text2animate

by tom-pettit

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct action: applying full SVGs, patching, polling user edits, creating animations, fetching guidelines, listing animations/styles, and opening preview. No overlap in purpose.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with underscores (e.g., apply_edit, list_animations, open_preview), making them predictable and easy to understand.
Tool Count5/5
8 tools cover the full workflow of creating, editing, listing, and previewing animations without excess. The scope is well-defined and each tool earns its place.
Completeness4/5
Core CRUD operations are covered except for explicit deletion or retrieval of a single animation. The interactive edit loop is robust, but missing a delete tool is a minor gap.
Average 4.1/5 across 8 of 8 tools scored. Lowest: 3.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 11 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.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the tool updates the animation in place with live preview, indicating a mutation. However, no annotations are provided, so the description carries the full burden. It does not detail side effects, permissions, or error conditions.
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?
Two sentences efficiently convey the tool's purpose and a key parameter hint. No extraneous information, though the first sentence could be slightly more structured.
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?
Adequately covers the tool's function and parameter meaning given the absence of an output schema and annotations. Missing details about return values or failure modes, but the workflow context is clear via sibling tool references.
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 baseline is 3. The description reinforces that 'svg' must be the complete updated SVG, but does not add substantial meaning beyond the schema.
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?
Clearly states it applies a regenerated SVG to an animation edit request. The verb 'apply' and resource 'edit request' are specific. However, it does not explicitly distinguish from sibling tool apply_patch, which might handle partial updates.
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?
Implies usage after await_edit_request by mentioning 'from await_edit_request'. Provides context for when to use but no explicit when-not or alternative guidance. Lacks exclusion criteria.
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?
The description only states the result ordering and session scope. With no annotations, it fails to disclose behavioral traits such as whether the list is read-only, if authentication is required, or if the output includes metadata. The agent lacks crucial safety and usage context.
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 is concise and front-loaded with the key action and result. No unnecessary words are present.
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?
While the tool is simple with no parameters, the description omits the return value structure. Since no output schema exists, the description should explain what fields each animation object contains. It also does not define 'session,' leaving ambiguity.
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 zero parameters in the input schema, so the baseline is 4. The description adds no parameter information because none exists, which 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 clearly states the verb 'list', the resource 'animations', the scope 'created this session', and the ordering 'newest first'. It fully distinguishes from sibling tools such as create_animation or list_styles.
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 provided on when to use this tool versus alternatives like get_best_practices or apply_edit. The description does not mention excluded scenarios or prerequisites.
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 provided, so description carries full burden. It describes rendering and opening in browser, and emphasizes that the SVG must be self-contained. However, it lacks details on side effects like whether it replaces previous previews or opens a new tab, and does not mention error handling or state changes.
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 concise with 5 sentences, each adding value: purpose, composition guidance, preliminary step recommendation, style recording note, and SVG requirement. 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?
Given complexity (7 params, no output schema), description explains input requirements and workflow well. However, it does not mention what the tool returns (e.g., success status, animation ID), which is a gap since no output schema is provided.
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?
Schema coverage is 100%, so baseline is 3. The description adds meaning beyond schema by specifying that 'svg' must be a complete document with viewBox and embedded animations, and that 'style' should match the designed style for recording. This adds value for key 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 renders an animated SVG in a local preview UI and opens it in the browser. It distinguishes from siblings by mentioning get_best_practices as a preliminary step, implying this is for creation rather than editing.
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?
It recommends calling get_best_practices first for full guidance, which provides context for when to use this tool. It does not explicitly state when not to use it, but the context against siblings like apply_edit is 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 provided, so the description carries full burden. It honestly describes a read operation (returning guidelines) with optional style input, but does not disclose return format or any potential side effects. Adequate but could add more detail.
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 with purpose, no redundant information. Every word 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?
Given no output schema and no annotations, the description adequately covers purpose and optional style usage, but does not specify the return format (e.g., text, JSON) or response size. Moderately complete.
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?
Schema coverage is 100% for the single parameter. The description adds value by explaining that 'style' can be a preset key or freeform phrase and that it yields concrete art direction, going beyond the schema description.
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 it returns guidelines for composing and animating SVGs, and specifies it should be read before generating an animation. It differentiates from sibling tools like create_animation and list_styles.
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 explicitly says 'Read this before generating an animation,' providing clear when-to-use guidance. It also explains how the optional style parameter adds art direction, though it lacks explicit when-not-to-use or sibling comparisons.
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 burden of behavioral disclosure. The verb 'list' implies a read-only operation with no side effects, but the description does not explicitly state that it is non-destructive or safe. It is adequate but not explicit.
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: the first states the main purpose, the second provides usage guidance with alternatives. No filler or redundant information. Exceptionally concise and well-structured.
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 no parameters and no output schema, the description covers the essential purpose and usage. It could be slightly more complete by hinting at the return format (e.g., list of preset names/IDs), but the current text is sufficient for a simple list tool.
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?
The tool has no parameters, so the description does not need to add parameter information. The mention of freeform phrases for other tools is helpful context but not relevant to this tool's parameters. Baseline for 0 params is 4.
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 clearly states that the tool lists built-in animation style presets. It also mentions alternatives for freeform style phrases, but does not explicitly differentiate from sibling tools that also deal with styles or animations. The purpose is specific and clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (to list built-in presets) and when to use alternatives (create_animation/get_best_practices for freeform phrases). This provides clear guidance on selecting the correct tool.
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 provided, the description carries the full burden. It discloses that the tool may start a web server and opens the browser, which is good, but does not mention potential blocking behavior, error handling, or whether it is safe to invoke multiple times.
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 wasted words. Every word adds value: the verb, the resource, and the prerequisite condition.
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 zero parameters, no output schema, and simple action, the description is complete. It tells the agent to ensure the server is running and then open it in the browser, covering the main behavior.
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?
The input schema has zero parameters and schema coverage is 100%, so the description does not need to add parameter meaning. It appropriately describes the action without needing param details.
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 explicitly states the verb 'open' and the resource 'preview UI', and adds the prerequisite of ensuring the web server is running. This clearly distinguishes it from sibling tools that handle editing, patching, or listing styles.
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 for previewing UI output but does not explicitly state when to use it over alternatives like apply_edit or list_animations. It lacks guidance on exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavioral traits: it states edits are applied in place, the patch is rejected wholesale if any find is missing, and the preview refreshes live. It discloses atomicity and failure mode clearly.
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 concise and front-loaded: purpose first, then usage guidance, then constraints. Every sentence adds value with no redundancy. It fits in a short paragraph.
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 no output schema, the description could be more explicit about return values or response format. However, it covers the essential behavior (live preview, rejection) and constraints well. Slightly incomplete on result details.
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?
Schema coverage is 100%, so baseline is 3. The description adds critical context beyond schema: 'Each find must match the current SVG exactly (verbatim substring)' and explains rejection behavior. This adds meaning to parameter usage.
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 applies small find/replace edits to an animation's SVG in place, lists examples (color, size, etc.), and explicitly distinguishes itself from the sibling 'apply_edit' as a faster alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises 'Prefer this over apply_edit' and provides clear fallback behavior: if a find isn't found the patch is rejected, with instructions to fix the find or fall back to apply_edit. This gives excellent when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. Discloses blocking behavior, timeout, return types ('idle' or edit), and required follow-up actions. Explains the continuous polling loop.
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?
Description is relatively long but well-structured: starts with purpose, then loop guidance, then tool choice. Each sentence adds necessary information. Could be slightly tighter but appropriate for complexity.
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 no parameters, output schema, or annotations, the description fully covers behavior, timing, return types, and integration with sibling tools. No gaps for effective agent usage.
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?
Schema has 0 parameters with 100% coverage, so baseline is 4. No parameter details needed. Description adds context about the tool's function without 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?
Clearly defines the tool as a long-poll for user changes from the preview UI chat box. Uses specific verb ('wait', 'long-poll') and resource ('edit request'). Distinguishes from siblings like apply_patch and apply_edit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use and when-not-to-use instructions: use apply_patch for small tweaks, apply_edit for structural changes. Describes the iterative loop pattern and handling of 'idle' and timeout (~25s).
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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