studio
Server Details
Turn analyzed data into a real Excel-like spreadsheet at a shareable URL: cells, formulas, tables.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
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Tool Definition Quality
Average 4.2/5 across 4 of 4 tools scored.
Each tool has a clearly distinct purpose: get_schema provides the base schema and feature index, get_feature_spec retrieves additional schemas for specific features, publish_sheet creates a public sheet, and get_sheet fetches a published sheet. No two tools overlap or cause ambiguity in selection.
All tool names follow a consistent verb_noun pattern: get_ for read operations (get_schema, get_feature_spec, get_sheet) and publish_ for the write operation (publish_sheet). The naming is predictable and clear throughout.
With 4 tools, the server is well-scoped for its purpose of managing the publishing and retrieval of ReoGrid sheets with schema support. Each tool earns its place, and the count is appropriate for the domain.
The server covers the core lifecycle of publish (publish_sheet) and fetch (get_sheet), with schema support to enable valid publishing. Missing update and delete operations are a minor gap, but the descriptions suggest this is intentional in Phase 1, so the surface is largely complete for its stated purpose.
Available Tools
4 toolsget_feature_specAInspect
Returns the full schema fragment for one advanced feature listed in get_schema().features.
| Name | Required | Description | Default |
|---|---|---|---|
| feature | Yes | Feature name from get_schema().features[].name |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It indicates a read operation via 'returns', but does not disclose error behavior, permissions, or side effects. For a simple getter, it provides basic transparency but lacks richer behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. It earns its place by providing the essential purpose and referencing the source of valid input values.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema. The description adequately explains what the tool does and how to obtain the parameter, though it does not describe the exact structure of the returned schema fragment. Given the low complexity, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; the parameter 'feature' is already described as coming from get_schema().features[].name. The tool description repeats this information without adding additional meaning, so the baseline of 3 applies.
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 returns the full schema fragment for one advanced feature, using the specific verb 'returns' and identifying the resource (schema fragment). It also distinguishes itself from siblings by referencing get_schema().features, which lists the features.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It says the feature is listed in get_schema().features, implicitly instructing the user to call get_schema() first to obtain valid feature names. This provides clear context for when to use the tool, though it does not explicitly mention when not to use it or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_schemaAInspect
Returns the base ReoGridJsonDocument schema (envelope + cells, styles, borders, merges) and an index of advanced features. Call get_feature_spec(feature) for any feature in the index before populating it.
| 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 discloses the return content (schema plus index) and advises a sequence (call get_feature_spec before populating), but it does not mention potential side effects, authentication requirements, or rate limits. The read-only nature is implied by 'Returns' but not explicitly stated, so a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, starts with the core purpose, and includes necessary follow-up guidance. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description adequately explains what the tool returns (schema envelope plus index) and how to proceed for advanced features. Given the simplicity of the tool and clear sibling guidance, the description is complete enough for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema covers 100% of the parameter space. The description does not need to add parameter details, and it doesn't, allowing a baseline of 4 for this no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a base ReoGridJsonDocument schema and an index of advanced features, using a specific verb ('Returns') and resource ('ReoGridJsonDocument schema'). It distinguishes itself from siblings by mentioning get_feature_spec explicitly, making its unique role clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance to call get_feature_spec(feature) for any feature in the index before populating it, which serves as a clear alternative usage instruction. However, it does not explicitly state when not to use get_schema or how it relates to other siblings like get_sheet or publish_sheet, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sheetAInspect
Fetches a previously published sheet by its short ID.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Short ID returned by publish_sheet |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. 'Fetches' clearly indicates a read operation, and 'previously published' sets a precondition, but it does not describe error behavior, idempotency, or what happens if the ID is invalid. Minimal but not misleading.
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, well-structured sentence that starts with the main verb and includes all essential information without any redundant words. It is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema), and the description gives the core purpose and precondition. However, since there is no output schema, it would benefit from stating what the return value contains. The sibling context (publish_sheet) helps, but the description alone is somewhat sparse.
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%, and the schema description ('Short ID returned by publish_sheet') fully defines the parameter. The tool description adds no new semantic information beyond what the schema already provides, matching the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetches') and resource ('previously published sheet'), clearly distinguishing it from siblings like get_schema and get_feature_spec. The phrase 'by its short ID' also identifies the key input, making the purpose unmistakable.
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 (must be a previously published sheet, so presumably publish_sheet should be called first) but does not explicitly state when to use this tool vs alternatives or provide exclusions. It leaves the timing and prerequisites to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
publish_sheetAInspect
Publishes a ReoGridJsonDocument and returns a public URL. Anonymous; rate-limited per IP. No expiry in Phase 1. The doc must conform to the schema returned by get_schema().
| Name | Required | Description | Default |
|---|---|---|---|
| doc | Yes | A ReoGridJsonDocument (format=reogrid-json, version=1) | |
| title | No | Optional human-readable title |
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 effectively covers key behavioral traits: authentication (anonymous), rate limiting (per IP), expiration (no expiry in Phase 1), and validation constraint (must conform to get_schema). This is substantial transparency beyond the bare action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences. The first sentence states the core purpose, the second adds key behavioral constraints, and the third adds a validation prerequisite. No wasted words; every sentence contributes necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and no annotations, the description covers the main aspects: what the tool does, the validation requirement, and important behavioral constraints (rate limit, no expiry). It could mention error handling or the exact structure of the returned URL, but the essentials are present. For a simple publish operation, this is adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds meaning by specifying that the 'doc' parameter must conform to the schema returned by get_schema(), which gives validation context not present in the schema property description. The 'title' parameter is already well-described in 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?
Clearly states the action ('Publishes a ReoGridJsonDocument') and the result ('returns a public URL'). This is a specific verb+resource description that distinguishes the tool from its sibling getters (get_feature_spec, get_schema, get_sheet).
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 contextual usage guidance: anonymous access, rate-limiting per IP, and no expiry in Phase 1. It also implies a prerequisite by stating the document must conform to get_schema(), which directs the agent to call a sibling first. No explicit alternatives or exclusions are given, but the context is sufficient for basic use.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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