GoldenFlow
Server Details
Standardize, reshape, and normalize messy data — CSV, Excel, Parquet, S3, databases.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- benzsevern/goldenflow
- GitHub Stars
- 1
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Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.4/5 across 10 of 10 tools scored. Lowest: 2.6/5.
Each tool has a clearly distinct purpose with no ambiguity: diff compares files, explain_transform describes transforms, learn generates configs, list_domains lists domains, list_transforms lists transforms, map auto-maps schemas, profile profiles data, select_from_findings maps findings to transforms, transform applies transforms, and validate dry-runs transforms. The descriptions clearly differentiate their functions, making misselection unlikely.
The naming is mostly consistent with a verb_noun or verb pattern (e.g., diff, explain_transform, learn, list_domains, list_transforms, map, profile, select_from_findings, transform, validate), all using snake_case. However, 'map' and 'profile' are single verbs without nouns, which slightly deviates from the more descriptive multi-word names, but the pattern is still readable and coherent.
With 10 tools, the count is well-scoped for a data transformation and analysis server. Each tool earns its place by covering distinct aspects like comparison, description, learning, listing, mapping, profiling, selection, transformation, and validation, providing a comprehensive toolkit without being overwhelming.
The tool set offers complete coverage for data transformation workflows: it supports discovery (list_domains, list_transforms), analysis (diff, profile, validate), configuration (learn, explain_transform), mapping (map, select_from_findings), and execution (transform). There are no obvious gaps, enabling agents to handle end-to-end tasks without dead ends.
Available Tools
10 toolsdiffAInspect
Compare two data files and show what changed (added, removed, modified rows).
| Name | Required | Description | Default |
|---|---|---|---|
| path_after | Yes | Path to transformed file | |
| path_before | Yes | Path to original file |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full disclosure burden. It successfully reveals the output categorization (added/removed/modified rows), but fails to state whether the tool is read-only, handles large files efficiently, or supports specific file formats. Safety profile and performance characteristics are absent.
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?
Single sentence of 11 words with zero redundancy. The information is front-loaded with the action verb 'Compare' and immediately specifies the scope (data files) and output granularity (row-level changes). Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple 2-parameter schema with no nesting, the description is nearly sufficient. It compensates for the missing output schema by describing the return categories (added/removed/modified rows). However, it could improve by specifying the output format (e.g., JSON structure, text diff) since no output_schema exists.
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 clear parameter descriptions ('Path to original file', 'Path to transformed file'), establishing a baseline of 3. The description references 'two data files' which aligns with the parameters, but adds no additional semantic detail about path formats, relative vs absolute paths, or file accessibility requirements 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 compares data files and identifies specific change types (added, removed, modified rows). It effectively distinguishes from siblings like 'transform' (which creates changes) and 'validate' (which checks correctness), though it doesn't explicitly contrast with 'explain_transform' which could conceptually overlap.
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 context (when you need to compare file versions), but provides no explicit guidance on when to prefer this over 'explain_transform' or whether it should be used before/after 'transform'. No prerequisites or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
explain_transformAInspect
Describe what a specific transform does, its mode, and input types.
| Name | Required | Description | Default |
|---|---|---|---|
| transform_name | Yes | Name of the transform |
Tool Definition Quality
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 what information the tool returns (functionality description, mode, and input types), but fails to mention safety characteristics (read-only vs. side effects), error behaviors (e.g., invalid transform names), or response 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 a single, efficient sentence that front-loads the action verb ('Describe') and immediately specifies the scope and output content. There is no redundant or wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter introspection tool without output schema or annotations, the description adequately covers the tool's purpose and return content (mode, input types). However, it lacks completeness regarding error handling and safety guarantees that annotations would typically provide.
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% description coverage for its single parameter ('Name of the transform'). The description references 'a specific transform,' which aligns with the schema but does not add semantic nuance beyond the parameter's existing documentation, warranting the baseline score of 3.
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 'Describe[s] what a specific transform does, its mode, and input types,' providing a specific verb and resource. It implicitly distinguishes from siblings like 'transform' (execution) and 'list_transforms' (enumeration) by focusing on explanation of a specific item, though it does not explicitly contrast with these alternatives.
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 context (use when you need to understand a transform's functionality), but lacks explicit guidance on when to use this versus 'list_transforms' (to discover available transforms first) or prerequisites like needing to know the transform name beforehand.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
learnCInspect
Generate a YAML config from data patterns.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to data file |
Tool Definition Quality
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. While it implies the output is YAML, it fails to state whether the config is returned in the response, written to disk, or if the operation is read-only versus 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?
The description is a single, front-loaded sentence with no redundant words. However, given the tool has nine siblings suggesting a complex domain, it may be overly terse rather than appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of nine sibling tools suggesting a data transformation domain, the description lacks critical context about what the generated YAML config contains (e.g., transformation rules, schemas) and how it integrates with other tools like 'transform' or 'validate'.
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% description coverage for its single 'path' parameter. The description adds no additional context about the parameter, but since the schema is fully self-documenting, it meets the baseline requirement.
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 the tool generates a YAML config, providing a clear verb and output format. However, 'from data patterns' is vague and does not distinguish this tool from siblings like 'profile' or 'explain_transform' in what appears to be a data processing suite.
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 like 'profile' or 'transform', nor does it mention prerequisites such as the format of the input data file.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_domainsBInspect
List available domain packs (e.g., people_hr, ecommerce, finance).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
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. While 'List' implies a read-only operation, the description does not confirm safety, side effects, rate limits, or return format. The examples add some context about return values but insufficient behavioral transparency for a tool with zero annotation coverage.
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 consists of a single efficient sentence that immediately states the purpose and provides helpful parenthetical examples. There is no wasted text or unnecessary elaboration.
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, the description should ideally explain what gets returned. The examples partially compensate by showing sample return values, but the description lacks explicit return type documentation. For a simple zero-parameter listing tool, the description is minimally adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema contains zero parameters. According to scoring guidelines, this establishes a baseline score of 4. The description appropriately does not fabricate parameter details.
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 'List[s] available domain packs' and provides concrete examples (people_hr, ecommerce, finance) that clarify what domain packs look like. However, it does not explicitly differentiate from the sibling tool 'list_transforms', leaving potential ambiguity about when to use each listing tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites (if any), or when not to use it. While the examples hint at the tool's utility, there is no explicit 'when-to-use' context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_transformsAInspect
List all registered transforms with their modes, input types, and auto-apply status.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It compensates well by disclosing what the operation returns (modes, input types, auto-apply status), which is critical given the lack of output schema. However, it omits safety/permission details that would normally be covered by annotations (though 'List' implies read-only).
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?
Single sentence with zero waste. Front-loaded with the action verb. Every clause earns its place: 'registered' defines scope, and the three attributes define the return payload structure without verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description adequately covers the return values by listing the specific fields returned. It could be improved by mentioning if the results are cached or if the operation is expensive, but it covers the essential contract.
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 tool has zero parameters, which establishes a baseline of 4 per the scoring rules. No parameter description is needed or expected.
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 uses specific verb 'List' with clear resource 'registered transforms' and enumerates exactly what data is returned (modes, input types, auto-apply status). It effectively distinguishes from sibling 'transform' (execution vs. discovery) and 'explain_transform' (list all vs. explain specific).
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?
Usage is implied by the name and description (discovery tool), but there is no explicit guidance on when to use this versus 'transform' directly, or whether to use this before calling 'explain_transform'. No 'when-not-to' or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mapCInspect
Auto-map schemas between source and target files.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | Source file path | |
| target | Yes | Target file path |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but fails to indicate whether this tool modifies files, returns a mapping object, requires specific permissions, or handles conflicts. The term 'auto-map' implies automation but does not disclose algorithm limitations or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at six words, with no redundant or filler content. However, given the absence of annotations and output schema, this brevity leaves critical gaps in agent understanding; one additional sentence describing the return value or side effects would significantly improve utility without sacrificing 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 lack of annotations and output schema, the description inadequately prepares an agent for invocation. It omits crucial context such as the output format (likely a schema mapping structure), whether the operation is read-only or destructive, and how it relates to the broader transformation workflow implied by sibling tools like 'transform' and 'validate'.
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?
Since the input schema has 100% description coverage for both parameters ('Source file path' and 'Target file path'), the baseline score applies. The description mentions 'source and target files' but adds no semantic depth regarding acceptable file formats, path conventions, or whether these refer to physical files versus 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 core action (auto-map schemas) and the operands (source and target files), providing specific verb and resource identification. However, it does not explicitly differentiate from the sibling 'transform' tool, which could confuse agents about whether this tool performs the actual data conversion or just establishes field correspondences.
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 like 'transform', 'diff', or 'validate'. It does not indicate prerequisites (e.g., whether files must be profiled first) or when mapping might fail, leaving agents without selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
profileBInspect
Profile a data file showing column types, nulls, and patterns.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to data file |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full disclosure burden. While it states what is analyzed, it omits critical behavioral details: whether the operation is read-only, performance characteristics for large files, the output format/structure, and error handling 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 a single, efficient sentence of nine words. It is front-loaded with the action and target, with zero redundancy or filler 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 simple single-parameter input and lack of output schema, the description partially compensates by listing what the profile contains (column types, nulls, patterns). However, it fails to specify the return format or structure, leaving agents uncertain about how to parse results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage for the single 'path' parameter, the schema already fully documents the input. The description mentions 'data file' which aligns with the path parameter but adds no additional semantic information (e.g., supported file formats, path resolution rules) 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 uses a specific verb ('Profile') with clear resource ('data file') and enumerates exact outputs ('column types, nulls, and patterns'). This clearly distinguishes it from siblings like 'transform' (modification), 'validate' (quality checking), and 'learn' (pattern inference).
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 like 'validate' or 'learn', nor does it mention prerequisites (e.g., file accessibility) or post-processing steps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
select_from_findingsAInspect
Map GoldenCheck findings to recommended GoldenFlow transforms. Bridge tool for Check-to-Flow handoff.
| Name | Required | Description | Default |
|---|---|---|---|
| findings | Yes | List of GoldenCheck findings (each with 'check' and 'column' fields) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It explains the mapping logic but omits critical behavioral traits: it does not clarify if this is a read-only operation (likely) or if it modifies state, nor does it describe error handling when findings have no matching transforms.
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 with zero waste. The first sentence states the core function; the second provides workflow context. Every word earns its place with no redundant or filler 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 single parameter and simple schema, the description adequately covers the input side. However, with no output schema provided, the description should ideally characterize the return value (e.g., what the 'recommended transforms' look like) to be 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%, establishing a baseline of 3. The description mentions 'findings' but does not add semantic value beyond the schema's explanation that findings are objects with 'check' and 'column' fields. No additional context on valid values or format constraints is 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 maps GoldenCheck findings to GoldenFlow transforms using specific domain terminology. While it effectively identifies the specific resources involved (findings → transforms), it does not explicitly contrast with the generic 'map' sibling tool to guide selection.
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 phrase 'Bridge tool for Check-to-Flow handoff' provides implied workflow context, suggesting when to use it in a pipeline. However, it lacks explicit prerequisites (e.g., 'run after GoldenCheck') or exclusion criteria contrasting it with the 'map' or 'transform' siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
transformBInspect
Transform a data file using GoldenFlow. Zero-config or config-driven.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to data file | |
| config | No | Optional YAML config path |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Mentions GoldenFlow engine and config-driven behavior, but fails to disclose critical mutation details: whether the file is overwritten, output location/return value, reversibility, or side effects. 'Transform' implies mutation but safety profile is undefined.
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 waste. First sentence establishes core function; second clarifies configuration modes. Perfectly front-loaded with no redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with simple flat schema and no output schema, description covers the essential invocation pattern. However, given zero annotations and the likely destructive nature of file transformation, gaps remain regarding output handling and execution safety that should be addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, establishing baseline 3. Description adds 'Zero-config or config-driven' which reinforces the optional nature of config and its driving role, but doesn't add syntax details, examples, or constraints 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?
States specific action (Transform), resource (data file), and technology (GoldenFlow). Distinguishes from siblings like explain_transform and list_transforms by implying execution rather than explanation or listing. However, doesn't clarify difference from sibling 'map' or 'validate' operations.
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 implied usage guidance through 'Zero-config or config-driven,' indicating the config parameter is optional but recommended for advanced use. However, lacks explicit when-to-use guidance, prerequisites, or alternatives compared to siblings like explain_transform or validate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validateAInspect
Dry-run transform on a file. Shows what would change without writing output.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to data file | |
| config | No | Optional YAML config path |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It successfully communicates the non-destructive nature ('dry-run', 'without writing output'), but fails to describe the return format or structure of what 'shows what would change' looks like, leaving a gap given the lack of 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero waste. The first sentence front-loads the core operation ('Dry-run transform'), while the second clarifies the behavioral guarantee ('without writing output'). 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 2-parameter tool, the description adequately covers the operation and safety profile. However, given the absence of both annotations and output schema, the description should specify the return format (e.g., diff, report, validation errors) to be complete. As written, the agent knows what it doesn't do (write output) but not exactly what it returns.
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%, establishing a baseline of 3. The description adds minimal semantic context beyond the schema, though 'transform on a file' implicitly contextualizes the path parameter as the input data target. No additional parameter constraints, formats, or examples 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 uses specific verbs ('Dry-run transform') and identifies the resource ('file'). It clearly distinguishes from the sibling 'transform' tool by emphasizing 'without writing output', establishing this as a safe preview operation.
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 phrases 'Dry-run' and 'without writing output' implicitly signal when to use this tool (for previewing changes) versus the sibling 'transform' tool (for actual execution). However, it stops short of explicitly naming the alternative tool or stating explicit when-not-to-use conditions.
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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{
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"maintainers": [{ "email": "your-email@example.com" }]
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