mcp-india-stack

by rehan1020

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.4.2
Disambiguation5/5
Each tool targets a distinct Indian validation, calculation, or lookup (e.g., GSTIN, PAN, HRA, capital gains). No two tools have overlapping purposes, and descriptions clearly differentiate them.
Naming Consistency5/5
Tool names follow a consistent verb_noun pattern with verbs like 'validate', 'calculate', 'bulk_validate', 'decode', 'lookup', each clearly indicating the action. The pattern is uniform across the set.
Tool Count5/5
30 tools is a comprehensive yet focused collection covering major Indian tax, identity, and regulatory needs. Each tool serves a distinct purpose without redundancy, well-scoped for the domain.
Completeness5/5
The tool surface covers core Indian compliance workflows: ID validation, tax calculations, GST/TDS, bank IFSC, and state lookups. No obvious gaps for the stated purpose of an India compliance stack.
Average 4/5 across 30 of 30 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 8 commits in the last 12 weeks
- Last stable release on June 5, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds '# PermissionTier: READ_ONLY,' which is largely redundant and does not disclose additional behavioral aspects like side effects, error conditions, or auth requirements. Since annotations are present, the description adds minimal value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, but it does not provide structured information or earn its place beyond restating the tool name. It is not verbose, but the lack of detail limits its usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate but lacks context about validation behavior, expected inputs, or potential outcomes. It does not explain what validation entails or how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of the single parameter with a clear format description ('XX/XXXXX/XXXXXX/XXX'). The tool description adds no further parameter-level details, so it meets the baseline for high schema coverage without enhancing meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Validate EPF establishment code,' which is a specific verb and resource, but it closely mirrors the tool name without adding further context. It distinguishes from sibling validation tools (e.g., validate_pan) by specifying EPF, but lacks elaboration on scope or format beyond what the schema provides.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus any of the many sibling validation tools. There are no explicit when-to-use, when-not-to-use, or alternative tool references, leaving the agent to infer usage solely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds '# PermissionTier: READ_ONLY', which is already conveyed by the annotations (readOnlyHint: true). It does not provide additional behavioral details such as whether the validation is strictly syntactic or involves external checks. Given annotations cover read-only and idempotent behavior, the added value is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and immediately states the core purpose. However, it could be slightly more descriptive without being verbose. It is efficiently structured but borderline too terse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple validation function with one parameter and an output schema (indicated). The description does not address error handling, output format, or validity criteria beyond the schema. For a minimal tool, this may suffice, but lacks completeness for nuanced edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single 'code' parameter, including a format description. The description does not add any further meaning beyond what the schema already provides. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates an ESIC employer code, which is a specific verb and resource. It implicitly distinguishes itself from sibling tools like 'validate_epf_code' by focusing on ESIC-specific codes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives like 'validate_epf_code' or other validation tools. The '# PermissionTier: READ_ONLY' comment hints at usage context but is insufficient for decision-making among many siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint. The description adds 'parallel' execution and a permission tier, but lacks details on rate limits, error handling, or other behavioral traits beyond what annotations cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with one sentence and a permission comment, front-loading key information. However, it could be slightly more informative without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema and simple parameters, the description is minimally adequate but omits the max batch size and potential error cases, leaving the agent to infer from schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, with a clear description. The tool description adds no additional meaning beyond the schema's 'List of PANs to validate (max 500)'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Validate', resource 'multiple PANs', and distinctive feature 'in parallel', distinguishing it from sibling 'validate_pan'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies batch validation but does not explicitly state when to use this tool versus alternatives like 'validate_pan' for single PANs, nor does it mention exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the main behavioral traits. The description adds 'Calculate' which aligns with read-only. No additional behavioral details (e.g., data source, state coverage) are disclosed beyond annotations, so the description meets but does not exceed the baseline.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences with no extraneous information. The first sentence defines the core purpose, and the second provides usage context. Every word earns its place, making it ideally succinct.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 required parameters), an output schema exists to describe return values, and annotations cover safety, the description is largely complete. It could mention that the calculation depends on state-specific tax slabs, but the schema's state_code description and the 'state-wise' hint suffice. Minor gap: no mention of edge cases like zero salary or unsupported states.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100%, so the schema itself documents both parameters (gross_salary_monthly, state_code). The description does not add any extra meaning, constraints, or formatting hints beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Calculate state-wise professional tax'. It identifies the specific resource (professional tax) and implies a state-dependent calculation. However, it does not explicitly differentiate from sibling tools like calculate_income_tax or calculate_tds, which may be needed when computing total tax liability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context: 'Use when computing total tax liability including professional tax deductions.' This indicates when to use but offers no guidance on when not to use or suggests alternatives among sibling calculator tools. It is vague and lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint. Description adds '# PermissionTier: READ_ONLY' which is consistent but redundant. No additional 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with a compact permission tag. Front-loaded and no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Sufficiently complete for a simple one-parameter lookup tool with an output schema. Could hint at response fields but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and includes a description for the parameter. The tool description itself does not elaborate on the parameter beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action 'look up' and resource 'bank details from RBI master list'. Distinguishes from sibling tools like lookup_ifsc by specifying the data source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like lookup_ifsc. Lacks context on when not to use it or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and idempotentHint, which the description does not contradict. The description does not add behavioral details beyond the obvious validation action, but given the strong annotation coverage, it is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences. It front-loads the key information (what it validates and the acronym meaning) and contains no filler or redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, validation-only, with output schema available), the description is complete enough. It tells the agent the tool's purpose and when to use it. The output schema covers return values, so no further description is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full coverage (100%) and includes format guidance ('AAA-XXXX or AAAXXXX') for the 'llpin' parameter. The description does not add any additional semantics beyond what the schema already describes, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates LLPINs and expands the acronym. It is specific about the resource (LLPIN) and action (validate). However, it does not explicitly differentiate from sibling validation tools like 'validate_cin' or 'validate_gstin', though the name and context suffice.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use when verifying LLP registration numbers,' which gives a clear context of use. But it does not provide when-not-to-use or mention alternatives, leaving the agent without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly and idempotent. The description adds 'in parallel' and a redundant permission note, but no additional behavioral context (e.g., rate limits, error handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence plus a metadata note. No wasted words, and the key functional differentiator (parallel) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present and thorough annotations, the description is minimally adequate. It lacks guidance on when to choose this over sibling bulk tools, but covers the core functionality.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage on the only parameter ('List of IFSC codes to validate (max 500)'), so description adds no further meaning beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Validate multiple IFSC codes in parallel') and distinguishes from siblings like 'lookup_ifsc' and single validation tools by emphasizing parallel batch processing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives; the 'in parallel' hint implies batch usage, but no when-not conditions or other tool comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds no behavioral context beyond stating it is a calculation. It does not elaborate on edge cases, accuracy, or performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two short sentences that front-load the purpose and usage. Every word adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of a complete output schema and annotations, the description adequately covers the tool's purpose and usage. It is concise but complete for a simple calculator tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning the input schema already describes all three parameters well. The description adds no extra parameter-level details, so it meets the baseline without improvement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates 'Recurring Deposit maturity amount'. The name and description together specify the exact resource (RD) and action (calculate maturity). It is distinct from sibling tools like calculate_fd_maturity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context: 'Use when projecting RD returns or planning recurring deposits.' While it doesn't explicitly exclude cases or name alternatives, the guidance is clear and sufficient for typical use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint as true. The description adds a permission tier note but does not elaborate on behavioral traits like what 'map to validator' means or any caveats. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose and includes a permission tier note. Every part is valuable and there is no redundancy or verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter), presence of an output schema (covering return values), and thorough annotations (read-only, idempotent), the description adequately conveys the core functionality. Could briefly explain the 'map to validator' outcome but not strictly necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single required parameter 'uri' described as 'DigiLocker document URI'. The description does not add any additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Decode') and resource ('DigiLocker document URI') and outcome ('map to validator'). This distinguishes it from sibling validation tools which validate documents rather than decoding URIs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating the purpose but provides no explicit guidance on when to use this tool versus alternatives like validate_pan or lookup_ifsc. The permission tier note is not a usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true and idempotentHint: true, so the safety profile is clear. The description adds no additional behavioral context beyond the annotations, which is acceptable but not enhancing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no redundant information, and front-loaded with the core purpose. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and 100% parameter coverage, the description is adequate but does not explain calculation details or edge cases. It is minimally viable for a simple calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already provides full parameter descriptions. The tool description adds no extra meaning about parameters beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate GST late filing penalty', providing a specific verb and resource. The name itself distinguishes it from other calculation tools, and the second sentence reinforces its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when estimating late filing fees or planning compliance', which provides clear context for when to use. However, it does not mention alternatives or exclude any cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and idempotentHint=true. Description adds usage context but no additional behavioral details beyond stating the calculation function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loaded with the purpose. Could be slightly more streamlined, but no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Provides sufficient context for a simple calculator: what it calculates and when to use. Output schema exists, so return value details are not needed. Assumes basic knowledge of SSY/SCSS but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-described in schema. Description does not add new parameter meaning beyond what is already in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it calculates maturity amounts for SSY and SCSS, two specific savings schemes. The verb 'calculate' and resource 'maturity amount' are specific, and it distinguishes from sibling calculate tools for other instruments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to use: planning long-term savings for girl child (SSY) or retirement (SCSS). No explicit exclusion or alternatives, 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly and idempotent; the description adds that it builds JSON, consistent but not significantly additive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise, front-loaded sentences with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values are covered. The description references external ReBIT spec, which is appropriate for a specialized tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions; the tool description doesn't elaborate on parameters, but the schema carries the load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool builds an AA consent request JSON per ReBIT spec for open banking, distinguishing it from sibling validation/calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It says 'Use when setting up data sharing consent for open banking workflows', providing clear context, though it doesn't explicitly mention when not to use it or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds value by mentioning ThreadPoolExecutor for parallel processing. It does not detail concurrency limits, error handling, or rate limits, but these are not critical given 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundant information. The first sentence front-loads the action and key detail (parallel execution). Efficient and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (no need to describe returns), annotations for safety/idempotence, and the description covering purpose, usage, and parallelization, the tool is adequately specified. Minor gap: no mention of validation criteria or error behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the 'numbers' parameter description including max 500 limit. The description adds no parameter-specific details beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Validate' with resource 'multiple Aadhaar numbers' and mentions parallel execution via ThreadPoolExecutor, clearly distinguishing from sibling validate_aadhaar which handles single numbers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states batch validation for KYC, onboarding, or compliance workflows, implying it is not for single validation. However, it does not explicitly mention the alternative sibling tool validate_aadhaar for single cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, so the tool is safe and deterministic. Description adds no behavioral detail beyond the calculation itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values are covered. Description is adequate for a calculation tool with well-documented parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. Description does not add additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Calculate Fixed Deposit maturity amount' with a specific verb and resource. It is distinct from sibling tools like calculate_rd_maturity and calculate_ppf_maturity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Includes explicit usage context: 'Use when projecting FD returns or comparing deposit options.' Lacks explicit when-not or alternatives, but sufficient for standard use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description's simple statement adds no further behavioral insight. It does not disclose any side effects, assumptions, or edge cases 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two efficient sentences with zero wasted words. It front-loads the main action and context immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so the description need not explain return values. It names the governing act, which provides legal context. However, it omits mention that the parameter 'is_covered_under_act' affects eligibility, a detail that would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all three parameters with descriptions, achieving 100% coverage. The description does not add additional semantic meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the verb ('Calculate') and resource ('gratuity under the Payment of Gratuity Act, 1972'). This clearly distinguishes it from sibling tools like calculate_income_tax or calculate_epf_esic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Use when computing terminal benefits, comparing CTC packages, or planning retirement benefits.' However, it does not mention when not to use or name alternative tools for related calculations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true and idempotentHint=true, so the safety profile is clear. The description adds no extra behavioral details (e.g., assumptions, output specifics), but given annotations cover the key aspects, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero wasted words – 'Compare buying vs renting financial outcome. Use when deciding between buying a home or renting.' Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown but present), so return values are documented. The description covers the main purpose and usage. It could mention the output type briefly, but with high schema coverage and annotations, it's nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters have individual descriptions. The tool description does not add extra semantic meaning beyond the schema; it only gives a general overview. Baseline 3 is correct.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Compare buying vs renting financial outcome', which is a specific verb and resource. It distinguishes itself from sibling tools that are other calculators (e.g., tax, EMI) by focusing on the unique decision of homeownership vs renting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It says 'Use when deciding between buying a home or renting', which explicitly states the context. No when-not or alternatives are given, but siblings are unrelated so exclusion is implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, so the description adds minimal behavioral context beyond 'calculate'. No contradictions, but no additional traits disclosed (e.g., no mention of output format or side effects).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action and specific sections. Every word earns its place, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists, so return values are covered. The description is complete for a calculator tool, providing both purpose and usage. It doesn't elaborate on prerequisites, but the required parameter 'total_tax_liability' implies its necessity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for all 5 parameters. The description does not add extra meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates interest under specific sections (234A, 234B, 234C) and provides the context of penalty interest for late filing or short advance tax payments, distinguishing it from sibling tools like calculate_income_tax.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises when to use the tool ('Use when computing penalty interest for late tax filing or short advance tax payments'), though it does not mention when not to use or provide direct alternatives. However, the specificity is sufficient for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, so the description does not need to restate safety. It correctly implies a non-mutating calculation, adding no contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the action and purpose, with no unnecessary words. Every sentence is useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a calculation tool with an output schema, the description is adequate. It could provide more detail on the calculation methodology, but the schema and annotations fill the gaps sufficiently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions, and the description adds no additional meaning beyond what the schema already provides, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates the tax-exempt portion of leave encashment under a specific section (10(10AA)), distinguishing it from sibling tools like calculate_gratuity or calculate_income_tax.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context ('when computing leave encashment tax exemption or planning retirement benefits'), but does not explicitly mention when not to use or alternative tools, though siblings do not directly overlap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to restate these. The description adds the behavior of calculating corpus and pension, which is consistent and sufficient, but no additional behavioral traits 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, no fluff, and efficiently communicates purpose and usage. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple calculate tool with 6 parameters (all described in schema) and an output schema, the description is complete enough for an AI agent to understand its use. Could include example values but not strictly necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage (all parameters have descriptions). The tool description does not add any parameter semantics beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates NPS corpus and monthly pension at retirement, with a specific verb and resource. It distinguishes from sibling tools by specifying 'NPS' and the use case 'planning retirement with NPS or projecting pension'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: 'Use when planning retirement with NPS or projecting pension.' It does not explicitly state when not to use or list alternatives, but the sibling tool names implicitly differentiate (e.g., calculate_epf_esic for EPF).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to repeat that. It adds context about applicable sections (44AD/44ADA) but does not detail output behavior; however, an output schema exists, so this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, front-loaded with the core action. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description does not need to explain return values. It covers the purpose, usage context, and required parameters adequately for a tool with moderate complexity (6 params, 2 required). Could mention that it computes tax amount, but it's implied.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter clearly described. The tool description adds minimal new information beyond the schema, which is acceptable. Baseline score of 3 applies due to full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates tax under Sections 44AD and 44ADA for small businesses/professionals. The verb 'Calculate' and resource 'tax under presumptive scheme' are specific and distinguishable from sibling tools like calculate_income_tax.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when computing tax for small businesses or professionals under presumptive taxation,' providing clear context. It does not mention when to avoid using it or alternative tools, but the sibling list includes broader tax calculators, so some inference is possible.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description's mention of 'calculate' adds minimal behavioral insight. It doesn't contradict annotations, but also doesn't add significant undisclosed behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy. The first sentence states the core function, and the second lists use cases. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and full parameter documentation, the description is sufficient for a calculation tool. It could mention output format briefly, but the schema likely covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 9 parameters, so the description's high-level mention of 'salary restructuring options' does not add additional parameter-level meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates salary restructuring for tax optimization, which is a specific verb-resource pair. It distinguishes from sibling tools like 'calculate_income_tax' or 'calculate_hra_exemption' by focusing on overall restructuring rather than individual components.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: advising on tax-efficient structures, comparing options, and planning CTC optimization. While it lacks explicit 'when not to use' statements, the context of sibling tools makes it implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly and idempotent. Description adds inflation adjustment detail but does not discuss further behavioral aspects like rounding or precision.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the core functionality and usage guidance, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists to define return format; description covers purpose and usage. Minor gap: could mention that output includes inflation-adjusted maturity value, but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage, describing all parameters with defaults, so description adds no additional meaning beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool calculates SIP maturity with inflation-adjusted returns, distinguishing it from sibling tools like calculate_step_up_sip and other return calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use when projecting mutual fund SIP returns or planning systematic investments', providing clear context. However, no mention of when not to use or alternatives like calculate_step_up_sip.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description's simple statement of calculation adds marginal value by specifying marginal relief. No contradictions, but no extra behavioral detail beyond what annotations imply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences: first defines purpose, second gives usage context. No wasted words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, return values need not be described. The description covers purpose and usage, and the tool's simplicity (3 params) means it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and descriptions are adequate. The description adds no extra parameter details beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates surcharge and marginal relief, and distinguishes it from the sibling calculate_income_tool by noting it is separate and standalone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises using this tool when computing surcharge standalone, and notes the income tax tool already includes this logic, implying when not to use it. It lacks explicit mention of alternatives but provides clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to restate these. It adds minor behavioral context by mentioning 'get MCP tool pairings' but no additional traits like side effects or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two efficient sentences, front-loading the main action and usage. Every word adds value, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema present, annotations covering behavior), the description is nearly complete. It could optionally mention the output structure, but the output schema likely handles that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a descriptive parameter comment ('FI type code (e.g., DEPOSIT, MUTUAL_FUNDS)'). The description adds no extra meaning beyond the schema, warranting the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool decodes AA Financial Information type and returns MCP tool pairings, using a specific verb and resource. It distinguishes from sibling decode tools like decode_isin by specifying 'AA Financial Information type'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'Use when mapping FI types to validation/calculation tools,' providing clear context for when to use the tool. It does not explicitly exclude alternatives or mention when not to use, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint. The description adds the specific decoding logic (from 4th character) and reinforces read-only nature via PermissionTier note. No contradictions. Lacks disclosure of behavior for invalid inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence plus a note. Front-loaded and no wasted words. Every part adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with one parameter and output schema. Description explains core behavior and read-only nature. Could mention possible entity types or error cases, but output schema likely covers return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description '10-character PAN'. The description adds no extra meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Decode' and resource 'PAN entity type' with specific logic 'from 4th character'. It distinguishes from sibling tools (e.g., validation, other decodes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a permission tier note but does not explicitly state when to use this tool versus alternatives like decode_state_code. Usage context is implied, but no exclusions or comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true. Description adds that the tool looks up details, which is consistent. No additional 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines purpose, second provides usage guidance. No superfluous text, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given annotations cover safety, schema fully documents parameters, and an output schema exists, the description is sufficient. It provides usage context and category hints, making it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage for all three parameters. The description provides a list of categories similar to the schema's category description, adding no new meaning. Adequate but not improved.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool looks up BBPS biller details, specifying verb and resource. It lists applicable bill categories (electricity, gas, etc.), distinguishing it from sibling validation and calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use when setting up bill payments for...' providing clear context. While it doesn't specify exclusions or alternatives, siblings are distinct, so guidance is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint as true. The description adds no new behavioral details (e.g., what 'decode' entails, auth needs), but it is consistent and does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences that immediately convey purpose and usage. Every word is purposeful, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter, clear annotations, and presence of an output schema (not shown but indicated), the description adequately covers purpose and context. It could mention that the output includes decoded segments, but the output schema likely handles that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is only one parameter, 'dl_number', whose description in the input schema already provides format details and an example. Schema coverage is 100%, so the tool description adds no extra semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('validate') and resource ('Indian driving license number format and decode segments'). It distinguishes from sibling validators by specifying 'Indian driving license', making its unique purpose obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use when verifying DL format, extracting state/RTO/year in KYC workflows,' providing clear context. It does not explicitly list exclusions or alternatives, but the use case is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description adds no extra behavioral context beyond 'validate format', which is consistent but not additive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences with front-loaded purpose; no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential function for a simple validation tool; output schema exists, so return format details are not needed. Minor lack of mentioning 'format-only' is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with detailed parameter info; the tool description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific verb-resource (validate Indian passport number format) and distinguishes from siblings by focusing on Indian passport specifically.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases ('KYC, travel, or identity workflows') but does not mention when not to use or list alternatives; however, sibling names make the distinction clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. Description adds no extra behavioral context (e.g., rate limits, auth needs) beyond stating validation purpose. Consistent 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero wasted words. Front-loaded with purpose and usage, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple (1 param, no enums) and output schema exists, so description need not detail return values. Context is complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'pran' described as '12-digit PRAN'. Tool description does not add meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool validates PRAN (Permanent Retirement Account Number) for NPS, using specific verb 'Validate' and resource 'PRAN'. It distinguishes from sibling validation tools by naming the exact number type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use when verifying NPS account numbers', providing clear context for when to use the tool. Does not include when-not or alternatives, but context is sufficient given sibling tool list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and idempotentHint=true, covering safety. Description adds no behavioral traits beyond that, so score is baseline 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise, front-loaded sentences. No unnecessary information, every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description doesn't need return values. Covers purpose, usage, and asset scope. Complete for a calculator tool with good annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 8 parameters have descriptions in the input schema (100% coverage). Description does not add extra meaning beyond schema, so baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Calculate capital gains tax' with specific verb and resource, and lists asset types. It distinguishes from sibling tools like calculate_income_tax or calculate_gst, which cover different tax types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('when computing tax liability on sale of...'). Does not explicitly state when not to use or name alternatives, but context from sibling tools makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by specifying that it covers both employer and employee contributions and assists in CTC comparisons, which goes 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The first sentence states the core function; the second provides use cases. Ideal front-loading and conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so return values are covered. However, the description omits important context like wage ceilings for EPF/ESIC, which could affect accuracy. Adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add parameter-specific details, but the schema itself documents all parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Calculate EPF and ESIC contributions for employer and employee' with a specific verb and resource. It clearly distinguishes this tool from siblings, as no other sibling tool targets EPF/ESIC calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: 'Use when computing payroll costs, employee deductions, or comparing CTC structures.' It does not explicitly state when not to use or mention alternatives, but the context is sufficient for most cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, which are consistent with the description. The description does not add behavioral details beyond what annotations provide, so it does not enhance transparency further.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences: the first states the purpose, the second provides usage guidance. No unnecessary words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (as per context signals) and the input schema fully documents parameters, the description is complete. It adequately conveys the tool's purpose and usage without needing to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have descriptions in the input schema (100% coverage). The tool description does not add additional meaning beyond the schema, warranting a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates transaction charges for specific transfer modes (NEFT/RTGS/IMPS/UPI). It distinguishes itself from sibling calculation tools by focusing on bank transfer costs, providing a specific verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use the tool: 'when estimating bank transfer costs or comparing payment modes.' While it does not provide when-not-to-use or alternatives, the guidance is clear and contextually appropriate given the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and idempotentHint, so the description does not need to restate these. It adds no further behavioral traits (e.g., error handling, performance characteristics). The bar is lowered due to annotations, but the description only covers purpose, not behavior beyond what's already declared.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. The first sentence announces the action and input, the second specifies the usage context. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no nested objects, output schema present), the description covers the essential scope: what it decodes, from what inputs, and what outputs are provided. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameter 'value' is well-documented in the schema. The description reiterates that it accepts a code or GSTIN prefix, but adds no new semantic detail beyond the schema's description '2-digit state code or GSTIN.' Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool decodes Indian GST state code metadata from a code or GSTIN prefix, listing specific output fields (state name, abbreviation, capital, GST zone). It distinguishes from sibling tools, none of which perform this specific decode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when you need canonical state name, abbreviation, capital, and GST zone mapping,' providing clear usage context. It does not mention when not to use alternatives, but no sibling tool offers this functionality, so the omission is minor.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, so the tool is known to be safe and idempotent. The description adds context about the fiscal year and regulatory scope but no additional behavioral traits like pagination, caching, or update frequency. Adequate but not enhanced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences. The first clearly defines the tool's purpose, and the second states practical use cases. No superfluous words, well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 optional parameters, no required fields) and the presence of an output schema, the description covers purpose and usage adequately. It is complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already fully documents the three parameters (category, from_date, to_date). The description does not add any additional meaning or usage hints beyond what the schema provides, so baseline score 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the specific resource 'India's tax & regulatory compliance calendar for FY2025-26'. It distinguishes itself from sibling tools, which are mostly calculations and validations, by being a calendar query tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists use cases: 'planning tax compliance schedules, setting reminders for deadlines, or building financial compliance dashboards'. While it doesn't mention when not to use, the context is clear and no alternatives are obvious among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds limited behavioral insight beyond mentioning what is decoded. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no extraneous words. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present and one simple parameter, the description provides adequate context including what data is extracted. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description covers 100% of the single parameter with format and example. The description adds no additional parameter meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates and decodes an Indian CIN, with specific verb 'validate and decode' and resource 'CIN'. It lists extracted data (listing status, NIC code, etc.), distinguishing it from sibling validation tools like validate_din.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides use cases: 'when verifying company registration data, extracting listing status, NIC code, state, year, and company type'. While it doesn't list when not to use, the context is clear given sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description's 'validate... format' is consistent. The description does not add significant behavioral context beyond what annotations provide, earning a baseline 3.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose and usage. No redundant or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 1-param tool with output schema, the description provides necessary purpose and context. No gaps given the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with 1 parameter fully described. The description repeats the schema's '8-digit DIN (spaces allowed)' and example, so it adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it validates an Indian DIN format, with specific verb 'Validate' and resource 'Indian DIN'. It distinguishes from sibling tools like validate_pan or validate_gstin.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use when verifying director identity numbers in MCA compliance workflows', providing context and implied usage. No when-not or alternatives, but clear enough among similar validation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, indicating the tool is safe and idempotent. The description does not add significant behavioral context beyond the annotations. It does not describe return format or any edge cases, but for a validation tool, this is acceptable given 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise with two sentences. The first sentence defines the core functionality, and the second sentence provides usage context. No word is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, clear purpose), the description is complete. It covers what the tool does and when to use it. The presence of an output schema and annotations means the description does not need to explain return values or safety concerns further.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a thorough description: '10-char PAN (spaces/hyphens allowed)' with max and min lengths. The description does not add further value about the parameter. Since schema coverage is 100%, the baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates Indian PAN format and decodes the entity type from the 4th character. It uses specific verbs ('validate' and 'decode') and identifies the resource ('Indian PAN'). This distinguishes it from sibling tools like 'decode_pan_type' (which may only decode) and 'bulk_validate_pan' (for bulk operations).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context by stating that the tool should be used when normalizing tax identity records in KYC, invoicing, or vendor onboarding. Although it does not explicitly mention when not to use it or list alternatives, the usage guidance is clear and relevant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and idempotentHint=true. The description adds that it validates format, implying no side effects, but does not elaborate on behavior beyond that. Since annotations cover the main safety signals, additional context is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences: the first states the core purpose, the second provides usage context. Every word is necessary; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple validation tool with one well-documented parameter, clear annotations, and an output schema (not shown but present), the description is sufficiently complete. It explains what the tool does and when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the single parameter voter_id with a description and example. Schema description coverage is 100%, so the description adds no extra parameter information; baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates an Indian Voter ID (EPIC) number format, specifying the verb 'validate' and the resource. It distinguishes from sibling validation tools like validate_pan or validate_aadhaar by focusing specifically on voter ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use when verifying voter ID format in KYC, identity, or electoral workflows,' providing clear context. However, it does not explicitly exclude other scenarios or mention alternatives, leaving room for improvement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the parallel execution via ThreadPoolExecutor and performance improvement to ~N/10 batches, adding context beyond annotations (readOnlyHint, idempotentHint). No destructive behavior is indicated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, each adding distinct value: action, usage guidance, and performance benefit. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one parameter, annotations, and existing output schema, the description covers purpose, usage, and performance. It is complete for the tool's complexity, though output details are left to the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter description 'List of GSTINs to validate (max 500)'. The description adds no further parameter information; baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates multiple GSTINs in parallel, distinguishing it from sibling tools like 'validate_gstin' and other bulk validators by specifying the resource and parallel execution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly gives usage context: 'Use when batch-validating vendor GSTINs for onboarding or reconciliation.' This helps in selecting the tool over alternatives, though it doesn't explicitly mention 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral details beyond annotations (readOnlyHint, idempotentHint): computes CGST/SGST/IGST split and optional cess. No contradictions 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states function, second provides usage context. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, return values need not be explained. Description covers purpose, usage, and mentions key parameters sufficiently for a calculator tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description mentions 'CGST/SGST/IGST split' (transaction_type) and 'optional cess' (cess_category) but adds minimal new meaning beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies 'Calculate GST breakdown with CGST/SGST/IGST split and optional cess', clearly stating verb and resource. Distinguishes from sibling tools like calculate_income_tax and calculate_tds.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use when computing tax for invoices, quotations, or GST compliance', providing clear context. However, lacks explicit when-not-to-use or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, idempotentHint), description details computational components: slab, rebate, surcharge, cess. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with front-loaded purpose and no wasted words. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers key computation aspects. With output schema present, return value details are unnecessary. Minor gap: no mention of input validation or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with clear descriptions. Description adds no additional parameter insights beyond listing computation elements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Calculate Indian income tax for FY2025-26', specifying verb and resource. It distinguishes from sibling tools like calculate_advance_tax and calculate_capital_gains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'Use when computing tax liability, comparing regimes, or planning deductions.' Could be improved by stating when not to use (e.g., for other tax types).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds behavioral context by noting the output is a 'year-by-year breakdown'. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the main purpose, and every word adds value. No redundant or excessive content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return values are not needed. The description covers purpose and usage context adequately. Could include limitations or edge cases, but not critical for a calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents parameters. The description does not add extra meaning beyond what the schema provides; it only hints at output structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Calculate' and the resource 'PPF maturity amount', while adding 'year-by-year breakdown' which distinguishes it from sibling tools like calculate_fd_maturity or calculate_rd_maturity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use: 'planning long-term savings, comparing investment options, or calculating retirement corpus'. However, it does not mention when not to use or specify alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true and idempotentHint: true, so the tool is known to be a safe, idempotent calculation. The description does not contradict these and adds context about the calculation scope. It does not reveal additional behavioral traits, but given the strong annotations, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first sentence states the core function and year, the second lists use cases. There is no redundancy or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high schema coverage and existence of an output schema, the description adequately covers purpose and usage. It is complete for the tool's complexity, though a brief mention of the return format could further improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter already has a description in the input schema. The tool description does not add extra semantic detail beyond listing some use cases. Baseline for high coverage is 3, and there is no additional enrichment.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'calculate', the resource 'TDS', and the tax year 'FY2025-26'. It lists specific applicable scenarios (contractor payments, professional fees, etc.), distinguishing it from sibling tools like 'calculate_income_tax' which cover broader tax calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: 'Use when computing withholding tax on contractor payments, professional fees, interest, rent, commissions, or purchase of goods.' This gives clear positive guidance, but it does not mention when not to use or explicitly name alternative tools, which slightly reduces the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose readOnly and idempotent hints. Description adds that validation checks structure and flags, consistent with read-only operation. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. Purpose and usage are front-loaded, making it easy to grasp.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given single parameter and presence of output schema (context signals), description is adequate. Could mention return value but output schema likely covers it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description 'AA consent artifact JSON'. Description adds no further parameter semantics beyond what schema provides. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('validate'), the resource ('AA consent artifact'), and scope ('structure and flags'). It distinguishes from sibling tools like 'build_aa_consent_request' and other validation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'when verifying consent artifacts received from AA before processing'. Provides clear usage context, though does not mention when not to use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, so the agent knows it's a safe read operation. The description adds that the tool decodes details, implying extra functionality beyond format validation. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence states the action, the second gives the use case. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one parameter, annotations providing safety guarantees, and existence of an output schema (though not shown), the description sufficiently covers the tool's purpose and usage. The decoded details are presumably documented in the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter, with the schema already providing format and example. The description does not add parameter-specific details beyond the schema, so it meets baseline expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool validates FSSAI license number format and decodes details. This is a specific verb-resource combination that distinguishes it from sibling validation tools for other document types (e.g., PAN, GSTIN).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: 'Use when verifying food business operator licenses in compliance checks.' This provides clear context, though it does not include explicit exclusions or direct comparisons with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the tool is known to be safe and idempotent. The description adds value by revealing checksum verification and decoding behavior, which enriches the agent's understanding beyond structural hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: first states action and key feature (checksum verification), second provides usage context. Every sentence is purposeful, no fluff, and front-loaded with crucial information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (context signals confirm), the description does not need to detail return values. It covers purpose, usage, and a behavioral trait (checksum). Missing error conditions or edge cases, but overall complete for a validation tool with rich annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the input schema already describes the gstin parameter (type, length, allowed characters). The description adds no further parameter-level details, so the baseline score of 3 applies; it does not improve or worsen parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates and decodes an Indian GSTIN with checksum verification, making the action and resource specific. It distinguishes from sibling validators like validate_pan or validate_aadhaar by explicitly naming GSTIN and mentioning checksum, with use case examples.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies when to use the tool: 'before invoicing, reconciliation, or compliance workflows.' While it provides clear context, it does not explicitly exclude alternatives or note when not to use it, but the sibling tool list helps differentiate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint; description adds only 'for TDS compliance' context, not substantial behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with action, no redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values need not be described; tool is simple and description covers usage context sufficiently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters; description adds example format '10-character TAN (e.g., ABCD12345E)', providing helpful illustration beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Validate TAN format' with specific resource (TAN) and action (validate), distinguishing it from other validate_* sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context 'Use when verifying TAN format for TDS compliance', giving clear usage direction without needing to specify alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the tool is read-only and idempotent (readOnlyHint=true, idempotentHint=true). The description adds valuable context: it 'decodes known provider handles,' which implies the tool provides additional information beyond a simple pass/fail. There is no contradiction with annotations, and the description enhances understanding of the tool's output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. The first sentence states the core function, and the second explains when to use it. Every word is meaningful, and the information is front-loaded. No unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input schema (one parameter), clear annotations, and the presence of an output schema (as indicated by context signals), the description provides the necessary context for an agent to decide when to call the tool. It could briefly mention that it does not validate against live systems, but the current description is largely adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the 'vpa' parameter already includes a description and example). The tool description does not add new semantic information about the parameter beyond what the schema provides. Baseline is 3, and no extra value is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Validate UPI VPA structure and decode known provider handles.' It uses a specific verb ('validate') and resource ('UPI VPA'), and distinguishes itself from sibling tools (e.g., validate_pan, validate_gstin) by focusing on UPI addresses. The additional context about 'before payment routing' reinforces the specific use case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'Use when checking whether a UPI address is structurally valid before payment routing.' This tells the agent when to use the tool. While it does not explicitly state when not to use or mention alternatives, the sibling list makes it clear that this is the only tool for UPI VPA validation, so the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true; the description adds that it provides due dates and amounts, aligning with safe behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with front-loaded purpose, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With full schema coverage and an output schema, the description adequately covers purpose, usage, and output without needing further detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with detailed parameter descriptions; the tool description adds no extra parameter context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates quarterly advance tax installment schedule per legal sections 234B and 234C, distinguishing it from sibling tax tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use when planning quarterly tax payments to avoid interest penalties', providing clear usage context, though lacks explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and idempotentHint=true, indicating safe, repeatable operation. The description adds behavioral context by stating it produces a 'year-by-year amortization schedule', which informs the agent about the output structure beyond what annotations cover. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the core purpose ('Calculate EMI for a loan with year-by-year amortization schedule') followed by usage guidance. No redundant or unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters fully described in the schema, an output schema available (as per context signals), and annotations that cover safety and idempotency. The description completes the picture by clarifying the scope (year-by-year schedule) and use cases, making it comprehensive for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are already documented in the input schema. The description does not add new semantic details beyond what is in the schema, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates EMI with a year-by-year amortization schedule, specifying the verb 'Calculate' and the resource 'EMI for a loan'. It distinguishes itself from sibling tools like calculate_gst or validate_pan by focusing on loan EMI computation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Use when computing loan EMIs, comparing loan options, or planning prepayment strategies.' This tells the agent when to invoke the tool, but it does not mention when not to use it or offer alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, deterministic computation. The description adds no new behavioral traits beyond 'Calculate', so it provides minimal additional transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two short, efficient sentences with zero redundancy. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given full schema descriptions for 4 parameters, annotations for safety/idempotency, and an output schema, the description is complete. It effectively states purpose and usage guidelines, covering all necessary context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters have descriptions. The tool description does not add extra meaning beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate SIP with annual step-up increment', which is a specific verb+resource. It distinguishes this tool from the sibling 'calculate_sip_returns' which presumably handles flat SIP.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'Use when comparing step-up SIP vs flat SIP or planning salary-linked investments.' This gives clear context and suggests when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint. Description adds behavioral detail about the two query modes (exact code vs keyword search), which is beyond what annotations provide. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences: first states action, second provides usage context. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (2 optional params, output schema present) and sibling tools unrelated to HSN, the description fully covers the tool's purpose and usage without needing to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and both parameters have descriptions in the schema. The description references the two modes but adds no additional semantic detail beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Lookup HSN/SAC by exact code or search by keyword', providing a specific verb and resource with two clear modes. No sibling tool overlaps with HSN lookup, so differentiation is implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use for GST classification workflows where users provide a code or only a product keyword', giving clear context. Does not mention when not to use or alternatives among siblings, but context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly and idempotent hints. The description adds valuable behavioral context about data source (bundled dataset with live fallback), which supplements 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Front-loaded with core function, then usage context. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description adequately covers data source, use cases, and the single parameter. No gaps for a simple lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema already provides full description (100% coverage) with example and length constraints. The description adds no additional meaning beyond what the schema offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'look up' and resource 'IFSC code', clearly stating it retrieves bank branch details with a bundled dataset and live fallback. It distinguishes itself from siblings like 'bulk_validate_ifsc' by implying single-lookup use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: for bank branch details from IFSC in invoices, onboarding forms, or payment validation. While no explicit when-not or alternatives are given, the context is clear and the sibling tool names imply bulk validation alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only and idempotent. Description adds that it returns all post offices, providing output context 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: function statement then use cases. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, description adequately covers input and use cases. Mentions return of post offices, sufficient for a straightforward lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers parameter completely with description '6-digit pincode' and length constraints. Description adds no extra semantics beyond reinforcing 'pincode' role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies verb 'look up', resource 'India pincode details', and outcome 'return all post offices'. Clearly distinguishes from sibling validation/lookup tools by focusing on pincodes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists use cases (address normalization, district/state extraction, GST crosswalk). No explicit when-not-to-use, but use cases sufficiently guide agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint. Description adds the Verhoeff checksum algorithm, providing useful behavioral detail 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action and algorithm, followed by usage context. No redundant or vague language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, annotations, and output schema, the description is complete: it defines purpose, algorithm, and use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description (12-digit, spaces/hyphens, example). The tool description adds no extra parameter info, so baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates an Aadhaar number using Verhoeff checksum, distinguishing it from sibling tools that validate other Indian identifiers (PAN, GSTIN, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (KYC, identity verification, government benefits), though no explicit when-not-to-use is given. Context from sibling tools makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds value by stating 'detect operator/circle', which hints at the return content. No contradictions; the description complements annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, front-loaded sentences with no extraneous information. Every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the annotations cover safety, the input schema fully describes the parameter, and an output schema exists, the description is complete enough for an AI to decide when and how to use this simple validation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (parameter 'mobile' described as '10-digit mobile number with or without +91/0'). The description does not add any new meaning beyond the schema, so baseline score 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Validate Indian mobile number and detect operator/circle', which is a specific verb+resource. It also provides a usage context, distinguishing it from sibling validation tools for other entities (e.g., Aadhaar, PAN, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use when validating mobile numbers for KYC or contact verification', providing clear context for when to use. However, it does not mention when not to use or list alternative tools, but given the sibling list, alternatives are implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint as true, indicating a safe, read-only operation. The description adds value by explaining the internal logic ('compares three conditions and takes minimum'), providing useful behavioral insight beyond annotations. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: three sentences with no wasted words. The first sentence states the core purpose, and subsequent sentences add usage and logic. Front-loaded and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, 3 required) and the presence of an output schema, the description is complete. It covers purpose, usage context, internal logic, and is self-contained. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so every parameter already has a clear description in the schema. The tool description adds minimal extra meaning (e.g., 'compares three conditions' gives context), but does not significantly enhance parameter understanding beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate House Rent Allowance (HRA) exemption under Section 10(13A).' It uses a specific verb-resource combination and distinguishes from sibling calculation tools like calculate_advance_tax and calculate_income_tax.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context: 'Use when computing tax-exempt HRA component for salary structuring or income tax filing.' It also notes the tool compares three conditions and takes the minimum, but does not explicitly mention when not to use or list alternatives, which would elevate to a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so safety and idempotence are covered. Description adds the Luhn check detail, which is a behavioral trait beyond annotation, enhancing transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, zero wasted words. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with one parameter and output schema present (not shown but indicated). Description sufficiently covers validation usage context, leaving no gaps for an agent to misunderstand.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, baseline is 3. Description adds value by providing a format example 'e.g., INE1234567890' and specifying '12-character', which clarifies the parameter beyond the schema's 'string' type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Decode' and resource 'ISIN (International Securities Identification Number)' with specific detail 'Luhn check'. It distinguishes from siblings like validate_pan, which are pure validations, by being a decode operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises 'Use when validating ISIN for Indian securities', providing clear context. However, it does not mention when not to use it or point to alternatives among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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