@revxl/devtools

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.2
Disambiguation5/5
Each tool targets a distinct developer utility—regex, cron, JSON diffing/querying/formatting, encoding, hashing, JWT, etc.—with no meaningful overlap. Even the JSON tools are clearly separated by operation: diff, query, format.
Naming Consistency4/5
Most composite names use lowercase snake_case (json_diff, sql_format, url_encode) while well-known single-purpose tools use lowercase single words (regex, cron, chmod, jwt). This is largely consistent and readable, with minor deviation between single-word and underscored multi-word styles.
Tool Count4/5
At 17 tools, the set is slightly above the typical 3-15 sweet spot, but the broad 'devtools' scope justifies each tool. There are no redundant utilities, and the count feels comprehensive without being overwhelming.
Completeness4/5
The tools cover a wide range of everyday developer tasks including JSON manipulation, encoding, hashing, timestamp conversion, SQL formatting, config conversion, regex, cron, secrets scanning, and JWT handling. Minor gaps exist (e.g., HTML escaping, string case conversion), but the core utility surface is largely complete for a general-purpose devtools server.
Average 3.7/5 across 17 of 17 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It communicates the expression syntax and a commercial note ('3 free trials'), but does not state whether it is read-only, what it returns for matches versus no match, how wildcard results are shaped, or how invalid JSON is handled.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core function is stated in one front-loaded sentence with no filler. The trailing '[PRO - 3 free trials]' is promotional noise rather than useful operational detail, which keeps it from a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema fully documents the two required parameters, and the description covers the query syntax, making basic invocation possible. Missing context includes return format, behavior on nil/empty results, and error handling, which an agent may need for reliable use — especially because no output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds only minimal meaning beyond the schema: the schema already documents dot-path syntax, wildcards, and array indices. The description's value is mostly restating what an agent can read in the query parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Query') and resource ('JSON data'), and clarifies the mechanism (dot-path expressions with nested keys, array indices, and wildcard expansion). This distinguishes it from nearby siblings like json_format and json_diff, though it doesn't explicitly name those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for extracting or projecting values from JSON, but provides no explicit when-to-use or when-not-to-use guidance. It doesn't mention alternatives such as json_format, json_diff, or yaml_convert, leaving the agent to infer selection from the name and syntax alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must carry the full burden of behavioral disclosure. It says it converts between formats but does not explain what the output looks like, whether a target format can be selected, or how ambiguous inputs are resolved. This leaves the core conversion behavior underspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the action and resource, followed by a compact list of supported formats. There is no redundancy or wasted wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description must specify what the tool returns, but 'convert between' leaves it open whether the output is a single converted value, an object with all formats, or something else. This ambiguity is essential for correctly invoking and interpreting the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents the single parameter with 100% coverage, listing 'now', epoch seconds, epoch milliseconds, and ISO 8601 strings. The description adds 'human-readable' as an additional category but otherwise largely overlaps with the schema, so the added semantic value is modest.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Convert') on a specific resource ('timestamp') and names the supported format families. Among siblings like regex, cron, json_diff, and base64, timestamp conversion is clearly delimited, so an agent can identify when this tool is relevant.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no preconditions, and no exclusions. It essentially restates the function, leaving the agent to infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the core action but does not explain output format, whether results include matched secret types, any limitations, or the significance of 'PRO - 3 free trials.' The billing note hints at usage restrictions but does not clarify behavior, leaving important operational details undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately front-loads the action ('Scan text') and the object (leaked secrets). It catalogs relevant secret types efficiently. The '[PRO - 3 free trials]' suffix is a minor aside about plan limitations but does not detract from readability or function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description is adequate for basic invocation but leaves out return-value expectations and behavioral constraints such as trial limits or result structure. The simplicity of the tool lowers the burden, but the absence of any output/usage notes means an agent cannot fully anticipate the response or potential plan restrictions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input parameter is already well documented in the schema. The description adds context about what kinds of secrets are detected, which enriches the parameter's meaning slightly. However, it does not provide additional format, length, or encoding details beyond what the schema already states. Baseline 3 applies because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Scan' with a clear resource: text, for leaked secrets including API keys, tokens, passwords, and connection strings. This distinguishes it clearly from all sibling tools like regex, cron, or base64, which serve different purposes. The action is unambiguous and immediately tells an agent what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: scan text to detect secrets. It does not explicitly state when to use this tool versus alternatives, but the narrow purpose strongly signals its intended scenario. There is no mention of exclusions, prerequisites, or alternative tools, so guidance is minimal but reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the burden. It discloses the core transformation behavior but does not mention return format or behavior on invalid Base64 input during decode, which is a notable gap for a tool without an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One short front-loaded sentence with zero filler. Every word earns its place, and it is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema fully documents parameters and the purpose is clear, but with no output schema the description does not explicitly state the return value or failure behavior. This is adequate but leaves an agent to infer the output format and error handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already explains both text and action. The description adds no parameter-specific meaning beyond what the schema provides, so the baseline applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Encode or decode Base64 strings.' The algorithm is explicit and immediately distinguishes it from siblings like url_encode and hash_text, so an agent can select it without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use or when-not-to-use guidance is given. With several encoding siblings (url_encode, hash_text, uuid_generate), an agent is not told when Base64 is the right choice or what input constraints apply.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It accurately states that the tool can encode or decode URL strings, but does not detail character-set handling, return format, or errors. This is adequate for a simple pure function but leaves edge cases unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler. It front-loads the verb and resource and is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter utility with full schema coverage, the description is minimally adequate. It explains the operation but omits return-value details, encoding rules, and error behavior. Given no annotations or output schema, additional context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema documents both parameters (text, action) with clear descriptions, giving 100% schema coverage. The description adds no parameter-level detail beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb-resource pair: 'URL encode or decode strings'. This clearly distinguishes it from sibling encoding tools like base64 by specifying the URL encoding scheme, leaving no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to choose this tool over alternatives such as base64 or hash_text. The description merely states the operation without addressing selection criteria, so an agent must infer usage from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool converts between formats and provides an explanation, and hints at a PRO trial limit, but it does not describe the output structure, error handling, or how the trial limit works. This is adequate for a pure conversion utility but lacks deeper behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single, front-loaded sentence that clearly states the action and scope. The promotional suffix '[PRO - 3 free trials]' is minor noise, but the overall structure is compact and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, has one required parameter, and the schema is complete. There is no output schema, and the description does not specify the exact return format or behavior for invalid input, though these can be reasonably inferred for a conversion tool. It is sufficient but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the description mirrors the schema's examples ('755' and 'rwxr-xr-x') without adding extra constraints. It adds chmod context but no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description has a specific verb ('Convert'), a clear resource ('chmod permissions'), and a precise scope ('numeric (755) and symbolic (rwxr-xr-x)'). It clearly distinguishes this utility from the sibling tools, none of which relate to chmod permission conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The use case is implied by the verb 'Convert' and the chmod context, but the description does not explicitly state when to use this tool versus alternatives or mention any exclusions. It provides a clear function but no direct routing or decision guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose that responses include code snippets and that there is a 'PRO - 3 free trials' monetization/limit aspect, which is useful. However, it does not describe output format, error behavior, authentication needs, or what happens after trial limits are reached.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, reasonably compact sentence that front-loads the three action types and appends the pricing note. It earns its place, though the phrase 'with code snippets' is slightly ambiguous as to which action it modifies.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three modes with different expected outputs, and there is no output schema. The description names the outputs (plain English, cron, next run times) but does not clarify output structure, error cases, or the practical implications of the 'PRO - 3 free trials' notice, so an agent has only partial guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents each parameter, including action options and example expressions. The description adds context about the overall purpose but no significant parameter-level meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly enumerates three specific, distinct operations: explain, generate, and next_runs. It names the resource (cron expressions) with specific verbs, making it easy to distinguish from unrelated sibling utilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool by listing its three modes, but it does not explicitly state when to prefer this over alternatives or provide exclusions. The action enum and parameter descriptions carry most of the routing responsibility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must bear the full burden of behavioral disclosure. It states the core operation (hash with selected algorithm) but omits the output format (e.g., hex digest, return key), how empty or non-string inputs are handled, and that hashing is one-way. These are non-obvious details an agent may need when invoking the tool correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single eight-word sentence that places the action 'hash' up front. It is free of filler and every word contributes to conveying the tool's purpose and supported algorithms.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter utility with no annotations, the description plus schema covers parameters and available algorithms, but the absence of any mention of the return value is a notable gap. An agent cannot tell from the description or schema what shape the result will take, such as the field name for the digest.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters completely (text and algorithm with enum values), so the baseline is 3. The description lists the same algorithms already present in the schema's enum and adds no new information about parameter constraints, encoding, or defaults beyond what the schema states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with the verb 'hash' and the object 'text', naming the resource and operation. It further specifies three algorithms (MD5, SHA-256, SHA-512), which clearly distinguishes it from sibling utilities like base64, url_encode, and jwt, which perform encoding or signing rather than hashing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool is for computing a hash of arbitrary text, but it gives no explicit when-to-use or when-not-to-use guidance. It does not mention that base64 or url_encode are for reversible encoding or that hashing is irreversible, so an agent must infer the appropriate choice from the tool's name and purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the responsibility for behavioral disclosure. It does state that decoding inspects header/payload/expiry and creation is HMAC-signed, and the '[PRO - 3 free trials]' note hints at entitlement behavior, but it does not explain signature verification behavior, error handling, side effects, or any access restrictions beyond the PRO hint. For a read/decode plus token-generation tool, that is modest but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence that front-loads the core actions and resource. It conveys both operations, key inspected elements, and a monetization constraint without redundant wording. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With six parameters, one nested object, two enums, no output schema, and no annotations, the description covers the top-level duality of the tool well but leaves some context implicit, such as what exactly is returned after creation or decode, whether the signature is verified on decode, and how expiration is handled. The schema handles parameter structure competely, but the absence of an output schema and annotations means the description could have provided a little more usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema's own descriptions already explain each parameter, including action-specific prefixes like '(decode)' and '(create)'. The tool description adds little beyond the schema: it mentions decoding header/payload/expiry and HMAC signing, but it does not provide additional meaning for token, secret, payload, algorithm, or expires_in beyond what the schema already gives. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Decode' and 'create' with a clear resource, JWT, and clarifies the two distinct actions: inspecting a token or generating one. It also names the inspected components (header, payload, expiry) and the signing method (HMAC), making the tool's purpose unambiguous and differentiating it from the unrelated sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool — when a JWT needs to be decoded or created — but it does not provide explicit when-to-use guidance, exclusions, or alternatives. The action enum in the schema provides useful internal routing, but there is no explicit statement of when this tool should be preferred over others, though the siblings are largely unrelated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It clearly identifies a formatting operation and mentions the PRO/free-trial constraint, but it does not describe the return value, behavior on invalid SQL, or handling of unsupported dialects. Core behavior is clear, but operational details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose and adds a concise trial constraint. Every part is relevant, and there is no redundant restatement of schema fields or annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity formatter with two documented parameters, the description is mostly adequate. However, there is no output schema, and the description does not explicitly state that the tool returns the formatted SQL string or how errors are surfaced. These are moderate gaps given the lack of structured output information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides full documentation for both parameters, including the dialect enum and the default note. The description adds no parameter-specific meaning beyond what the schema already states, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Format and prettify SQL queries'. The additional detail about 'proper indentation and clause separation' makes the tool's function concrete and clearly distinguishes it from unrelated siblings like json_format or regex.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the description, but there is no explicit when-to-use or when-not-to-use guidance. Since none of the sibling tools offer SQL formatting, the description is not actively misleading, yet it leaves routing decisions entirely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It indicates a read-only lookup and the kind of result returned, but it does not describe how invalid codes are handled, what the return shape looks like, or how categories are conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence with no filler and the key action is front-loaded. Every word contributes to understanding what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup utility, the description combined with the schema sufficiently covers input and overall output. It would be slightly stronger if it enumerated common categories or return formats, but nothing critical is missing for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: the code parameter is already described with an example (404). The tool description adds no additional semantic detail about valid ranges, formats, or constraints, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('look up') with a clear resource ('HTTP status code') and result ('name and category'). It is unambiguous and distinct from the utility siblings such as regex, base64, and json_query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: whenever HTTP status code metadata is needed. It does not provide explicit when-not-to-use guidance, but there are no closely related sibling tools that create confusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses the 500-item limit and the free-tool restriction, but it is silent on important batch behavior such as partial failures, error aggregation, execution order, and whether the PRO trial note affects invocation or cost.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded with the core purpose. Every sentence earns its place, and the limit plus eligibility constraint are stated efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The core invocation requirements are present, but with no output schema and no annotations, the description leaves batch failure/response behavior and the ambiguous "[PRO - 3 free trials]" note under-explained. An agent might invoke it correctly, but not fully understand what to expect from the result or cost model.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both `tool` and `items`. The description adds little parameter-specific meaning beyond restating the item limit and the free-tool requirement, which the schema already contains.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is specific and verb-first: "Run any free tool across multiple inputs in one call." It clearly identifies the tool as a batching wrapper, which naturally distinguishes it from the sibling utility tools that operate on single inputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when you have multiple inputs for a free tool and want to run them in one call. It also states the key exclusion: only free tools are supported. It does not explicitly name alternatives, but the usage context is strong enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It goes beyond the schema by disclosing that comparison is deep, reports added/removed/changed values, and includes paths. It does not cover edge cases like invalid JSON or array ordering, but the core behavioral contract is clearly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The main content is one efficient, front-loaded sentence that states the operation and output value. The trailing '[PRO - 3 free trials]' is promotional noise rather than functional guidance, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description sufficiently explains what the agent will receive: differences categorized as added, removed, and changed with paths. It could be more complete by addressing input validity or output formatting, but for a straightforward two-string comparison tool it is largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters documented as 'First JSON string' and 'Second JSON string'. The description adds no additional parameter-level detail beyond saying these are JSON objects, so the baseline of 3 is appropriate since the schema already covers meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Deep-compare' with resource 'two JSON objects' and specifies exactly what is produced: added, removed, and changed values with paths. This clearly differentiates it from siblings like json_query and json_format, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied: use this when you need to compare two JSON values and see their differences. However, it does not explicitly state when to prefer this over json_query or provide any exclusions or alternative routing, so the usage guidance is not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It lists the three actions but does not disclose what happens on invalid JSON, whether validation returns a simple boolean or detailed errors, or how output is delivered. The core behavior is clear but edge-case behavior is undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero filler. It efficiently conveys the full purpose without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with a fully documented schema, the description is mostly complete. However, there is no output schema and validate's return format is ambiguously implied, which leaves a meaningful gap for an agent deciding how to handle results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters. The description adds no additional semantic detail beyond the action list, which fits the baseline expectation for high-coverage schemas.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource (JSON strings) and three precise operations (format, minify, validate), which immediately distinguishes it from siblings like json_diff and json_query. It communicates exactly what the tool can do.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states the tool's core use cases, making it easy to infer when to select it over json_diff or json_query. It does not explicitly mention alternatives, but the scope is so precise that the intended usage is unmistakable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It correctly conveys that the tool generates v4 UUIDs and supports multiple results, but it does not explicitly state that the UUIDs are random, non-deterministic, side-effect-free, or how the output is shaped (string vs array).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to the tool's purpose and basic capacity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter utility with full schema coverage, the description is nearly adequate. However, with no output schema and no annotation, it leaves the return format ambiguous: whether a single UUID is returned as a string and multiple as an array, or whether the result is always an array. This is a meaningful gap for an agent deciding how to consume the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'count' parameter, including default and max. The description's phrase 'one or more' lightly reinforces the parameter but adds no meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate') and a precise resource ('v4 UUIDs'), and indicates the tool supports multiple outputs via 'one or more'. It clearly distinguishes this tool from the unrelated sibling utilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose is so self-evident that usage context is implied clearly: call this whenever a v4 UUID is needed, with an optional count. No exclusions or alternatives are necessary given the sibling list contains no similar UUID-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose a usage limitation ('PRO - 3 free trials'), but it does not describe the output shape, error behavior, or how conversion handles formatting details. This is partial disclosure with room for improvement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler. It states the action and target formats efficiently, and the trial limitation is appended without obscuring the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple converter with a fully described schema, the description is mostly adequate. However, there is no output schema, and the description does not explicitly state what the tool returns, leaving some ambiguity about the response format. The trial note is useful but also vague about what counts as a trial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and all three parameters (text, from, to) are already described in the schema. The description adds no additional parameter-level meaning beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Convert'), the exact resource domain (YAML, JSON, TOML), and clearly differentiates the tool from the formatting/query siblings like json_format and json_query. An agent can understand what this tool does immediately.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: whenever conversion among YAML, JSON, or TOML is needed. It does not name alternatives or exclusions, but there are no close sibling conversion tools, so the usage 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It reveals useful behavioral details beyond the name: it returns match details/groups/indices, can generate code across languages, and flags a 'PRO - 3 free trials' limitation. This gives the agent important expectations about output richness and potential access restrictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core action, then adds output details, the code-generation capability, and the trial limitation. Every clause earns its place and there is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description, combined with a fully self-documenting input schema, is complete enough for an agent to select and invoke the tool correctly. It clarifies expected outputs (match details, groups, indices) and highlights a hard constraint ('3 free trials'). A dedicated output schema or explicit return-shape details would raise this further, but nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all five parameters and their meanings. The description adds little parameter-level detail beyond pointing to code-generation languages, which mirrors the existing 'languages' parameter. Baseline 3 is appropriate because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Test a regex pattern against a string' and also covers code generation. This clearly distinguishes it from the unrelated sibling dev-utility tools. The mention of match details, groups, and indices makes the tool's purpose concrete and recognizable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a clear usage context: use this tool when you need to validate or test a regex against a string, inspect match groups/indices, or generate regex code across multiple languages. It does not explicitly name alternatives or exclusions, but no sibling tool offers a comparable regex-testing function, so the guidance is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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