developer-tools

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

Annotations are absent, so the description must fully disclose behaviors. It does not mention that AES-GCM uses an IV/nonce (presumably auto-generated), that the output format includes IV+tag+ciphertext, or that decryption requires the exact password and original ciphertext. No information about error handling or security implications (e.g., password strength) is provided.

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

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

The description is brief at three sentences, but it contains a minor typo ('ciphertext' instead of 'ciphertext') and could be more tightly structured. It front-loads the purpose and operation list, which is helpful. No unnecessary content.

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

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

Given no output schema, the description should clearly state the return format of encrypt (base64 string containing IV+ciphertext+tag) and decrypt (plaintext). It only says 'base64 ciphertext' which is insufficient. Error conditions (wrong password, tampered ciphertext) are not mentioned. The open-ended 'options' parameter leaves significant gaps.

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

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

Although schema coverage is 100%, the description adds little value. The 'options' parameter is explained only by referencing an external schema URL, leaving crucial parameters like 'password' undocumented. The description does not clarify what keys 'options' accepts, such as password or iv. This fails to compensate for the schema's vagueness.

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

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

The description states it performs AES-GCM encryption and decryption, but fails to specify how the password is provided. The schema does not include a password parameter, and the description only mentions 'using a password' without clarifying if it's passed via options or elsewhere. This omission undermines purpose clarity.

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

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

No guidance is given on when to use this tool versus sibling tools like 'hash', 'base64', or 'bcrypt'. There are no mentions of prerequisites, security considerations, or scenarios where decryption might fail. The description merely lists operations without contextual usage advice.

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

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

No annotations provided, and description does not disclose side effects, limitations, or error behavior. It is a read-like operation but not explicitly stated.

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

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

Relatively short but contains double periods and an awkward structure. Each sentence earns its place, but formatting could be improved.

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

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

No output schema or annotations, description does not explain return format, the options structure (additionalProperties), or which bases are supported, leaving gaps for the agent.

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

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

Schema coverage is 100%, so description adds marginal value. It reiterates operation types and roles of input/options but 'several bases' hint is not detailed in schema or description.

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

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

Description clearly states the tool converts text to/from character codes and lists two operations. However, it mentions 'several bases' without specifying which, and the enum only has to-codes and from-codes, not base options.

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

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

No guidance on when to use this tool versus alternatives (e.g., base64, char-inspector). Only a generic call format is given, lacking context for selection.

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

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

No annotations are provided, so the description carries the full burden. It clearly declares the tool performs encoding and decoding, which are inherently safe and reversible operations. It does not hide any behavioral details, though it could mention edge cases like invalid input.

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

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

The description is relatively short but contains punctuation issues (double periods, semicolon) that detract from clarity. It front-loads the purpose but could be more polished. Every sentence earns its place, but formatting reduces effectiveness.

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

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

Given the tool's simplicity, no output schema is needed, and the description adequately covers inputs. It does not mention return formats or error handling, but for a straightforward encode/decode tool, this is sufficient. The schema covers 100% of parameters.

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

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

The input schema already defines the three parameters with descriptions. The description adds value by explicitly explaining the operation enum values ('encode' and 'decode') and their meanings, which goes beyond the schema's basic description.

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

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

The description clearly states the tool's purpose: encoding and decoding text in multiple formats (Base64, Base64URL, Base32, Base58, Base85, hex). This distinguishes it from sibling tools like aes-encrypt or hash, which handle different encoding types.

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

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

The description provides the call pattern (operation, input, options) but offers no guidance on when to use this tool versus alternatives like url-encode or html-entity. It does not explain exclusion criteria or provide context for selecting among the many sibling encoding tools.

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

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

Without annotations, the description must disclose behavior. It mentions the two operations and that cost is used for hashing, but omits details like default cost, output format (hash string vs boolean), error handling, or side effects. Some transparency is provided, but significant gaps remain.

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

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

Description is short and front-loaded with the key purpose. It is efficient but has minor redundancy (repeats operations in a list and then in a sentence). No extraneous content.

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

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

Given the lack of an output schema, the description should explain return types (e.g., hash string for hash, boolean for verify). It fails to do so, leaving agents guessing about what the tool returns. This is a significant gap for a tool with no output schema.

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

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

Schema coverage is 100%, so baseline is 3. The description adds marginal value by clarifying that 'input' is the password or hash depending on operation, and that 'options' may be relevant. However, the 'options' description defers to an external schema, not adding much.

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

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

Description clearly states the tool does bcrypt hashing and verification, listing the two distinct operations ('hash' and 'verify'). It distinguishes itself from sibling tools like 'hash' and 'password' by specifically naming bcrypt and its purpose.

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

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

The description explains basic usage (calling with operation, input, and optionally options) but does not explicitly guide when to use bcrypt over alternatives like generic 'hash' or 'password' tools. Usage context is implied rather than made explicit.

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

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

With no annotations, the description carries the full burden. It mentions 'options where relevant' but does not disclose behavior for edge cases, invalid input, or what the 'options' object expects. The reference to an external schema at '/api/v1/case' is vague and not helpful inline.

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

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

The description is concise with two sentences and a bullet-like list for operations. It is front-loaded with the main purpose. However, the structure could be improved by separating the operations more clearly, but it is not verbose.

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

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

The description does not explain the return values or output format, which is problematic given no output schema. For the 'all' operation, it likely returns multiple cases, but this is not specified. The nested 'options' object is also left unexplained, making the description incomplete for a tool with complex parameters.

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

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

Schema coverage is 100%, so baseline is 3. The description adds little beyond the schema, merely restating that the tool should be called with 'operation' and 'input' and optionally 'options'. No additional meaning or constraints are provided.

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

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

The description clearly states the tool's purpose: 'Convert text between camelCase, snake_case, kebab-case and more.' It specifies two operations ('convert' and 'all'), making it distinct from sibling tools like 'aes-encrypt' or 'base64' which serve different purposes.

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

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

The description implies usage for text case conversion and instructs to call with 'operation' plus 'input' and optionally 'options', but it does not explicitly state when to use this tool vs alternatives, nor does it provide any exclusions or when-not-to-use guidance.

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

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

With no annotations, the description carries full burden. It transparently explains the operation's behavior: inspecting each character and returning code point, category, and bytes. It implies a read-only, non-destructive action, though it does not explicitly state safety 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.

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

The description is concise with two sentences. It front-loads the core action. Minor typographical issues (double periods) do not significantly detract.

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

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

No output schema exists, so the description should hint at return structure. It mentions outputs (code point, category, bytes) but not how they are organized or formatted. Adequate for a simple tool, but could be more complete.

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

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

Schema description coverage is 100%, so baseline 3. The description adds minimal value beyond schema: it restates the operation and input parameters. It does not elaborate on 'options' or provide examples.

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

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

The description clearly states it breaks a string into per-character Unicode details, listing specific outputs (code point, category, bytes). The verb 'inspect' and resource 'character' are specific. It distinguishes from sibling tools which are mostly about encoding, hashing, or formatting, not character-level inspection.

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

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

The description provides basic usage instructions ('Call with operation plus input and options'), but lacks guidance on when to use this tool versus alternatives. It does not mention any contexts where this tool is preferred or excluded.

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

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

No annotations, so description must carry weight. Mentions output nature (symbolic string and description) but lacks details on return format, error handling, or any 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.

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

Relatively concise but has a typo (double period) and could be more structured. Two sentences cover the core, but not every word earns its place.

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

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

For a simple conversion tool with complete schema coverage, the description adequately explains both operations and output expectation, despite lacking output schema.

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

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

Schema coverage is 100%, so baseline is 3. Description repeats operation list but adds little beyond schema: only clarifies 'input' is primary and 'options' are optional.

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

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

Clearly states converting between octal and symbolic Unix permissions. Lists two specific operations with examples, distinguishing it from sibling encoding tools.

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

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

Gives basic calling pattern ('Call with operation plus input and options where relevant') but no explicit when-to-use or when-not-to-use compared to alternative tools.

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

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

No annotations provided; description only states what it does (parse, calculate). Does not disclose side effects or idempotency, but tool is inherently read-only. Acceptable, not exceptional.

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

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

Two sentences: first states purpose, second states operation and call pattern. No unnecessary words.

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

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

No output schema, but description names returned fields. Missing error conditions or format details, but adequate for a simple parse tool. Context signals indicate it's straightforward.

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

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

Schema covers all parameters with descriptions (100%). Description adds usage pattern but no new semantics. Options parameter references external schema vaguely.

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

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

Clear verb 'Parse' and resource 'CIDR block', with specific outputs. Distinct from siblings which are other encoding/formatting tools.

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

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

Explicitly states the operation 'calculate' and call pattern with operation, input, and optional options. Does not exclude alternatives but purpose is self-explanatory.

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

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

Discloses that convert expects HEX input and returns all spaces, and palette generates harmony palettes. However, without annotations, lacks detail on error behavior, validation, or output format. Adequate but not thorough.

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

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

Three sentences, front-loaded with purpose, then operations. No redundant text. Though structured with semicolons, it is efficiently concise.

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

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

No output schema, but description does not specify return format (e.g., object with color codes for convert, array of colors for palette). Also missing error handling or input validation details. Incomplete given the tool's simplicity.

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

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

Schema coverage is 100%, so baseline is 3. The description adds little beyond the schema: 'input' is primary string, 'options' references an external schema. Does not clarify options for each operation.

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

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

The description clearly states the tool converts colors between spaces and generates palettes, with two explicit operations. However, it does not differentiate from the sibling 'color-palette', which likely overlaps on the palette operation, slightly diming clarity.

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

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

Minimal guidance: 'Call with operation plus input and options where relevant.' No when-to-use or when-not-to-use advice, no mention of alternatives like color-palette, and no prerequisites for input format.

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

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

No annotations are provided, so description carries full burden. It states generation but doesn't disclose whether it's read-only, auth requirements, rate limits, or any side effects. Minimal behavioral context.

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

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

Description is short but contains redundant phrasing ('Generate harmony, shade and tint palettes from a base HEX color.' repeated twice). Efficient front-loading, but typographical issues detract.

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

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

No output schema provided; description fails to explain return values (e.g., structure of palettes). Also missing error handling or example usage. For a tool with 3 parameters and no output schema, more context is needed.

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

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

Input schema has 100% coverage, so description doesn't need to add much. It clarifies that 'input' is a base HEX color, which adds value beyond schema's generic string. However, options are left vague and description only references external schema.

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

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

Description clearly states it generates harmony, shade, and tint palettes from a base HEX color, with specific verb 'generate' and resource 'color-palette'. It distinguishes itself from siblings like 'color' and 'contrast' by focusing on palette generation.

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

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

Description provides explicit call pattern: 'Call with operation plus input (and options where relevant)'. It gives clear usage context, though doesn't 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.

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

No annotations are provided, so the description carries full responsibility. It discloses that 'check' computes contrast ratio and pass/fail, and 'best-text' picks black or white text. However, it does not detail error handling, permissions, or output structure beyond these minimal descriptions.

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

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

The description is reasonably concise, front-loading the core purpose and then listing operations. There is slight repetition, but overall it is efficient and well-structured.

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

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

For a tool with 3 parameters and no output schema, the description explains the operations and parameter usage. However, it lacks details on the exact return format (e.g., JSON structure) and the specifics of the 'options' parameter, leaving some gaps for the agent.

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

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

Schema coverage is 100%, so baseline is 3. The description adds minor context by explaining the roles of 'operation', 'input', and 'options', but does not provide substantial additional meaning beyond the schema definitions.

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

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

The description clearly states the tool checks WCAG contrast between colors, with specific operations ('check' and 'best-text'). It distinguishes itself from siblings like 'color' by focusing on contrast and WCAG compliance.

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

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

Provides clear usage instructions: call with operation, input, and optionally options. However, it does not explicitly state when to use this tool versus alternatives like the 'color' tool, though the context is reasonably clear.

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

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

Without annotations, description must cover behavior. It lists two operations and their functions. Missing details on error handling, output format, or validation. For a compute-only tool, this is adequate but not comprehensive, so score 3.

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

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

The description is concise but contains double periods and a list that could be better formatted. It efficiently conveys the tool's purpose and two operations, but minor structure issues prevent a higher score.

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

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

For a tool with 3 params (2 required, one nested), no output schema, the description covers operations and basic usage but doesn't explain options content or return value. It's complete enough for a simple cron tool but could provide more context on options and error cases.

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

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

Schema coverage is 100%, but the input parameter description is generic ('primary input string') and doesn't specify it's a cron expression. The description in text mentions cron expressions, so agents can infer. Options parameter is vague. Baseline 3, with some added value from main description.

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

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

The description clearly states it handles cron expressions with two operations: describe and next-runs. It distinguishes from siblings (mostly text utilities) by focusing on cron scheduling. However, it could be more direct about parsing and computing, so score 4.

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

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

Provides basic usage pattern: call with operation, input, and optionally options. No guidance on when not to use or alternatives. Siblings include many single-function tools, but no explicit differentiation, so score 3.

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

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

No annotations; description mentions operations but does not disclose error behavior or limitations. Adequate for a simple transformation tool.

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

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

Description is short and front-loaded with purpose, but contains double periods and slightly awkward phrasing. Could be more polished.

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

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

Covers the two operations and hints at options. No output schema, but for a transform tool it is sufficiently complete.

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

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

Adds meaning beyond schema by explaining what each operation does (strip comments for minify, one declaration per line for beautify). Schema coverage is 100% but description enhances parameter understanding.

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

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

Description clearly states 'Minify or beautify CSS' with specific operations listed. Distinguishes from sibling tools which are all different utility categories.

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

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

Provides basic usage guidance 'Call with operation plus input (and options where relevant)'. Not explicit about when to use vs alternatives, but siblings are distinct.

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

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

No annotations are provided, so the description must disclose behavior. It mentions only the 'convert' operation and that options may be relevant, but omits details about input format, error handling, exact conversion logic, or whether all unit pairs are supported. This is insufficient for a tool with no annotations.

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

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

The description is short and front-loaded with the main purpose. However, it is slightly redundant (two sentences about 'convert') and could be more concise by merging sentences. Overall efficient.

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

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

With three parameters and no output schema, the description provides the essential purpose but lacks details on the input string format (e.g., '10px to rem') and the 'options' object. It is adequate for a simple conversion tool but not fully complete.

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

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

Schema description coverage is 100%. The description adds value by explaining the operation enum and listing the CSS units, which clarifies the intended use of 'input' and 'operation'. It goes beyond the schema's generic parameter descriptions.

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

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

The description clearly states it converts a numeric value between CSS units, lists supported units (px, rem, em, pt, pc, %), and names the only operation 'convert'. This specificity distinguishes it from siblings like base64 or json.

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

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

The description says to call with 'operation' plus 'input' and optionally 'options', providing basic invocation guidance. It does not explicitly state when to use this tool over alternatives, but the unique focus on CSS units implicitly excludes other conversion tools.

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

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

No annotations are provided, so the description carries the full burden. It does not mention side effects, safety, or error behavior, but the conversion nature implies no destructive actions. Adequate but not rich.

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

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

The description is two sentences, the first stating purpose and the second explaining call structure. It is concise and front-loaded, though there is a minor typo (double period).

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

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

Given the tool has three parameters with full schema coverage and no output schema, the description adequately covers the tool's function and calling pattern. It implies the return value is code snippets, which suffices.

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

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

Schema coverage is 100%, so the schema already documents all parameters. The description repeats the operation and input semantics but adds no extra meaning beyond what the schema provides.

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

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

The description clearly states the tool converts a curl command into fetch, Python, or Node snippets, using a specific verb and resource. It distinguishes itself from sibling tools which are all different converters (e.g., base64, bcrypt), so no confusion.

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

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

The description explains the required call structure: operation plus input, with optional options. While it doesn't explicitly say when not to use, the context of sibling tools (all different) makes it clear this is for curl-to-code conversion.

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

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

No annotations provided, so the description must carry the burden of behavioral disclosure. It states the tool parses and converts data sizes, implying a read-only operation. However, it does not explicitly confirm non-destructiveness or mention any side effects, authentication needs, or rate limits.

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

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

The description is short but contains repetition (two sentences stating the same conversion purpose) and a punctuation error (double period). It could be more concise and front-loaded with essential information.

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

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

Given the low complexity and full schema coverage, the description adequately covers the tool's purpose. However, it lacks information about the return format, and with no output schema, the agent may not know exactly what data is returned after conversion.

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

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

Schema coverage is 100%, so the schema already documents all parameters. The description adds the pattern 'Call with operation plus input (and options where relevant)', which reinforces usage but does not provide new semantic meaning beyond the schema.

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

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

The description clearly states the tool parses a data size and converts it to bytes plus decimal and binary units, with the specific operation 'convert'. This distinguishes it from sibling tools like 'aes-encrypt' or 'base64' which handle different data types.

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

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

The description provides minimal usage guidance (call with operation and input), but does not specify when to use this tool versus alternatives or when not to use it. No exclusions or alternative recommendations are mentioned.

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

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

No annotations are provided, so the description must fully disclose behavior. It mentions operations and parameters but fails to describe important traits like how to input two texts, authentication needs, side effects, or error behavior, leaving significant gaps.

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

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

The description is concise with only two sentences. It front-loads the purpose but the second sentence is slightly messy with semicolons and could be more structured. Overall, it earns its place without unnecessary words.

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

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

Given no output schema and no annotations, the description is incomplete. It does not explain return values for the two operations, how to format the 'input' parameter for two texts, or any limitations. This is insufficient for a tool with moderate complexity and multiple operations.

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

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

Schema coverage is 100%, but the description adds confusion by mentioning 'two texts' while the schema has only one 'input' string. The 'options' parameter is not described, just referenced to an external URL. The description repeats the schema structure without adding meaningful semantics.

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

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

The description states 'Compute a line-by-line diff between two texts' and lists two operations, which clearly indicates the tool's purpose. However, it does not clarify how to specify two texts given the input schema has only one 'input' parameter, which reduces clarity.

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

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

The description implies the tool is for text diffing but offers no explicit when-to-use or when-not-to-use guidance. Sibling tools like 'json-diff' exist, but the description does not differentiate from them, leaving the agent to infer usage context.

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

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

No annotations are provided, so the description carries the full burden. It does not disclose any behavioral traits beyond stating the two operations. There is no mention of side effects, permissions, rate limits, or any constraints. The tool's behavior is underspecified for a mutation-like operation ('generate' implying creation).

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

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

The description is fairly concise at two sentences (plus a brief operation list). It is front-loaded with the purpose. However, the structure is slightly awkward with the list of operations in the middle and a call pattern at the end. A more structured or bulleted format would improve clarity.

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

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

Given there is no output schema, the description should explain the return values (e.g., for 'generate' it returns a .gitignore content, for 'templates' it returns a list of keys). It also does not specify the input format (e.g., separate keys how?). The description is incomplete for a tool with two distinct operations and no output schema.

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

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

Schema description coverage is 100% (all parameters have descriptions). The tool description adds minimal value beyond the schema: it clarifies that 'generate' combines one or more template keys and 'templates' lists available keys. However, it does not specify the format of the 'input' parameter (e.g., comma-separated keys) or the structure of 'options'. Baseline 3 is appropriate.

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

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

The description clearly states it generates a combined .gitignore from template keys and lists two specific operations: 'generate' and 'templates'. This distinguishes the tool from its siblings (which are all other utilities like encryption, encoding, etc.) and gives a specific verb+resource. However, it could be more precise about what 'combined' means (e.g., merging multiple templates).

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

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

The description includes a call pattern ('Call with 'operation' plus 'input' (and 'options' where relevant)') which provides basic usage guidance. But it lacks explicit when-to-use vs. when-not-to-use directions, and no alternatives are mentioned despite the presence of many sibling tools. Guidance is minimal.

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

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

No annotations are provided, so the description bears the full burden. It lists supported algorithms and operations but does not disclose output format, error behavior, rate limits, or whether input encoding matters. The behavioral transparency 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.

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

The description is three sentences, but the first sentence has an unnecessary double period ('..') and the second sentence defines operations in a list format that is not strictly necessary. It could be more concise and better formatted.

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

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

Given no output schema and no annotations, the description should clarify return values and behavior. It does not mention what the tool returns (likely a digest string) nor details about the 'options' parameter. The tool requires more context for safe invocation.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds some context (e.g., input is the primary string, operation is an enum, options are optional) but does not significantly enhance understanding beyond the schema. The reference to an external schema for options is not helpful inline.

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

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

The description clearly states that the tool computes various hash algorithms (MD5, SHA, CRC32, HMAC) and lists two operations: hash and hmac. This gives a specific verb and resource, distinguishing it from many siblings. However, it is slightly verbose and the presence of a sibling tool named 'hmac' could cause confusion.

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

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

The description only says 'Call with operation plus input (and options where relevant).' It provides no guidance on when to use this tool versus alternatives (e.g., the sibling 'hmac' tool). There is no mention of when not to use it or how it compares to other hashing tools.

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

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

No annotations are provided, so the description carries the burden. It mentions SHA-2 but does not specify how the secret key is supplied (there is no key parameter in the schema), nor does it describe output format or side effects. This is a significant omission.

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

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

The description is reasonably concise with three sentences, though there is a minor formatting issue (double period). It front-loads the main purpose.

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

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

Given no output schema, the description should explain what the tool returns (e.g., the HMAC signature). It also omits how to provide the secret key, which is essential for HMAC. The tool is simple but key details are missing.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context about the operation and input but does not elaborate on the 'options' parameter or the format of the input. It references an external schema for options, which is suboptimal.

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

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

The description clearly states the tool 'signs a message with HMAC using a secret key and SHA-2 algorithm', providing a specific verb and resource. It is distinct from siblings like hash or aes-encrypt.

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

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

The description explains how to call the tool with 'operation' and 'input', and mentions 'options' where relevant, but does not provide guidance on when to use HMAC over alternatives or when not to use it.

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

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

Without annotations, the description transparently defines each operation's effect: format pretty-prints, minify strips comments/collapses whitespace, validate checks tags. No hidden side effects or omissions.

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

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

Description is concise, uses bullet-pointed list for clarity, and front-loads the main purpose. Could trim '..' double dots.

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

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

No output schema, and description does not specify return format (e.g., transformed string, validation errors). For a validation tool, this is a gap. Otherwise covers core usage.

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

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

Schema coverage is 100%, but description adds value by listing valid operation enum values explicitly. The 'options' description directs to external schema, which is less helpful but not harmful.

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

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

The description clearly states the tool handles HTML with three specific operations (format, minify, validate), distinguishing it from siblings like css-minify or json.

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

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

The description provides basic call structure ('Call with operation plus input and options where relevant') but lacks guidance on when to use this tool over alternatives or prerequisites.

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

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

No annotations are present, so the description carries the full burden. It explains the two operations but does not disclose any behavioral traits such as idempotency, error handling, rate limits, 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.

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

The description is exceptionally concise, using only three short sentences to convey the core functionality and call syntax. No unnecessary words.

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

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

The description is adequate for a simple tool but lacks detail on options, return format, error states, or example usage. Without an output schema, more behavioral context would improve completeness.

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

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

The schema covers all parameters (100% coverage). The description adds minimal value by explaining operations ('encode' and 'decode') which are already clear from the enum. The 'options' parameter is vaguely described as 'where relevant'.

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

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

The description clearly states the tool's purpose: encoding/decoding HTML entities with specific entity types (named, decimal, hex). This distinguishes it from sibling tools like base64 or url-encode.

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

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

The description implies usage by specifying the required parameters ('operation' and 'input') and notes that 'options' may be relevant. However, no explicit guidance on when to use versus alternatives or when not to use is provided.

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

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

With no annotations provided, the description carries the full burden. It discloses the operations (lookup, search) but does not explicitly mention that the tool is read-only, idempotent, or any potential side effects. However, the straightforward nature of the tool makes this acceptable.

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

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

The description is relatively concise, using two sentences to cover purpose and operations. It front-loads the core idea, though it includes a minor formatting issue (double period).

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

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

Given no output schema and a simple tool, the description explains the operations and parameter usage. However, it lacks details about output format, error handling, and the 'options' parameter (which references an external schema), making it moderately complete.

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

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

Schema coverage is 100%, providing baseline 3. The description adds value by explaining the two operations and how they relate to parameters (e.g., 'lookup — Look up a single status code by number'), offering contextual meaning beyond the schema.

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

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

The description clearly states the tool's purpose with specific verbs ('look up', 'search') and a concrete resource ('HTTP status codes'). It distinguishes itself from sibling tools (various encoding/formatting utilities) by focusing on a specific domain.

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

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

The description implies the tool is used for querying HTTP status codes and provides basic calling instructions ('Call with operation plus input'), but does not explicitly state when to use this tool over alternatives or include any when-not-to-use guidance.

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

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

No annotations are provided. The description does not disclose behavioral traits such as whether the tool is read-only or destructive, rate limits, output format, or the fact that only the 'build' operation is currently available.

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

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

The description is short and front-loads the purpose, but contains awkward punctuation (double periods) and is slightly disjointed. It is adequate but could be clearer.

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

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

Given the tool has 3 parameters with one enum and no output schema, the description is incomplete. It does not mention return values, behavior on failure, or any distinction between building and parsing.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds little beyond stating the required parameters; it does not explain what 'input' should contain or what 'options' are available.

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

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

The description mentions 'Build and parse base64 data URIs and embed snippets', but only provides one operation 'build-snippets'. This creates ambiguity about the 'parse' functionality. The purpose is somewhat clear but inconsistent.

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

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

The description only states to call with 'operation', 'input', and optionally 'options'. It provides no guidance on when to use this tool versus siblings like 'base64' or 'url-encode', nor when not to use it.

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

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

With no annotations, the description must fully disclose behavior. It describes each operation's effect: formatting with configurable indent, minification by stripping whitespace, validation with error location, and repair of common mistakes. This is clear and sufficient for a read-only utility tool, though it lacks explicit safety or state change warnings.

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

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

The description is relatively short but suffers from inconsistent punctuation (periods then semicolons) and a run-on structure. It mixes complete sentences with fragment lists, making it slightly harder to parse. Could be more concise and front-loaded.

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

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

The description covers the tool's operations and parameters adequately given its simplicity. However, it lacks explicit mention of return values (e.g., formatted string for 'format', boolean or error for 'validate'). Without an output schema, the agent relies on this description, which is partially complete.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the 'operation' enum values in detail and providing a usage pattern ('Call with operation plus input'). This goes beyond the schema's property descriptions to clarify how parameters interact.

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

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

The description clearly states the tool's purpose: formatting, minifying, validating, and repairing JSON. The verb 'Format, minify, validate and convert' is specific, though 'convert' is not present as an operation. The name 'json' and operations effectively distinguish it from siblings like json-diff or json-schema by focusing on core JSON manipulation.

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

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

The description gives minimal usage instructions ('Call with operation plus input') but provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, such as when to use json-csv for conversion or json-schema for validation, leaving the agent to infer context.

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

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

With no annotations provided, the description bears the full burden of disclosing behavioral traits. It merely states the conversion types without detailing side effects, error handling, performance characteristics, or format specifics (e.g., delimiter handling). This leaves considerable uncertainty about tool behavior.

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

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

The description is short but contains a typo (double period) and disjointed phrasing ('Operations: ' followed by semicolon-separated items). It front-loads the main purpose but could be more streamlined and well-structured.

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

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

The tool performs conversions and has no output schema, so the description should clarify output formats. It fails to mention that output is a string (CSV or JSON array) or explain how options affect behavior. For a tool with nested object parameters and no output schema, the description is incomplete.

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

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

Schema description coverage is 100% for the three parameters, but the description adds little beyond the schema. It repeats the operation and input concepts and references an external schema for options. It provides no additional meaning or constraints that the schema doesn't already cover.

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

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

The description clearly states the tool converts between JSON and CSV and lists the two specific operations ('json-to-csv' and 'csv-to-json'). It specifies the verb 'convert' and the resources 'JSON' and 'CSV', making the purpose unambiguous.

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

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

The description provides basic usage instructions ('Call with operation plus input') but does not explicitly tell when to use this tool versus alternatives. There is no mention of prerequisites or scenarios where other tools (like json or csv) would be better suited. Usage is implied but not guided.

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

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

No annotations are provided, so the description carries full burden. It states the tool compares JSON documents and reports changes, but it does not clarify how two documents are passed via a single 'input' string, nor does it disclose the return format, auth needs, or any side effects. The phrase 'by path' is vague.

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

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

The description is functional but somewhat redundant and poorly punctuated. It could be more concise and structured, e.g., front-loading the core action and then specifying parameters.

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

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

Given the absence of an output schema and the complexity of comparing two JSON documents, the description is incomplete. It does not explain how to provide the two documents (single string input), what output structure to expect, or what options are available. This leaves significant gaps 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.

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

Schema description coverage is 100%, so baseline is 3. The description reiterates the call pattern but adds little beyond the schema. The 'options' parameter is referenced vaguely ('see tool schema') without further clarification, so it does not significantly enhance understanding.

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

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

The description clearly states that the tool compares two JSON documents and reports differences, specifying the 'diff' operation. It mentions paths and the required call pattern. However, it does not explicitly differentiate from sibling tools like the text 'diff' tool, relying on the 'json' context.

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

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

The description provides no guidance on when to use this tool versus alternatives (e.g., text diff or other JSON tools). It does not specify prerequisites, typical use cases, or when not to use it.

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

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

With no annotations, the description carries the full burden. It discloses the basic operation but does not mention side effects, error behavior, or that it is read-only (though the single operation 'query' implies it). The description lacks transparency about output format and potential limitations.

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

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

The description is short and to the point, using two sentences. A minor typo (double period) prevents a perfect score. Overall, it is efficiently structured.

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

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

Given that there is no output schema, the description could explain what the tool returns (e.g., the query result). It also does not explicitly state that the input must be valid JSON. While parameters are fully covered, this missing context reduces completeness.

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

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

Schema coverage is 100%, so baseline is 3. The description simply paraphrases the schema ('Call with operation plus input and options where relevant') without adding new semantic meaning or usage details beyond the schema.

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

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

The description clearly states the tool's purpose: 'Query a JSON document with a JSONPath expression.' This is a specific verb (query) and resource (JSON document), and it distinguishes itself from sibling tools like 'json' and 'json-diff' by focusing on JSONPath evaluation.

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

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

The description provides no guidance on when to use this tool versus alternatives. It only explains the basic call pattern without any when-to-use or when-not-to-use information.

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

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

No annotations are provided, so the description must carry the full burden. It does not disclose that the tool is read-only, has no side effects, or any rate limits or auth requirements. The description only states the input parameters and operation, leaving behavioral traits unclear.

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

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

The description is two concise sentences. The first sentence states the core purpose, and the second provides operational details. No superfluous words, and it is front-loaded with the key action.

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

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

Given no output schema, the description should explain what the tool returns (e.g., a JSON Schema string or object). It does not. Also, it doesn't clarify error conditions or example usage. For a simple tool with only one operation, this is somewhat lacking but not severely incomplete.

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

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

Schema coverage is 100%, so all parameters are described in the schema. The description adds little beyond that: 'input' is just 'primary input string', 'options' points to another schema. This meets the baseline but doesn't enhance understanding of parameter semantics.

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

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

The description clearly states 'Infer a draft-07 JSON Schema from sample JSON.' This provides a specific verb ('Infer') and resource ('JSON Schema'), making the purpose unmistakable. It also distinguishes the tool from siblings like json-ts (TypeScript interfaces) or json-diff (differences).

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

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

The description mentions the operation 'generate' and what to call, but lacks explicit guidance on when to use this tool versus alternatives or when not to use it. For example, it doesn't say whether it works for any JSON or if there are size limits.

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

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

No annotations are provided, so the description must disclose behavior fully. It states the tool generates TypeScript types from JSON, which is clear, but lacks details on error handling, behavior for invalid inputs, or exact output format. It is adequate but not thorough.

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

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

The description is very concise, using 20 words to convey the core purpose and usage. It front-loads the action 'Generate TypeScript type declarations' and follows with operation specifics. Minor punctuation issues (double dot) do not detract significantly.

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

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

Given the simplicity of the tool and lack of output schema, the description should explicitly mention what the tool returns (e.g., a string with TypeScript declarations). It does not, leaving the agent uncertain about the output format. This is a notable gap.

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

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

Schema description coverage is 100%, so the baseline is 3. The description mentions 'operation', 'input', and 'options' but adds no significant meaning beyond what the schema already provides (e.g., 'input' is described as 'The primary input string' in schema).

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

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

The description clearly states the tool's purpose: 'Generate TypeScript type declarations from a JSON sample.' This is specific and differentiates it from sibling tools like json, json-schema, or json-diff, which address other JSON-related tasks.

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

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

The description provides a basic usage pattern: 'Call with operation plus input (and options where relevant).' However, it does not specify when to use this tool over alternatives (e.g., json-schema for schema generation) or when not to use it, leaving room for confusion.

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

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

No annotations provided, and description only mentions operations and call pattern. Does not disclose error handling, performance characteristics, or whether the tool is read-only/destructive.

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

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

Two sentences, zero wasted words. Front-loaded with purpose and operations.

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

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

Simple tool but lacks description of output format (expected return value). No output schema exists to compensate. Basic completeness for a conversion tool, but leaves ambiguity.

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

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

Schema coverage is 100%. Description adds meaning by clarifying operation enum values (to-xml and to-json) and their inputs. However, 'input' is vague and 'options' defers to external schema.

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

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

Clearly states it converts between JSON and XML, lists two specific operations (to-xml, to-json), and distinguishes from sibling tools like json or xml by specifying conversion.

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

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

Provides basic call pattern (operation plus input, optionally options) but does not explain when to use this tool vs alternatives or any prerequisites/limitations.

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

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

Discloses no signature verification, a key behavioral trait, but does not mention error handling, invalid input behavior, or output format. With no annotations, more detail would be beneficial.

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

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

Concise and front-loaded, but has minor punctuation issues (double periods). Information is efficiently presented.

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

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

Covers basics for a simple decode tool, but missing output format or structure description. Adequate given no output schema, but could be more complete.

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

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

Schema coverage is 100%, baseline 3. Description adds minimal context: explains the operation enum and notes options are optional, but does not significantly enhance parameter understanding beyond schema.

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

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

The description explicitly states the tool decodes JWT header and payload, mentions no signature verification, and specifies the operation 'decode'. It clearly distinguishes itself from the sibling tool jwt-encode.

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

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

Provides basic call pattern (operation + input + options) but lacks explicit when-to-use or when-not-to-use guidance relative to alternatives like jwt-encode or other crypto tools.

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

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

No annotations are provided, so the description carries the full burden. It fails to explain how the HMAC secret is supplied (not in schema as a parameter), what the return value is, or any side effects. The description implies the tool returns a JWT but does not confirm this.

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

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

The description is short but contains redundancy (repeating 'Sign a JSON payload into a JWT using an HMAC secret' in two sentences). It front-loads the main purpose but wastes words. A more concise version would merge the repetitive parts.

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

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

Given no output schema, the description should explain the return value and any prerequisites. It does not explicitly state that the tool returns a JWT string, nor does it cover how the HMAC secret is configured. The description is insufficient for a complete understanding.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by specifying that 'input' should be a JSON payload and that 'options' may be relevant, but it does not elaborate on the options structure or other parameters. The schema already describes the parameters adequately.

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

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

The description clearly states it signs a JSON payload into a JWT using an HMAC secret, which is specific and matches the tool name 'jwt-encode'. It distinguishes from siblings like 'jwt' and 'hmac' by specifying the signing action and algorithm.

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

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

The description provides a basic calling pattern ('Call with operation plus input and options where relevant') but offers no guidance on when to use this tool versus alternatives like 'jwt' or 'hmac'. There is no mention of prerequisites or exclusions.

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

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

No annotations are provided, so the description carries full burden. It states 'Generate placeholder text' and 'Generate lorem ipsum (or themed) placeholder text', which implies a read-like operation (creates new text) but lacks disclosure on side effects, limitations, or rate limits. Minimal transparency beyond basic function.

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

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

The description is concise (two sentences plus a fragment) with no redundant information. It front-loads the primary purpose and then details the operation structure. While brief, it is well-organized and easy to scan.

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

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

Given 3 parameters (one enum, one string, one object) and no output schema, the description is insufficient. It does not explain the return value (likely placeholder text), possible styles/themes, or examples. The input parameter's role is vague, leaving the agent with incomplete understanding of how to use the tool effectively.

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

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

Schema coverage is 100% with basic descriptions for each parameter. The description adds context that operation='generate' produces placeholder text and hints at themed variants via 'input', but does not clarify what the input string represents (e.g., number of words, theme). Options are referenced vaguely. The added value is marginal, meeting the baseline for high schema coverage.

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

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

The description explicitly states it generates placeholder text in several styles, and the name 'lorem' aligns with lorem ipsum generation. It distinguishes from sibling tools that handle other text operations (e.g., ascii, case), but does not elaborate on the 'several styles' mentioned, leaving some ambiguity.

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

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

The description provides basic calling instructions ('Call with operation plus input and options where relevant'), but does not specify when to use this tool versus alternatives (e.g., for placeholder text vs. other text transformations). No explicit guidance on prerequisites or context.

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

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

With no annotations, the description carries full burden. It discloses that 'render' produces sanitized HTML and lists three operations with their effects. However, it does not detail error handling, rate limits, or whether operations are idempotent, leaving some gaps.

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

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

The description is two sentences with clear front-loading of purpose, followed by operation details and usage instruction. Every sentence adds value without redundancy.

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

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

Given no output schema and missing annotations, the description should cover return formats. It does not specify what 'toc' returns (e.g., list of headers) or 'stats' fields (e.g., word count), leaving the agent guessing.

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

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

Schema coverage is 100%, but the description adds value by explaining each operation and the role of 'options' as conditional. The operation parameter benefits from the description's expanded explanations beyond the schema enum.

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

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

The description clearly states it renders Markdown to HTML, builds TOC, and computes statistics, listing three distinct operations. This distinguishes it from sibling tools like 'html' or 'markdown-table', providing a specific verb-resource mapping.

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

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

The description implies usage for Markdown processing but does not explicitly state when to use this tool versus alternatives. It provides clear operation details but lacks exclusions or comparative guidance.

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

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

With no annotations, the description should cover behavioral traits like side effects, permissions, or returns. It only says 'convert' which is trivially inferred. No details on output format, error behavior, or limits.

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

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

The description is short but contains awkward line breaks and periods. It repeats 'operation' unnecessarily. Could be more front-loaded with the core purpose.

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

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

Without an output schema, the description should explain what the tool returns. It does not. The options parameter references an external schema, which is incomplete for an agent. The description is insufficient for confident usage.

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

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

Schema coverage is 100%, so baseline is 3. The description adds that input is 'CSV or TSV rows', which gives context not in the schema. However, the input description in schema is vague, and options reference an external schema, reducing practical value.

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

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

The description clearly states the tool converts CSV or TSV rows into a Markdown table, and mentions the single operation 'generate'. This distinguishes it from sibling tools like 'markdown' and 'json-csv'.

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

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

The description only gives minimal usage instructions ('Call with operation plus input and options where relevant'). It does not specify when to use this tool versus alternatives, nor any prerequisites or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It implies a read-only lookup but does not disclose potential edge cases, error handling, or details about the return format. For a simple lookup, it is minimally adequate.

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

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

The description is concise with only two sentences. It could be improved by removing the double period and fragment, but overall it is efficient and front-loaded.

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

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

Given the tool's simplicity and the absence of an output schema, the description covers the essential usage instructions. It does not explain error behavior or return structure, but for a straightforward lookup, this is acceptable.

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

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

The schema has 100% coverage of parameters. The description reiterates the parameter names and basic usage ('input', 'options') but adds no new 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.

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

The description clearly states the tool's purpose: 'Look up MIME types by file extension or MIME type.' It uses a specific verb ('look up') and resource ('MIME types'), distinguishing it from sibling tools which are unrelated.

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

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

The description provides basic usage guidance: 'Call with "operation" plus "input" (and "options" where relevant).' However, it does not specify when to use this tool versus alternatives or mention any prerequisites or limitations.

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

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only mentions operations and input, omitting details on input validation (e.g., case sensitivity, punctuation handling), error scenarios, or the exact output format. This leaves significant ambiguity for an AI agent.

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

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

The description is relatively concise (about 40 words) but suffers from awkward punctuation and line breaks (e.g., period followed by newline then semicolons). It could be more structured with bullet points for operations, but it is not overly verbose.

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

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

For a simple tool with three parameters and no output schema, the description covers the basic purpose and main parameters. However, it lacks details on return value format, error handling, and edge cases, making it minimally complete. The sibling tools list does not inform completeness directly.

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

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

Schema coverage is 100%, so baseline is 3. The description adds clarity for the operation parameter by defining encode and decode. However, it adds no additional meaning for input or options beyond what the schema already provides. The options parameter remains vague.

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

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

The description clearly states 'Translate text to and from Morse code', which specifies a distinct verb and resource. The two sub-operations (encode/decode) are explicitly listed, and the tool is unambiguously differentiated from sibling tools like base64 or url-encode.

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

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

The description provides basic calling instructions ('Call with operation plus input and options where relevant'), but lacks explicit guidance on when to use this tool versus alternatives or any exclusions. For a niche tool like Morse code, the usage context is fairly clear, but no comparisons are made.

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

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

No annotations are provided, so the description carries the full burden. It states the tool converts numbers between bases but does not clarify how the input base is specified (e.g., does input include the base? Or is the base implied from the input format?). It mentions 'options' but does not explain what they do. The behavior of conversion to 'all supported bases' is vague regarding the output format.

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

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

The description is short (two sentences) and includes a summary of purpose and a usage pattern. It is concise but could be more structured (e.g., splitting into purpose and usage). However, it avoids unnecessary verbosity and front-loads the core verb.

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

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

With no output schema, the description should explain what the conversion result looks like (e.g., a JSON object with keys for each base?). It does not. It also lacks details on how to specify the source base. For a conversion tool with 3 parameters and no outputs documented, the description is incomplete for reliable agent usage.

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

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

Schema coverage is 100%, but the description adds little beyond the schema. It restates the parameter names (operation, input, options) without explaining important aspects like the format of the input string (e.g., prefixes like '0x' for hex) or what options are available. The schema already defines the enum for operation, so the description provides no additional semantic clarity.

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

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

The description explicitly states 'Convert numbers between binary, octal, decimal and hex' with a clear verb (convert) and resource (numbers). It identifies the single operation 'convert' and explains it converts to all supported bases. This distinguishes it from sibling tools that focus on encoding or other transformations.

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

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

The description provides basic usage instructions: 'Call with "operation" plus "input" (and "options" where relevant).' However, it does not specify when to use this tool versus alternatives (e.g., other conversion tools), nor does it mention prerequisites or limitations. The guidance is minimal and lacks explicit when-to-use or when-not-to-use context.

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

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

No annotations provided, but description clarifies it generates cryptographically random passwords and estimates entropy. It adequately discloses behavior for a simple tool, though could mention any limitations.

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

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

Two sentences: first defines overall purpose, second gives usage pattern. Extremely concise with no fluff, every word earns its place.

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

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

For a tool with 3 parameters and no output schema, description covers all necessary information: operations, required inputs, and optional options. No gaps.

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

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

Schema coverage is 100%, so baseline is 3. Description elaborates on operations but mainly restates schema info. Adds operational context (e.g., 'cryptographically random') but doesn't significantly enhance parameter understanding.

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

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

The description explicitly states the tool generates random passwords and estimates strength, listing two distinct operations. This clearly differentiates it from sibling tools like 'password-strength'.

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

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

Provides direct instructions: 'Call with operation plus input (and options where relevant).' It explains the two operations, but doesn't explicitly state when to use alternatives, though context makes it clear.

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

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

No annotations are provided, so the description must carry the full burden. It discloses that the tool estimates entropy, strength, and crack time, which are core behaviors. However, it does not reveal any side effects (e.g., whether the password is stored, logged, or transmitted) or discuss security implications, which is a notable gap for a password analysis tool.

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

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

The description is relatively short but contains redundancy: 'Analyze a password and estimate its entropy, strength and crack time.' is repeated verbatim. The structure is acceptable but could be more efficient. Every sentence has value, but the repetition wastes space.

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

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

There is no output schema, and the description does not explain the return format (e.g., units for entropy, crack time format). For a password strength tool, agents need to know what the output looks like to interpret results. The description lacks completeness in specifying output structure or expected behavior.

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

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

The input schema has 100% coverage with descriptions for all three parameters (input, options, operation). The description adds little value: it merely restates that 'operation' plus 'input' are required and mentions options. It does not explain the meaning of 'options' beyond referencing an external schema, nor does it clarify the nature of 'input' (e.g., what constitutes a valid password). Baseline for 100% coverage is 3, but the description fails to add semantic depth, so the score is 2.

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

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

The description clearly states the tool analyzes passwords to estimate entropy, strength, and crack time. The verb 'analyze' and resource 'password' are specific, and the single operation 'analyze' is well-defined. However, it does not explicitly distinguish from sibling tools like 'password' (which might generate passwords), but the domain is clear enough.

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

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

The description provides minimal usage guidance: 'Call with operation plus input (and options where relevant).' It does not specify when to use this tool versus alternatives (e.g., password generator, other security tools) or mention prerequisites or constraints. No exclusions or when-not-to-use guidance is given.

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

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

The description mentions 'cryptographically secure' as a behavioral trait, but does not disclose other behaviors such as idempotency, side effects, or required permissions. Since no annotations are provided, the description carries the full burden but is somewhat vague on pattern details.

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

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

The description is short (two sentences) and front-loaded with the main purpose. However, there is minor redundancy (double period after 'strings') and the structure could be slightly tighter.

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

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

The tool has three parameters and no output schema. The description covers the operation and basic call pattern but lacks details on return values, error handling, or example usage, which would improve completeness for an AI agent.

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

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

The schema coverage is 100% (baseline 3), and the description adds that 'input' represents a pattern for generation and 'options' are optional. However, it does not elaborate on the pattern syntax or what options are available, so the added value is modest.

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

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

The description clearly states the tool generates cryptographically secure random strings and specifies the 'generate' operation. It distinguishes from sibling tools like password or uuid by emphasizing cryptographic security and pattern-based generation.

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

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

The description tells the user to call with 'operation' plus 'input' and optionally 'options', but does not provide guidance on when to use this tool versus alternatives like password or uuid generation tools.

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

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

No annotations exist; description adds no behavioral traits beyond mentioning operations, failing to disclose side effects, safety, or performance considerations.

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

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

Short and relatively direct, though contains double periods and could be slightly more structured.

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

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

Lacks output schema and does not explain return values or error handling; for a 3-parameter tool with operations, the description is insufficient.

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

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

Schema covers all 3 parameters with descriptions; the tool description reiterates enum meanings and mentions options but adds minimal new semantic value.

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

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

The description clearly states the tool 'test a regex against a string and apply replacements' with specific operations 'test' and 'replace', distinguishing it from siblings.

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

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

Provides basic call pattern ('operation plus input and options') but lacks guidance on when not to use or comparison to alternatives.

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

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

No annotations provided, so description must disclose behavior. It only states basic conversion functionality, omitting details like valid input ranges, error handling, or return format.

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

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

Description is short and to the point, though trailing spaces and semicolons could be cleaned. Sentences are front-loaded with action.

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

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

With no output schema and missing annotations, description provides minimal context. It covers the basic conversion but lacks examples or edge case information.

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

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

Schema covers all parameters with descriptions. Description adds little beyond schema, only clarifying 'input' as primary string and referencing external schema for 'options'. Baseline 3 is appropriate.

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

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

Description clearly states the tool converts between integers and Roman numerals, lists two specific operations, and distinguishes from sibling tools which are unrelated.

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

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

Explains the required parameters (operation, input) and that options are optional, but does not provide guidance on when to use this tool vs alternatives or any exclusions.

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

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

No annotations are provided, so the description must carry the burden. It only describes the core function without disclosing behavioral traits like idempotency, error behaviors, or performance characteristics.

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

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

The description is redundant, repeating 'slugify' multiple times and using awkward punctuation (double periods). It could be more concise and better organized.

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

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

With no output schema, the description does not clarify the return type or structure. It also omits details on the 'options' parameter, which is a nested object.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds minimal information beyond the schema, simply restating the call pattern.

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

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

The description clearly states the tool's purpose: turning arbitrary text into a URL-safe slug. It distinguishes itself from sibling tools in the list, but could be more explicit about not being for general URL encoding or other text transformations.

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

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

The description provides basic call instructions ('Call with operation plus input and options') but offers no guidance on when to use this tool versus alternatives or when not to use it.

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

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

No annotations provided. Description does not disclose behavioral traits such as what 'clean' entails, handling of blank lines, or format of output. Lacks detail beyond basic function.

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

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

Description is concise (two sentences) and front-loaded with operation list. Some redundancy between first and second sentence.

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

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

Tool has 3 parameters and no output schema, but description omits return format, error states, and detailed behavior. Incomplete for an agent to invoke correctly without guessing.

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

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

Schema coverage is 100%, but description adds minimal value: explains operation enum but 'options' is vague with external reference. Input and options lack semantic meaning not already in schema.

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

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

Description states 'Sort, reverse, deduplicate and clean up lines of text' with specific verb+resource. However, schema only includes 'process' as operation, causing slight confusion between listed actions and actual functionality.

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

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

No guidance on when to use this tool over sibling tools like 'case', 'slugify', or other text utilities. No mention of prerequisites or limitations.

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

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

No annotations are provided, so the description carries the full burden. It only outlines the operations and calling convention, without disclosing behavioral traits such as side effects, error handling, or limits. This is minimal for a tool with no annotations.

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

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

The description is concise, with two sentences and a bullet-style list. It front-loads the main purpose (Format and minify SQL) and includes only essential details. Every sentence earns its place without redundancy.

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

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

Given the tool has three parameters (one nested), an enum, and no output schema, the description adequately covers the basic calls but fails to explain return values or how 'options' affect behavior. It is minimally viable but has gaps for a moderate-complexity tool.

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

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

Schema coverage is 100%, providing a baseline of 3. The description adds value by explaining the meaning of the 'operation' enum values (beautify adds newlines; minify condenses to one line). It does not elaborate on 'input' or 'options' beyond the schema, but the added context for operations is meaningful.

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

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

The description clearly states the tool formats and minifies SQL, listing two specific operations (beautify and minify). This verb+resource pairing distinguishes it from sibling tools, which are separate utilities for different data formats.

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

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

The description implies use for SQL formatting but does not explicitly state when to avoid it or compare with alternatives. It offers basic context but no exclusions or guidance on choosing among siblings.

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

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

No annotations provided, so description must carry disclosure burden. It implies non-destructive transformation but does not explicitly state side effects, idempotency, or behavior on invalid input. Adequate but not thorough.

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

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

Two sentences: first states purpose, second gives call signature. Efficient, no fluff, and front-loaded with key information.

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

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

Despite low complexity, the description omits return value (e.g., escaped/unescaped string). With no output schema, this is a notable gap for a transformation tool.

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

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

Schema coverage is 100%, so description adds little beyond schema: 'input' and 'operation' are clear, but 'options' is vaguely described as 'Optional parameters' and redirects to external schema, adding minimal value.

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

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

Clearly states the tool escapes and unescape strings for JSON, JS, HTML, URL, and regex, with explicit operations. Distinguishes itself from sibling tools like url-encode and html-entity by specifying multiple contexts.

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

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

Only provides a generic call signature ('Call with operation plus input'), lacking guidance on when to use this tool versus alternatives like url-encode or json. No exclusion criteria or context hints.

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

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

With no annotations, the description carries full burden. It outlines the two operations' behaviors but fails to disclose edge cases, error handling, or return format. Moderate transparency.

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

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

The description is concise with two sentences and a bullet-like list. Minor redundancy with extra periods, but overall efficient.

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

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

For a simple tool with 3 parameters and no output schema, the description covers operations and calling pattern. It misses return details but is largely complete given the constraints.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the calling convention and operation specifics, though it does not detail input formats or options structure.

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

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

The description clearly states the tool converts and inspects Unix timestamps and dates, listing two distinct operations. This distinguishes it from the diverse sibling tools, which are unrelated.

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

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

The description implies usage via the listed operations but lacks explicit guidance on when to use this tool versus alternatives or when not to use it. No exclusions or context are provided.

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

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

No annotations are provided, so the description must fully disclose behavior. It states the tool generates a TOTP from a base32 secret but omits critical details such as the time step (typically 30s), algorithm (SHA-1), number of digits, and handling of time drift. The options parameter is mentioned but not explained. This leaves significant behavioral gaps.

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

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

The description is concise (2-3 sentences) but contains redundancy: the first two sentences essentially repeat the same information. The instructions are clear but could be streamlined without loss of clarity.

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

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

Given the tool's complexity (TOTP generation with potential options) and the absence of an output schema, the description is incomplete. It does not specify the output format (the generated code), how options affect generation, or any constraints. An agent would lack sufficient context to use the tool correctly, especially for edge cases.

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

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

Schema description coverage is 100%, but parameter descriptions are minimal. The description clarifies that 'input' should be a base32 secret, adding value beyond the schema's 'primary input string.' However, 'options' is poorly described (references an external schema) and 'operation' is only listed as 'generate.' Overall, some added meaning but not fully compensates for the vague options.

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

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

The description clearly states that the tool generates a time-based one-time password from a base32 secret. It uses a specific verb ('generate') and resource ('TOTP'), making the purpose clear. However, it does not explicitly distinguish this tool from sibling tools that might also deal with passwords or encryption, so it falls short of a 5.

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

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

The description provides basic usage instructions ('Call with operation plus input and options where relevant') but does not offer guidance on when to use this tool versus alternatives (e.g., hash, hmac). There is no discussion of prerequisites or when not to use it. This lack of contextual guidance makes it harder for an agent to select the correct tool.

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

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

No annotations are present, so the description must carry the full burden. It only states the output type (ULID) but does not disclose other behavioral traits such as randomness, idempotency, 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.

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

The description is short and front-loaded with purpose, but contains redundancy (e.g., 'Operations: generate — Generate a new ULID' and the next sentence repeating the call pattern).

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

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

Given a simple tool with few parameters but no output schema, the description fails to fully explain the required 'input' parameter and does not provide an example or enough context for correct invocation.

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

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

Although schema description coverage is 100%, the descriptions are generic (e.g., 'The primary input string' for input). The tool description adds little beyond the schema, not explaining the role of 'input' in ULID generation.

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

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

The description clearly states it generates a lexicographically sortable ULID, which is specific and distinguishes it from sibling tools like uuid. However, the mention of 'operations' with only one operation may cause minor confusion.

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

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

The description provides no guidance on when to use this tool versus alternatives, nor does it specify prerequisites or exclude scenarios. It only instructs how to call the tool but not when.

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

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

Describes operations with some behavioral details (e.g., 'drop default ports' for normalize), but lacks information on error handling, side effects, or rate limits. No annotations present to supplement.

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

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

Two succinct sentences with front-loaded purpose and clear list of operations; no unnecessary words.

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

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

No output schema and fails to describe return values or result format, leaving the agent uncertain about what to expect from the tool.

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

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

Adds meaning to the operation enum by explaining each option; schema already covers parameters with 100% coverage.

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

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

The description clearly states the tool's function: parse, validate, and normalize URLs, with specific sub-operations. It distinguishes from sibling tools like url-encode.

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

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

Provides basic usage pattern ('call with operation plus input') but does not explicitly compare with alternatives or specify when not to use.

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

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

With no annotations, the description carries the burden. It mentions two operations and optional options, but does not disclose encoding standard, error handling, or behavior edge cases. Adequate for a simple tool.

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

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

The description is short and gets to the point, though the use of semicolons and quotes adds some clutter. Efficient but could be more streamlined.

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

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

Given no output schema and a simple tool, the description covers the basics. However, it lacks examples, error scenarios, and details on options. Adequate but not rich.

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

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

Schema coverage is 100%, so description need not add much. It mostly paraphrases schema with 'operation' and 'input'. Options are vaguely described as 'Optional parameters' without further detail.

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

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

The description clearly states the tool does percent-encoding and decoding of URL strings, with specific operations ('encode' and 'decode'). This distinguishes it from sibling tools like base64 or html-entity.

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

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

It briefly says to call with operation and input, but lacks guidance on when to use this over alternatives or prerequisites. No explicit when-not or context for choosing this tool.

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

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

No annotations are provided, so the description carries the full burden. It explains the tool parses strings and extracts details, which is transparent for a read-oriented operation. However, it misses details like whether the tool is idempotent, any error handling behavior, or the exact output format (e.g., JSON keys).

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

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

The description is only two sentences but contains repetition ('Parse a User-Agent string into browser, engine, OS and device' appears twice). It could be more compact by stating the purpose once and removing redundant phrasing.

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

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

No output schema exists, and while the description lists what is extracted (browser, engine, OS, device), it does not specify the exact field names or structure of the result. Additionally, it lacks details on how to handle invalid input or errors, which is important for an agent to use the tool effectively.

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

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

Schema coverage is 100% on all three parameters, so the schema itself documents them. The description adds minimal extra value beyond repeating 'operation' and 'input', though it mentions 'options' are optional and referenced elsewhere. Hence, baseline score of 3 is appropriate.

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

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

The description clearly states the tool parses a User-Agent string into browser, engine, OS, and device. The specific verb 'parse' and the resource 'User-Agent string' are well-defined, and the tool is distinct from its siblings, which are other unrelated utilities.

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

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

The description advises calling with 'operation' plus 'input' and optionally 'options'. While it doesn't explicitly state when to use this tool over alternatives, the sibling tools are all different, so confusion is minimal. A slight improvement could be to explicitly state 'Use this when you need to extract components from a user-agent string.'

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

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

Without annotations, the description carries the full burden. It explains each operation's behavior: v4 generates random UUIDs, v3 name-based, parse reports version/variant/timestamp. It mentions 'one or more' for v4, which adds context. However, it does not detail error cases or rate limits.

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

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

The description is relatively compact with two main parts: a summary sentence and a bulleted list of operations. It is front-loaded with the core purpose. Minor formatting issues (double periods, semicolons) slightly reduce clarity but do not obscure meaning.

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

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

For a tool with three parameters and no output schema, the description explains the operations and their inputs but lacks details on return formats for generation (beyond 'one or more UUIDs'), how to specify count, and the exact meaning of 'input' for v3 generation. The 'options' parameter is left undefined, creating gaps.

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

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

Schema coverage is 100% with descriptions for all three parameters. The description reinforces the parameter structure but adds minimal new meaning beyond the schema. For instance, it doesn't explain what the 'input' string represents for each operation or detail the 'options' object.

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

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

The description clearly states the tool generates and inspects UUIDs, listing three distinct operations (v4, v3, parse) with specific actions. This provides a specific verb-resource pair and distinguishes each operation's purpose.

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

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

The description gives basic usage instruction ('Call with operation plus input and options') but does not specify when to use this tool versus alternatives like ulid, nor does it mention when not to use it. No explicit 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.

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

No annotations are provided, so the description must fully cover behavioral traits. It only says it builds the payload string; it does not disclose how input/options are processed, error conditions, output format, or any side effects. This is insufficient for a tool with no annotations.

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

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

The description repeats the phrase 'Build the standard WIFI: payload string' twice, making it slightly redundant. It is not overly verbose but could be more concise. The structure is adequate.

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

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

Given the tool is simple and has no output schema, the description is mostly adequate. However, it lacks examples or constraints that would help an agent select and invoke it correctly, especially since operation is an enum with only one value. The description is complete for basic use but could be improved.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds minimal value beyond 'Call with operation plus input (and options where relevant)'. It does not provide additional semantics like expected formats or examples, so a baseline of 3 is appropriate.

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

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

The description clearly states the tool builds the standard WIFI: payload string for a WiFi QR code. This is a specific verb+resource, and given the sibling tools are other text/encoding utilities, it effectively distinguishes itself.

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

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

The description specifies to call with 'operation' plus 'input' (and 'options' where relevant), but does not explicitly state when not to use this tool or mention alternatives. However, the context of siblings and the tool's specialized nature makes usage relatively clear.

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

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

No annotations are provided, so the description must carry the full behavioral burden. It describes operations but lacks details on output format, error handling, performance, or side effects. For a simple computational tool, this is adequate but not comprehensive.

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

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

The description is two sentences plus a bulleted list of operations, with no redundant or superfluous text. It is front-loaded with the main purpose and efficiently communicates necessary details.

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

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

The tool has 3 parameters, no output schema, and moderate complexity. The description sufficiently explains operations but does not describe the return values or the format of results, leaving the agent to guess what statistics are returned. Some gaps remain.

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

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

Schema coverage is 100%, so each parameter is already described in the input schema. The description adds value by explaining the operations and how they relate to parameters, but does not provide additional meaning beyond the schema for most parameters.

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

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

The description clearly states the tool counts words/characters and computes readability statistics, listing three specific operations. It distinguishes from sibling tools which are all unrelated (encoders, formatters, etc.), making its purpose unique and unambiguous.

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

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

The description explicitly instructs to call with 'operation' and 'input', and explains each operation's purpose. While it doesn't provide when-not-to-use or alternatives, the sibling tools are entirely different, so no conflict exists.

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

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

Without annotations, the description carries full burden, but it only notes 'server-safe string transform' for both operations. It does not disclose side effects, error handling, output format, or any required permissions.

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

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

The description is moderately concise but contains awkward punctuation (double periods, semicolons) and repetitive phrasing ('server-safe string transform' twice). It could be streamlined.

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

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

Given 100% schema coverage and no output schema, the description adequately covers the two main operations. However, it omits details about return values, error states, and what 'highlight' refers to.

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

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

The input schema covers all parameters with descriptions, but the description adds value by explaining each operation's effect (e.g., 'Pretty-print XML with the chosen indent'). The 'options' parameter remains vague.

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

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

The description clearly states the tool's purpose: to pretty-print or minify already-serialized XML. It explicitly lists two operations ('format' and 'minify'), distinguishing it from sibling tools like json-xml which convert XML to JSON.

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

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

The description provides basic usage instructions ('Call with operation plus input') but does not specify when to use this tool versus alternatives, nor does it mention any prerequisites or constraints.

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

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

With no annotations, the description fully bears the burden. It states the core behavior (conversion) but omits details like output format, error handling, or whether it validates input. However, for a simple conversion tool, this is minimally adequate.

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

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

The description is two sentences and efficiently conveys the essential information. Minor punctuation issues but overall well-structured and front-loaded.

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

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

For a tool with no output schema and no annotations, the description should cover what the tool returns (e.g., converted string) and potential failure modes. It does not, leaving the agent with incomplete context.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no new semantic information beyond confirming the usage pattern, which is the expected baseline.

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

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

The description clearly states it converts between YAML and JSON, listing the two specific operations ('yaml-to-json' and 'json-to-yaml'), which precisely defines the tool's purpose and distinguishes it from sibling tools like json, json-csv, etc.

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

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

The description provides basic usage ('Call with operation plus input') but lacks guidance on when to use this tool versus alternatives (e.g., the json tool) and does not specify prerequisites or exclusions.

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