gemini-mcp

Server Quality Checklist

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Latest release: v1.4.0
Disambiguation5/5
Every tool targets a distinct media type or operation: music, image (generate/edit/set/interact), video, async results, model listing, file management. No two tools have overlapping purposes.
Naming Consistency5/5
All tools follow a consistent 'gemini_{verb}_{noun}' pattern with clear verbs like generate, edit, set, interact, list, upload. No mixing of conventions.
Tool Count5/5
11 tools is well-scoped for a generative AI server covering multiple media types (music, image, video) plus essential utilities (file management, async polling). Each tool earns its place.
Completeness4/5
Covers the full lifecycle for images (generate, edit, set, interact, upload), music (generate, async), video (generate), and file management. Minor gap: gemini_list_models only lists image models, not music/video, but the core generative tasks are well-covered.
Average 4.4/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 16 of 16 community issues answered or closed in the last 6 months
- 120 commits in the last 12 weeks
- Last stable release on August 8, 2026
- 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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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?
The readOnlyHint annotation already indicates no side effects. The description adds context that the tool lists models specific to the API key and includes the default model, but does not disclose additional behavioral traits beyond what annotations already provide. It confirms safe behavior.
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 that fully conveys the tool's purpose without extra words. It is appropriately sized and front-loaded.
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 the tool's simplicity (no parameters, no output schema, no nested objects), the description is sufficiently complete. It explains what is returned (models list and default model). However, it does not detail the structure of each model entry, which is acceptable for a list operation.
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 no parameters, so baseline is 4. The description adds meaning by specifying the model family (Nano Banana / Nano Banana Pro) and that the default model is included, which helps the agent understand what will be returned.
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 Gemini image-generation models available to the API key, including a specific model family (Nano Banana / Nano Banana Pro) and the current default model. This provides specific verb and resource, distinguishing it from sibling tools like gemini_image_generate or gemini_list_files.
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 checking available models and the default, but does not explicitly state when to use it versus alternatives, nor does it provide exclusions or when-not-to-use guidance. Since it's a simple listing tool, it's adequate but could be improved.
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?
Adds behavioral context beyond annotations by stating 'Gemini over-preserves the input; there is no edit-strength control' and suggesting retry with different seed or wording. Annotations already indicate non-read-only and open-world, so the description enriches understanding of side effects.
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 concise, front-loads purpose, then usage and behavioral notes. Every sentence contributes. Minor improvement could be splitting into separate lines for readability.
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?
Adequate for a complex tool, but lacks explicit differentiation from gemini_image_generate (which generates without input images) and does not mention output format or how to handle results when async is not used. Still covers core use cases and edge behaviors.
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 baseline is 3. The description mentions input images and text instruction but does not add meaningful extra semantics beyond what the schema already provides for each parameter.
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 'Edit or compose images' with input images and text instruction, and distinguishes from sibling gemini_interact for multi-turn edits. The verb-resource pair is specific and unambiguous.
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?
Explicitly tells when to use this tool (one-off edits or composing multiple inputs) versus alternatives (gemini_interact for successive edits), and provides advice on handling over-preservation and lack of edit-strength control with retry strategies.
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?
Describes the generation flow (master then scenes) and options like async, inline, confirm. Adds context beyond annotations (readOnlyHint=false, openWorldHint=true) without contradicting 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?
Two sentences efficiently convey core purpose and usage modes. No redundant information, front-loaded with key action.
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?
Covers the main functionality and usage patterns for a complex tool with 22 parameters. Lacks return value details but implies images are returned inline or written to disk.
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 baseline 3. Description summarizes the two modes but adds minimal new parameter meaning, leaving details to the schema.
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?
Description clearly states the tool generates a consistent set of images using a master prompt and per-scene prompts or variations. Distinguishes from siblings like single image generation or 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?
Explicitly explains the two usage modes (scenes or count) implying when to use each. Does not explicitly exclude sibling tools but provides clear context for usage.
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?
Annotations already declare readOnlyHint and openWorldHint. Description adds value by clarifying retention period and expiry behavior, which is 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 short sentences with no wasted words. Front-loaded with purpose, then key behavioral detail.
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?
Covers purpose, returned fields, and retention. No output schema but description compensates. Parameters are covered. Complete for a list 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?
Schema coverage is 100% and the single parameter (page_size) is well described in the schema. Description adds no extra parameter info, but 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?
Description clearly states the action (list) and resource (files, images, photos) along with returned fields (file_uri, MIME types, expiry times). Distinguishes from siblings like gemini_upload_file and gemini_delete_file.
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?
Provides context on retention (~48h) and explains that vanished files are expired, helping the agent understand behavior. No explicit when-not-to-use, but sibling differentiation is clear.
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?
Exceeds annotations by describing long runtimes, async polling, output to disk, idempotency key for avoiding duplicate charges, and the need for confirm=true. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with front-loaded purpose, every sentence adds value. Could benefit from bullet points for clarity, but still concise.
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?
Covers major modes, async, output, and prerequisites. Lacks detailed error handling or example scenarios, but adequate given complexity.
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 baseline is 3. The description adds workflow context (e.g., task modes, image referencing) but does not significantly enhance parameter meaning beyond schema.
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 the tool generates a short video via Gemini omni model, lists specific tasks (text→video, image→video, reference→video, edit), and distinguishes from sibling tools like gemini_music_generate.
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?
Provides guidance on when to use async, the need for confirm and funded account, and preferences for image input methods. Lacks explicit 'when not to use' statements.
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?
Discloses key behaviors beyond annotations: writes to disk or inline (readOnlyHint=false), long runtime, funded account requirement for preview. No contradictions 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with core function. Includes many details but each sentence adds value. Could be slightly more compact, but overall well-structured.
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 complex tool with 17 parameters and no output schema, the description covers usage, models, async behavior, output options, and image reference tips. It is fully complete for agent decision-making.
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 parameters. The description adds minor value (e.g., preferring images_url over images_base64) but doesn't significantly expand 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 clearly states it generates music from a text prompt, specifying models, output formats, and behavior. It distinguishes from sibling tools like gemini_image_generate and gemini_video_generate, making the purpose unambiguous.
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?
Provides guidance on when to use async for long runs, which model to choose, and notes the preview account requirement. It doesn't explicitly exclude alternatives but the context is sufficient for an agent to decide.
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?
Annotations indicate readOnlyHint=false and openWorldHint=true, aligning with the write operation described. The description adds behavioral details: 'upload once,' reusability, and token cost of data_base64. It does not contradict annotations.
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 front-loaded with the main purpose and keywords. It is slightly long but every sentence adds value, covering usage, parameters, and behavioral notes. Minor redundancy (e.g., 'reuse across calls' repeated) but overall efficient.
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 clearly states the return value (file_uri as files/<id>). It covers input sources and expiration. Missing details on error handling or size limits (except in url param), but for a file upload, this is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant value: it explains that exactly one of url, data_base64, or path must be provided, clarifies the confirm parameter's requirement, and warns about token cost for data_base64. This goes well beyond the schema's descriptions.
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 uploads a file to the Gemini Files API and returns a reusable file_uri. It lists supported file types (image, video, audio clip) and distinguishes from siblings like gemini_list_files or gemini_image_generate by focusing on upload-only functionality.
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 provides explicit use cases: upload files to avoid base64 tokens and for reusability across calls. It mentions expiration (~48h) but does not explicitly state when not to use this tool or name alternative tools. However, the sibling context shows no direct upload alternative, 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.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite annotations being minimal (readOnlyHint=false, openWorldHint=true), the description extensively covers behavioral traits: async mode for timeout avoidance, idempotency for retries, preview behavior when confirm is false, default timeouts varying by resolution, and multiple image input methods with preference order. This far exceeds 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The top-level description is concise (2 sentences plus sibling guidance), while parameter details are in the schema. The full description is relatively long but justified by the tool's complexity (22 parameters). It front-loads the key purpose and usage guidance.
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?
With 22 parameters, no output schema, and complex async behavior, the description covers the major flow: async polling, idempotency, input methods, output options (inline/disk). It doesn't explicitly state the return format for sync calls, but overall it's mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds significant value beyond the schema: e.g., model descriptions include usage advice (workhorse, premium, lite), timeout defaults are context-specific, images_url preference over base64 explained. This enriches parameter meaning substantially.
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 'Generate image(s) from a text prompt' with specific model names, and distinguishes from sibling gemini_image_edit. The verb and resource are precise, and the sibling gemini_interact is mentioned for iterative refinement, providing clear differentiation.
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 explicitly advises to 'prefer gemini_interact (multi-turn) as the entry point' for iterative refinement, and details model selection guidance (workhorse vs premium vs lite). No explicit 'when not to use' beyond that, but context is clear.
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?
Annotations declare readOnlyHint=true. The description adds expiration (~10 min), error handling (raises recorded error), and sidecar file existence, which are valuable beyond 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?
Two sentences with no wasted words. First sentence states primary purpose, second details behavior and lifecycle. Front-loaded and efficient.
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 parameter, the description covers purpose, parameter origin, behavior states, statuses, error handling, and expiration. No gaps.
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%, but the description adds context that job_id is returned by a generation tool with async:true, which helps the agent understand its origin and validity.
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 retrieves an async generation result, specifying the action (retrieve), the resource (async generation), and distinguishes from sibling tools like gemini_image_generate which are for creation.
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 explains when to use (when you have a job_id from an async generation), the flow of states (running, completion, failure), and expiration. It lacks explicit when-not-to-use, but context is clear.
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?
The description goes far beyond annotations, detailing timeout behavior (generation still completes client-side timeout), chain recovery on 404s, output format (JPEG), idempotency via idempotency_key, and how continuation works. All behavioral traits are well disclosed.
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 lengthy but every sentence earns its place due to the tool's complexity. It is front-loaded with the core purpose and chaining pattern, then covers edge cases. There is no fluff, though some minor redundancy could be trimmed. Overall well-structured.
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 23 parameters, no output schema, and high complexity, the description is exceptionally complete. It covers async mode, chain recovery, timeout handling, idempotency, and parameter best practices. No gaps are apparent for an agent to use this tool correctly.
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 significant value: model parameter includes model recommendations and capabilities; images/ images_url/images_base64 all include warnings about not re-attaching prior output; continue_last explains fallback to sidecar files; idempotency_key explains purpose. The additions are substantial, justifying a 4.
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 is for 'iterative or multi-step refinement of a single image' via Gemini's Interactions API. It distinguishes from siblings like gemini_image_generate and gemini_image_edit by emphasizing multi-turn chaining, making the purpose unambiguous.
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 provides explicit guidance on when to use this tool (iterative refinement) and when not to (avoid re-starting interaction or re-uploading image each turn). It details alternative approaches like continue_last, explicit chaining via previous_interaction_id, and handling timeouts and 404s, making usage clear.
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?
Annotations declare destructiveHint=true, and the description adds context: deletion causes 404 errors for other references, mentions ~48h expiry, and explains the confirm parameter's role. No contradictions.
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 the primary action, no unnecessary words. Efficient and clear.
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 tool with 2 parameters and no output schema, the description fully covers purpose, usage, behavioral effects, and parameter semantics. Annotations complement well.
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%, and the description reinforces the required parameter (file_uri) and clarifies the confirm parameter's behavior (preview if false). Adds slight value beyond schema by explaining the '~48h expiry' context.
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 deletes uploaded files by file_uri, and distinguishes it from sibling tools (upload, list) by specifying the deletion action and its consequence (404 for references).
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?
Explicitly warns that deleting a file will cause other tool calls referencing it to fail with 404, advising to delete only references you are finished with. Provides clear when-to-use and consequence.
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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