complexity (batch update with preview/confirm, multiple amount types, optional budget), and presence of output schema, the description is highly complete. It covers all parameters, the preview-confirm flow, and usage example.

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

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

Schema description coverage is low (25%), but the description compensates by explaining dry_run, budget_id, transactions array structure, amount options (preferred amount_decimal), and confirmation_token derivation. It adds meaning beyond the schema's bare types.

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

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

The description states 'Update 1–100 transactions in a single batch with dry-run preview,' clearly specifying the verb (update) and resource (transactions) with batch size and dry-run capability. This distinguishes it from sibling tools like ynab_create_transactions, ynab_delete_transaction, and ynab_update_transaction (singular).

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

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

The description provides explicit usage guidance: 'Write safety: call without confirmation_token to preview. Execute the identical validated request with the short-lived confirmation_token returned by that preview.' It also mentions optional budget_id to use default. However, it lacks explicit directions on when not to use this tool versus alternatives like ynab_update_transaction.

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