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Glama

Charts by Szum

Server Details

Render charts and data visualizations as SVG or PNG images from a JSON config.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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Tool DescriptionsA

Average 4.1/5 across 5 of 5 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool has a clearly distinct purpose: examples, mark types, themes, rendering, and validation. No overlap.

Naming Consistency5/5

All tools use a consistent verb_noun pattern with lowercase underscores (e.g., get_examples, list_marks).

Tool Count5/5

Five tools is appropriate for a charting server, covering metadata, validation, and rendering without excess or deficiency.

Completeness5/5

The tool surface covers the full workflow: exploring mark types/themes, getting examples, validating configs, and rendering. No obvious gaps.

Available Tools

5 tools
get_examplesA
Read-only
Inspect

Get example chart configs. Optionally filter by mark type. Returns ready-to-use JSON configs.

ParametersJSON Schema
NameRequiredDescriptionDefault
mark_typeNoFilter examples by mark type
Behavior3/5

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

Annotations already declare readOnlyHint=true, and the description adds only that it returns 'ready-to-use JSON configs' with optional filtering. No additional behavioral traits beyond what annotations provide.

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

Conciseness5/5

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

Two succinct sentences, front-loaded with the core action. No wasted words.

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

Completeness5/5

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

For a simple retrieval tool with one optional parameter and annotations, the description adequately explains what it returns and the available filter.

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

Parameters3/5

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

Schema description coverage is 100% for the single parameter, so baseline is 3. The description merely restates the parameter purpose without adding new information.

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

Purpose5/5

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

Clearly states it gets example chart configs with optional filtering by mark type, and distinguishes from sibling tools like list_marks and render_chart.

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?

Implies usage context but lacks explicit when-not or alternatives. The description indicates optional filtering, which is helpful but could be more directive.

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

list_marksA
Read-only
Inspect

List all available mark types with their specific properties and defaults.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Behavior3/5

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

Annotations already mark readOnlyHint=true, so the description's claim of listing is consistent. The description adds that it includes 'specific properties and defaults,' but no further behavioral traits (e.g., pagination, sorting) are disclosed. No contradiction with annotations.

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

Conciseness5/5

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

One sentence that is direct and to the point. Every word serves a purpose; no fluff.

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

Completeness5/5

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

Given the tool's simplicity (0 params, no output schema), the description fully covers what the tool does. It lists mark types with properties and defaults, which is sufficient for an agent to understand the outcome.

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

Parameters4/5

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

No parameters exist, and schema description coverage is 100%. Baseline for zero-param tools is 4. The description adds no parameter info but mentions the output will contain 'properties and defaults,' which is beyond schema structure.

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

Purpose5/5

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

The description uses a specific verb ('list') and resource ('mark types') with added detail about properties and defaults. It clearly distinguishes from siblings like get_examples, list_themes, render_chart, validate_chart, which have different functions.

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 implicitly indicates use for retrieving all mark types, and siblings are distinct enough to avoid confusion. However, it does not explicitly state when to use this tool versus alternatives, nor provide exclusion criteria.

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

list_themesA
Read-only
Inspect

List all available chart theme names.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint. The description does not add behavioral context beyond what annotations provide, but it also does not contradict them.

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 unnecessary words, making it highly concise and easy to parse.

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

Completeness5/5

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

For a zero-parameter, read-only list tool, the description fully informs the agent of what to expect (list of theme names). No output schema is needed for this simple return.

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

Parameters4/5

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

There are no parameters, and schema coverage is 100% by default. The description adds no parameter info, which is appropriate; baseline 4 for zero parameters.

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

Purpose5/5

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

The description clearly states the tool lists all available chart theme names, using a specific verb and resource, and it distinguishes from sibling tools like get_examples or list_marks.

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?

While no explicit when-to-use or alternatives are stated, the context is clear: when you need available chart themes, use this tool. Sibling tools cover different concerns, so no confusion arises.

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

render_chartAInspect

Render a chart from a JSON config. Returns a URL to the rendered image (expires after 10 min). Each call counts as one render against your monthly limit. "format" is required – set to "svg" or "png".

ParametersJSON Schema
NameRequiredDescriptionDefault
configYesJSON string of the chart configuration
Behavior3/5

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

Adds useful traits: URL expiry, monthly limit. However, contradiction about required 'format' undermines transparency. Annotations already indicate readOnlyHint=false.

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

Conciseness5/5

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

Two concise sentences, front-loaded with purpose and output. No wasted words.

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?

Covers input, output, expiry, limit. But the phantom 'format' parameter creates incompleteness and inconsistency.

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

Parameters2/5

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

Schema covers config param fully. Description adds 'format' as required, but it's not in schema, causing confusion and misleading the AI agent.

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

Purpose5/5

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

The description clearly states the tool renders a chart from JSON config and returns a URL. It distinguishes from siblings like validate_chart and get_examples.

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?

Mentions monthly limit and expiration, but also says 'format' is required, which conflicts with the schema (no format param). No explicit when-to-use or alternatives.

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

validate_chartA
Read-only
Inspect

Validate a chart config against the schema. Returns validation errors or confirms the config is valid. Does not count as a render.

ParametersJSON Schema
NameRequiredDescriptionDefault
configYesJSON string of the chart configuration to validate
Behavior3/5

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

Annotations provide readOnlyHint=true; description adds 'Does not count as a render' which clarifies side effects. No further behavioral details like error handling or performance are disclosed.

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

Conciseness5/5

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

Two sentences, front-loaded, no wasted words. Structure is efficient and direct.

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

Completeness5/5

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

For a simple validation tool with one parameter, no output schema, and annotations present, the description is complete enough: it clarifies purpose, outcome, and side-effect distinction.

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%; description does not add meaning beyond the schema's 'JSON string of the chart configuration to validate'. Baseline 3 applies.

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

Purpose5/5

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

The description clearly states 'Validate a chart config against the schema' with specific verb and resource, and distinguishes from sibling 'render_chart' by noting it does not count as a render.

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 implicitly recommends use for validation before rendering and explicitly excludes render behavior, but does not mention when not to use or alternatives like 'get_examples'.

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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