MCP Gemini CrunchTools

Server Quality Checklist

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Latest release: v0.3.0
Disambiguation2/5
Multiple tools have heavily overlapping purposes: gemini_query_tool, gemini_brainstorm_tool, and the various gemini_analyze_* tools all accept free-form text prompts to Gemini, making it nearly impossible to choose correctly. Pairs like gemini_generate_image_with_input_tool vs gemini_start_image_edit_tool, gemini_summarize_tool vs gemini_summarize_pdf_tool, and especially gemini_youtube_tool vs gemini_youtube_summary_tool create genuine selection ambiguity.
Naming Consistency2/5
The gemini_ prefix and _tool suffix are consistent, but the internal structure is a jumble: verb_noun (summarize_pdf, query_cache) mixes with noun_verb (imagen_generate), verb-only (speak, extract), and noun-only (youtube, structured) forms. The adjacency of generate_image, generate_image_with_input, and imagen_generate uses three different orderings for the same concept with no predictable rule.
Tool Count2/5
At 39 tools, this far exceeds a well-scoped surface, but the breadth might justify it since the server spans text, images, video, audio, documents, research, caching, and code execution. However, most of these domains don't need 3-6 near-synonyms each; the server could easily be consolidated to ~20 distinct capabilities without losing functionality.
Completeness4/5
For a Gemini API wrapper, the coverage is remarkably thorough: generation, editing, analysis, video, TTS/voice, research, caching, structured output, and code execution are all represented. Minor gaps exist (e.g., no way to list or cancel video operations beyond check, no delete for research sessions, no way to select a voice when calling speak despite list_voices existing), but these are edge cases rather than workflow-breaking holes.
Average 3.1/5 across 39 of 39 tools scored. Lowest: 1.7/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 1 commit in the last 12 weeks
- Last stable release on March 2, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under AGPL 3.0.
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

Behavior1/5
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 only says 'Analyze a YouTube video,' which gives no information about side effects, required permissions, output format, or any operational details. This is a significant lack of transparency for a tool that presumably calls external APIs and processes video content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise in length. However, it is under-specified to the point of being nearly content-free. It lacks necessary structure or elaboration, so while it is brief, it does not serve the agent well. Concise but ineffective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description gives no indication of what analysis is performed, what questions it can answer, or how it handles errors. With a sibling gemini_youtube_summary_tool, the description fails to clarify the unique value proposition. The tool has 3 parameters and a complex task (video analysis), so the description is grossly inadequate.
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 each parameter has a basic description ('YouTube video URL', 'Model to use', 'Question or instruction about the video'). The tool description adds nothing beyond the schema, but since the schema already documents parameters adequately, the baseline of 3 is appropriate. However, the descriptions are minimal and do not explain parameter choices (e.g., model options), yet that's not the tool description's fault.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Analyze a YouTube video' is extremely vague. It states a verb and resource but does not specify the nature of the analysis, what insights are generated, or how it differs from the sibling gemini_youtube_summary_tool. There is no differentiation or detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 gemini_youtube_summary_tool or gemini_check_video_tool. It lacks any context about use cases, prerequisites, or conditions when it should or should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full burden for behavioral disclosure. It fails to mention any limitations (e.g., number of URLs, supported content types), side effects, rate limits, or what the tool returns. The description is purely nominal and offers no transparency beyond 'analyze'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise and front-loaded. However, it is under-specified rather than appropriately concise; it provides no elaboration or structure. It is not verbose, but the brevity comes at the cost of usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, output schema, multiple sibling analysis tools), the description is severely incomplete. It provides no detail on expected outputs, interaction with other tools, or what 'analyze' entails. The agent cannot infer how to correctly invoke it without additional context.
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 all 4 parameters have descriptions. The tool description adds no extra meaning to the parameters, but per rubric, with high coverage the baseline is 3. The description does not compensate for any missing param detail, but the schema handles it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Analyze one or more URLs.', which is essentially a restatement of the tool name. It does not specify what kind of analysis is performed (e.g., summarize, extract, QA) and is indistinguishable from sibling tools like gemini_analyze_text_tool or gemini_extract_from_url_tool. The purpose is minimally clear but lacks specificity.
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?
There is no guidance on when to use this tool versus alternatives. It provides no context, prerequisites, or comparisons to similar URL analysis tools. The description only states the function with no insights into appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It does not mention whether the tool performs network requests, has side effects, requires specific permissions, or what it returns. The user is left completely in the dark about the tool's runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, which is efficient, but over-trimming reduces usefulness. It lacks essential details that could be conveyed without bloat, such as a brief explanation of the comparison types. It is a single sentence, but not well-structured for informative purposes.
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 an output schema is present (as indicated by context), the description does not explain the return format, error conditions, or any side effects. There is no mention of required context, limitations, or how the 'model' and 'aspect' parameters affect the comparison. The tool feels incomplete for practical use.
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 schema provides descriptions for all parameters (url1, url2, model, aspect), achieving 100% coverage. The descriptions are concise but adequate for basic understanding. However, the description does not add any extra context beyond the schema, so it slightly misses full value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Compare two URLs.' is extremely vague. It does not specify what kind of comparison is performed (content, structure, performance, etc.) or what the output will be. It is distinguishable from sibling tools only by the verb 'Compare', but lacks enough detail to clearly convey the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 'analyze_url' or 'extract_from_url'. There is no mention of scenarios, prerequisites, or context in which comparison is appropriate.
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?
No annotations are provided, placing the full burden on the description. 'Analyze code' is behaviorally neutral and doesn't disclose side effects (though seemingly none), output format, response size, or limits. It's not misleading, but provides zero transparency value. Annotation contradiction: false.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
At exactly 5 words, it's undeniably short and contains no filler. However, 'with Gemini' is redundant (the tool is already in the Gemini family and the name confirms it), reducing effective content to 2 words. Brief but not effectively so.
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?
For a 4-parameter tool with an output schema and 38 siblings, this description is severely under-specified. The 'focus' parameter implies meaningful capability (security, performance, bugs) that could clarify 'analysis', but the description fails to surface this. The tool name does most of the conceptual heavy lifting.
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?
With 100% schema description coverage, the baseline is 3. The description adds no parameter semantics beyond the schema, but doesn't need to — the schema fully documents 'code', 'focus', 'model', and 'language' including defaults and the focus enum values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Analyze code with Gemini' is essentially a rewording of the tool name itself, making it a tautology. It provides no scope details (e.g., what aspects of code are analyzed, what the output represents) and fails to differentiate from sibling tools like gemini_analyze_text_tool or gemini_run_code_tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers zero guidance on when to use this tool versus its 30+ siblings. It doesn't mention that this is for static analysis rather than execution, and explicitly fails to state that code execution should go to gemini_run_code_tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavioral traits. It says nothing about side effects, permissions, rate limits, or output behavior. The agent has no indication whether this is a read-only operation or what the response format looks like, making it a black box.
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 a single sentence with no fluff or redundancy. It is appropriately concise, though it is arguably too terse, sacrificing helpfulness in favor of brevity. It earns its place by stating the core purpose but does not elaborate beyond that.
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?
Given the tool's multiple analysis modes and the large number of sibling tools, the description is incomplete. It does not explain the different analysis types or how this tool relates to similar text-processing tools. The output schema exists, but the description still fails to provide enough context for an agent to choose it confidently.
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?
The schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning about the parameters; it does not mention text, model, or analysis_type, nor does it expand on the allowed values. The schema already documents these parameters, so the description provides no additional semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource ('Analyze text'), which distinguishes it from tools analyzing images, code, or documents. However, it is generic and does not specify the types of analysis (general, sentiment, tone, summary) that are defined in the schema, nor does it differentiate from other text-related tools like gemini_summarize_tool or gemini_query_tool.
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?
The description provides no guidance on when to use this tool versus the many sibling tools. It does not mention any exclusions, alternatives, or specific use cases. An agent would be left to infer usage from the name and schema, which is insufficient.
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?
With no annotations, the description must carry the full burden of behavioral disclosure. 'Extract specific data from a URL' does not reveal what the extraction process does, whether it fetches and parses the page, what formats are supported, whether authentication is needed, or what side effects (if any) occur. This is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no filler or redundancy. However, brevity here comes from under-specification rather than efficient communication of necessary details. It is concise but not sufficiently informative.
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?
Given the tool has four parameters, one required, and no annotations, the sparse description is not complete enough. Users/agents cannot infer key facts like what 'custom_fields' accepts, how 'data_type' values map to output, which models are valid, or how this differs from gemini_analyze_url_tool. The output schema exists, but the description still needs to cover usage context.
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?
The schema has 100% parameter description coverage, so the schema itself documents each property clearly. The description adds nothing beyond the schema; it neither clarifies parameter relationships nor provides examples. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb+resource ('Extract specific data from a URL') but 'specific data' is vague and does not differentiate this tool from closely related siblings like gemini_analyze_url_tool, gemini_compare_urls_tool, or gemini_extract_tool. It gives a general sense of purpose but lacks specificity about what kinds of extraction are supported.
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 usage guidance is provided. The description does not explain when to use this tool versus the many similar sibling tools, nor does it mention prerequisites, limitations, or typical use cases. The only cue is the tool name itself, which is insufficient.
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?
With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'Get structured JSON output from Gemini.' It does not explain how the schema constrains output, whether the tool can fail, grounding behavior, revision behavior for structured output, or any operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words, which is structurally clean. However, it is so under-specified that conciseness borders on incompleteness rather than efficient communication.
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?
Given the tool has four parameters and exists among many similar Gemini tools, the description is far too thin. The presence of an output schema reduces the need to explain return values, but the description still lacks the contextual information needed to select this tool over its siblings.
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 four parameters. The description adds no parameter-level meaning beyond what the schema provides, keeping the score at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool gets structured JSON output from Gemini, so the basic action and resource are clear. However, it is vague about what 'structured output' entails and does not distinguish this tool from siblings like gemini_query_tool or gemini_extract_tool.
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 about when to use this tool versus alternatives. The description is a single sentence with no context, prerequisites, or exclusions, and the large sibling list makes this gap significant.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention that the tool is read-only, whether it reads the file from the local system, what the output structure is, or any side effects. The presence of an output schema is not referenced, and no details about error handling or limitations are given. The description is purely functional with no transparency into behavior.
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 a single sentence, direct and to the point, with no redundant phrasing. It effectively communicates the core action without fluff. However, it is perhaps too terse, lacking any additional context that could be conveyed concisely, but it does not suffer from verbosity.
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?
Given the absence of annotations and the minimal description, the tool is severely under-specified. It lacks guidance on selection criteria, output details, and behavioral expectations. The many sibling tools highlight a need for clarity on when this generic 'analyze' tool is appropriate, but nothing is provided. Overall, the description is insufficient for an agent to confidently use it correctly.
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 each parameter has a description: 'Absolute path to the document', 'Question or instruction about the document', and 'Model to use'. These descriptions are clear and sufficient for basic understanding, but they lack additional context such as allowed values for model (e.g., 'flash' vs other options), formatting rules, or how the question parameter affects output. The descriptions are adequate but shallow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool analyzes documents of various types (PDF, DOCX, TXT, etc.), which identifies the general function but uses the vague verb 'analyze' without specifying what kind of analysis is performed (summary, extraction, QA, etc.). While it differentiates from some siblings by covering multiple formats, it does not clearly distinguish from tools like gemini_summarize_tool or gemini_extract_tables_tool, which have more specific purposes.
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 the numerous sibling tools. There is no mention of prerequisites, file size limits, or scenarios where this tool is preferred over gemini_summarize_pdf_tool or gemini_extract_tables_tool. The description offers no contextual hints for selection.
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?
No annotations are provided, so the description must carry the burden. It only says 'Extract structured data' and gives no clue about side effects, permissions, limitations, or processing behavior. The agent cannot anticipate whether the tool is read-only, requires authentication, or has special constraints. This is minimal and insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence), which could be seen as concise, but it under-specifies the tool's capabilities and usage. It does not add sufficient value for an agent to effectively decide when to use it. This is under-specification rather than concise efficiency.
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 an output schema exists (so return format is covered elsewhere), the tool has four parameters and sits among many similar tools. The description lacks context about what types of structured data can be extracted, how to choose extract_type, and when to use this tool versus siblings. This makes the description incomplete for an agent to correctly invoke it.
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 adds no extra meaning beyond the schema, but the schema already documents each parameter adequately. The description does not clarify the relationship between extract_type and custom_fields, or provide examples, but it meets the baseline since the schema is self-sufficient.
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 the action ('Extract') and resource ('structured data from text'), giving a basic sense of purpose. However, it does not differentiate from sibling tools like gemini_extract_tables_tool or gemini_analyze_text_tool, which also involve extraction/analysis. It earns a 4 because it is clear but lacks sibling distinction.
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 given on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, leaving the agent to infer usage from the name and schema. This is a significant gap, especially given the many overlapping Gemini tools.
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?
With no annotations provided, the description carries the full burden for behavioral disclosure, but it only says 'using Gemini' (already implied by the tool name). It does not disclose that the tool generates a configurable number of ideas, uses a default model, accepts optional context, has no side effects, or what the output shape will be.
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 a single focused sentence with no structural waste. 'using Gemini' is somewhat redundant with the tool name, but the sentence is short and the action is front-loaded.
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?
The schema and output schema cover the mechanical aspects, but the tool description is too thin for a tool with four parameters and many close siblings. It lacks usage criteria and behavior context, leaving the agent to guess when brainstorming is appropriate and what the tool will actually produce.
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?
The schema describes all four parameters with 100% coverage, so the baseline is 3 and the description need not repeat parameter details. The description does not add value beyond the schema, but no parameter semantics are missing from the structured 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?
The description states a specific action ('Brainstorm ideas') and a target resource ('a topic'), making the core purpose clear. It is distinguishable from query/analyze/summarize siblings by the creative ideation focus, though it does not explicitly differentiate itself from gemini_dialogue_tool or gemini_deep_research_tool.
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 given about when to prefer this tool over alternatives such as gemini_query_tool or gemini_deep_research_tool. There is no when-to-use, when-not-to-use, or prerequisite information; the only usage signal is the implied 'brainstorm' action.
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?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does not mention whether the operation is read-only, any side effects, performance characteristics, or limitations. Minimal transparency beyond the basic function.
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 extremely concise, using a single sentence with no fluff. It is efficient to parse, though slightly under-specified, earning a 4 rather than 5.
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?
With an output schema present and full parameter schema coverage, the description is not required to explain return values. However, given sibling tools with overlapping purposes, some contextual detail about the scope or limitations of 'extract tables' would improve completeness. It is adequate but not outstanding.
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 adds no parameter-level detail beyond what the schema already provides, so it neither elevates nor degrades the score.
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 'Extract tables from a document.' clearly states the verb (extract) and resource (tables from a document). It is specific, but it does not distinguish itself from sibling tools like gemini_extract_tool or gemini_analyze_document_tool, so it misses the highest marks.
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?
The description offers no guidance on when to use this tool versus alternatives, no mention of prerequisites, exclusions, or use cases. It is a single sentence with no context clues for tool selection.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'generate an image' without any details about side effects, costs, latency, output format, or error conditions. Since this is a generation (non-destructive) operation, the lack of transparency is not harmful, but it still doesn't offer any insights beyond the basic action.
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 a single, clear sentence that is front-loaded with the core action. It avoids redundancy and wastes no words. It is concise but does not include structured elements like bullet points, which is acceptable for a simple tool.
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?
Given the existence of several sibling image-generation tools (e.g., 'with_input', 'imagen', 'image_prompt'), the description is not complete enough to guide the agent. It doesn't mention when to prefer this tool over others, nor does it indicate that the output schema exists (though it does). The description is minimal and leaves ambiguity about its unique value proposition.
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?
The schema covers 100% of the parameters (prompt, style, image_size, aspect_ratio, use_google_search), so the baseline is 3. The description does not add any additional meaning beyond what the schema already provides. It simply reiterates the core purpose without elaborating on parameter usage or constraints.
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 the action (generate an image), the resource (an image from a text prompt), and the model ('Gemini's native image model'). It is specific enough to distinguish from the Imagen tool but does not explicitly differentiate from the similar sibling 'gemini_generate_image_with_input_tool', which also generates images. The addition of 'native' provides some context.
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?
There is no guidance on when to use this tool versus alternatives like 'gemini_generate_image_with_input_tool' or 'gemini_imagen_generate_tool'. No context is given about prerequisites, restrictions, or appropriate scenarios. The description simply states what it does, not when to apply it.
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?
With no annotations, the description carries the full burden of behavioral disclosure. It does not mention that this is a read-only operation, what happens if the cache does not exist, or any error behavior. The single phrase 'Query content in a cache' adds no transparency beyond the basic action.
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 a single concise sentence with no fluff. It is front-loaded with the verb, but it is slightly under-specified for a tool that depends on a prior cache creation step. Still, it is efficient.
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?
Although an output schema exists, the description fails to provide important context such as the relationship to gemini_create_cache_tool or the requirement that a cache must already exist. It is too sparse to be considered complete for a query tool with dependencies.
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%, with both parameters already documented in the schema. The description adds no additional meaning beyond what the schema provides, so the baseline of 3 is appropriate.
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 'Query content in a cache' clearly states a specific verb (query) and resource (cache), distinguishing it from sibling tools like gemini_query_tool which likely query other data. It does not elaborate on what a 'cache' is, but the presence of gemini_create_cache_tool provides context.
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, nor any prerequisites such as the need to create a cache first. The description is a bare statement without usage context or exclusions.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only repeats the Google Search grounding capability already present in the schema and does not explain costs, latency, response behavior, or any caveats.
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 two short sentences with no filler. It immediately states the main purpose and a distinguishing feature, making it easy to scan and consume.
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?
Even with full schema coverage and an output schema, the description lacks the context needed to choose among ~39 sibling Gemini tools. It does not explain when to use this generic query tool instead of specialized tools, and the absence of annotations leaves behavioral gaps unaddressed.
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 all parameters are already documented in the structured schema. The description adds little beyond restating the use_google_search behavior, so the baseline score of 3 is appropriate.
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 the action ('Query Gemini') and the input ('with a prompt'), and mentions Google Search grounding as a feature. However, it does not differentiate this generic query tool from the many specialized sibling tools that also query Gemini.
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 specialized alternatives like gemini_summarize_tool, gemini_search_tool, or gemini_analyze_text_tool. The only hint is that Google Search grounding is supported, but no exclusions or explicit use cases are mentioned.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it only states the basic function. It does not mention any side effects, output formats, rate limits, or potential limitations, offering minimal insight into the tool's runtime behavior beyond the obvious.
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 a single declarative sentence that efficiently communicates the tool's purpose. It is concise without unnecessary verbosity, though it could be seen as slightly under-specified rather than elegantly compact. Still, for the tool's simplicity, it works well.
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?
For a simple TTS tool with two parameters and an output schema, the description covers the essential action. However, it lacks useful context such as input length limits, supported audio formats, or typical use cases. It's adequate but leaves room for enhancement, matching the 'minimum viable' standard.
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?
The input schema already documents both 'text' and 'voice' parameters completely, including a default value and enumerated voice options. The description adds no additional semantic value, but since the schema coverage is 100%, the baseline score of 3 is appropriate.
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 'Convert text to speech' uses a clear verb-resource pairing that unambiguously conveys the tool's core function. It effectively differentiates this tool from siblings like image generation or query tools, though it could add more contextual distinction. While not as descriptive as the top examples, it meets the criteria for a specific and understandable purpose.
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?
The description provides no guidance on when to use this tool versus the many sibling tools, no prerequisites, and no exclusions. It simply states the action without any contextual advice, leaving the agent without direction on appropriate usage scenarios or alternatives.
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 does not mention whether the operation is read-only, any side effects, or potential errors. Without annotations and with no such disclosure, agents cannot infer the tool's behavioral impact.
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 exceedingly brief—one sentence—which is concise and free of fluff. However, it is so terse that it sacrifices necessary detail, so it is not optimally structured for agent understanding.
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?
Given the tool has an output schema (though not shown), the description does not explain what the summary output looks like or any error handling. It lacks critical context about return values and potential failure modes, making it incomplete.
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?
The schema descriptions for 'model', 'style', and 'file_path' are present and provide basic meaning, so coverage is 100%. However, the tool description itself adds no extra context or constraints, and the parameter descriptions are generic (e.g., 'Model to use' could be clearer).
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 the action ('Summarize') and the resource ('PDF document'), which is specific enough. However, it lacks distinguishing details from sibling tools like gemini_summarize_tool or gemini_analyze_document_tool, which might also handle text summarization.
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 over alternatives, nor any prerequisites or context. The description is too minimal to help an agent decide if this is the appropriate tool.
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?
With no annotations, the description must convey behavior, but it only says 'summarize content'. It does not disclose whether the tool is read-only, whether it has side effects, or what the return structure is. This leaves significant behavioral ambiguity.
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 extremely concise, consisting of a single sentence that captures the core purpose. There is no redundancy or unnecessary detail, making it efficient and well-structured for a simple tool.
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?
The description is minimal but adequate for a straightforward summarization tool. However, it lacks context on expected input formats, output structure, or when to prefer this tool over other summarization-related siblings. The schema fills some gaps, but the description could provide more contextual completeness.
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?
All parameters (model, format, length, content) have descriptions in the schema, providing full coverage. The description does not add extra meaning beyond the schema, but since schema coverage is high, the baseline score of 3 is appropriate.
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 the tool's function: summarizing content with Gemini. It is specific and distinguishes itself from sibling tools by the action 'summarize'. However, it could be more precise about what types of content (e.g., text, documents) are supported.
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, nor any prerequisites or limitations. The description only states the action without context for appropriate invocation.
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?
With no annotations provided, the description carries full responsibility for disclosing behavior. 'Check the status' is too minimal; it does not state whether the operation is read-only, what statuses might be returned, or whether it requires an active research session. This lacks the detail needed for safe autonomous invocation.
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, clear sentence with no wasted words. It is appropriately sized for a simple status-check tool.
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?
For a tool that is part of a larger research workflow, the description is incomplete. It lacks any mention of prerequisites (e.g., the research must already be running), expectations about the output, or how to handle failures. The presence of an output schema alleviates return-value documentation, but context for use is missing.
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% (research_id is described as 'The research ID from gemini_deep_research.'), so the schema fully documents the parameter. The description adds no further meaning, which is acceptable given the coverage.
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 'Check the status of a deep research operation' clearly states a specific action (check status) on a specific resource (deep research operation), distinguishing it from sibling tools like gemini_deep_research_tool (which starts research) and gemini_research_followup_tool (which continues it).
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 given on when to use this tool versus alternatives. It does not mention that it should be used after starting a deep research operation or how it relates to sibling tools, leaving the agent without context for selection.
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?
With no annotations, the description carries the full burden. It only mentions the high-level purpose but does not disclose behavioral traits like whether creation is immediate, how errors surface, permission requirements, or any side effects. The phrase 'upload content once' hints at a write operation but is not detailed.
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 purpose, and zero extraneous text. Every word earns its place, making it highly efficient.
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?
Despite full schema coverage and an output schema, the description leaves ambiguity about how to actually provide the content (via content or file_path) and what the expected output is. It does not mention that either content or file_path should be set, nor does it hint at the ttl_minutes or display_name defaults. This is insufficient for an agent to confidently use the 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 description coverage is 100%, so the description adds no value beyond what the schema already provides. It does not clarify the relationship between content and file_path or the consequences of leaving them null, which could confuse an agent.
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 the tool creates a content cache for repeated queries, which distinguishes it from sibling cache tools (query, list, delete). However, it does not explicitly mention the dual input methods (content vs file_path) or the model parameter, so it lacks some specificity.
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?
It implies usage for repeated queries by saying 'query it multiple times without re-sending', but does not explicitly state when to prefer this over other cache tools or provide exclusions. No alternatives are mentioned, so guidance is only implicit.
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?
With no annotations, the description carries the full burden, but it only restates the action. It does not disclose output format, whether the audio is returned as a file/URL, how speaker labels map to voices, or any other behavioral traits.
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, focused sentence that immediately communicates the purpose without redundancy. It is front-loaded and appropriately concise.
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?
Despite having parameter descriptions and an output schema, the description is under-specified. It lacks guidance on how to format dialogue text, how the two voices are assigned to speakers, and when to use this tool over gemini_speak_tool, making it incomplete for a generation 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 description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; it does not clarify how 'text' with speaker labels should be structured or how voice1/voice2 are used.
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 'Generate multi-voice dialogue audio' clearly states the tool's function with a specific verb and resource. The 'multi-voice dialogue' qualifier differentiates it from sibling tools like gemini_speak_tool (single-voice speech) and gemini_generate_video_tool.
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 usage guidance is provided. The description does not mention when to use this tool vs alternatives, nor does it note any exclusions or prerequisites. It only defines the core action.
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 the transparency burden. 'Check the status' implies a harmless read operation, which is positive. However, it doesn't explain what statuses mean, whether agents should poll repeatedly, or how to handle non-terminal states. Since an output schema exists, return values are partially covered.
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?
A single clear sentence that states purpose in 9 words. Front-loaded with the action 'Check the status' and the context 'video generation operation.' 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?
For a simple status-check tool with one self-documenting parameter and an output schema, the minimal description is borderline adequate. It doesn't explain polling semantics or terminal states, but given the tool's simplicity and the presence of gemini_generate_video_tool as context, it's acceptable though not complete.
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% with the single operation_name parameter well-described ('The operation name from gemini_generate_video'). The description adds no additional parameter semantics, but with full schema coverage, the baseline 3 applies.
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 single sentence clearly identifies the verb (check), the object (status), and the context (video generation operation). The purpose is unambiguous even without reading the schema. Could be enhanced by listing what status values the agent might encounter, but the core purpose is fully stated.
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 when-to-use guidance is provided. There's no mention that the operation_name comes from gemini_generate_video_tool (though the parameter schema references it), and no polling/status-interpretation guidance. The sibling list shows a generate_video_tool exists but the description doesn't connect them.
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?
With no annotations, the description must disclose behavioral traits. It only states the core function without mentioning side effects, model-specific tokenization behavior, or any limitations. The read-only nature is implied but not explicit, and no other behavior is conveyed.
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 zero irrelevant content. It is as concise as possible while still conveying the core purpose.
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?
The tool is simple and an output schema exists, so return values need not be explained. However, the description is minimal and lacks context about model-specific tokenization or usage scenarios, leaving a moderate gap in completeness.
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%, with both 'model' and 'content' documented. The tool description adds no extra meaning beyond the schema, so the baseline of 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 uses a specific verb 'count' and clearly identifies the resource 'tokens in content'. It uniquely distinguishes this tool from siblings, none of which mention token counting.
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. The one-sentence description lacks any context about prerequisites, use cases, or why an agent would choose this over other gemini tools.
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?
No annotations are provided, so the description must disclose side effects. It only states the action without mentioning that deletion is permanent/irreversible, whether it affects dependent operations, or any permissions required. For a destructive operation, this lacks necessary transparency.
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 short sentence, front-loaded with the verb and object. No fluff or redundancy. Perfectly concise for a simple delete operation.
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?
The description is minimal but sufficient for a simple delete with a single parameter and an output schema (though its content is unknown). It lacks any note on use cases, like 'use after cache is no longer needed' or error conditions, but for a straightforward delete it may be adequate.
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?
The schema already documents the single parameter 'cache_name' with a description. The tool description adds no additional semantic meaning, such as format, expected identifier, or how to obtain it. Since schema coverage is 100%, the baseline is 3, and no extra value is added.
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 action (delete) and the target (content cache). The verb 'delete' is specific and unambiguous, and the resource 'content cache' is precise. This distinguishes it from sibling tools like create, query, or list caches.
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 on when to use this tool versus alternatives such as gemini_create_cache_tool or gemini_list_caches_tool. It simply says 'Delete a content cache' without context like prerequisites (e.g., cache must exist) or typical use cases (e.g., after no longer needed).
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?
With no annotations, the description carries full behavioral burden. It reveals nothing about how the tool operates—whether it asks follow-up questions, returns a refined prompt, or modifies its output based on the 'model' parameter. This is a significant transparency gap.
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 a single seven-word sentence, extremely concise and front-loaded. It earns its place but is under-specified; however, conciseness is strong compared to verbose alternatives.
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?
Although the tool has an output schema, the description is incomplete for an agent to confidently select it. It lacks guidance on return format, when to use relative to sibling tools, and any behavioral expectations, making it insufficient for a tool without annotations.
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?
All four parameters have descriptions in the input schema (100% coverage), so baseline is 3. The description adds no extra parameter semantics, but the schema already documents the meaning of description, mood, style, and model adequately.
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 it 'crafts an effective image generation prompt,' using a specific verb and resource. This distinguishes it from sibling tools like gemini_generate_image_tool, which actually generate images, and make the tool's 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternative recommendations are provided. The description implies this tool is for crafting prompts before image generation, but it doesn't explain when to choose it over gemini_brainstorm_tool or when not to use it, leaving usage guidance implied.
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?
No annotations are provided, so the description carries the full burden. It only states 'Summarize a YouTube video' with no disclosure about requirements (e.g., captions), limitations (e.g., video length), 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler or redundancy. It is front-loaded and easy to parse.
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?
The output schema exists and params are documented, but the description omits behavioral constraints and usage caveats such as video length or caption requirements. It is minimally sufficient for a simple tool but lacks robustness.
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?
The input schema already describes all 3 parameters (url, model, style) with 100% coverage. The tool description adds no extra parameter meaning, so the baseline score of 3 is appropriate.
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 uses the specific verb 'Summarize' and resource 'YouTube video', clearly stating what the tool does. It distinguishes from generic summarization tools by specifying YouTube, though it doesn't explicitly contrast with the sibling gemini_youtube_tool.
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 when summarizing a YouTube video but provides no explicit guidance on when to use it over alternatives like gemini_summarize_tool or gemini_youtube_tool. There are no 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.
Behavior2/5
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 disclosing behavior. It only mentions 'multi-step web research,' but does not explain whether the task is asynchronous, how results are retrieved, if there are rate limits or costs, or any side effects. For a deep research tool, this is a significant gap in 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action ('Start a deep research task'), and contains no filler or redundant phrasing. Every sentence adds relevant information.
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?
This is a complex tool that likely involves asynchronous research and has sibling tools for checking status (gemini_check_research_tool) and follow-up (gemini_research_followup_tool). The description does not explain the research lifecycle, how to obtain results, or how it interacts with these siblings. The existence of an output schema is noted but the description is too minimal to fully guide an agent.
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?
The input schema already fully documents the single parameter 'query' with description 'The research question or topic.' The tool description adds minimal extra meaning (e.g., 'complex questions'), but does not provide examples, format constraints, or additional semantic context. With 100% schema coverage, the baseline of 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?
The description clearly states the tool's purpose: 'Start a deep research task using a specialized Gemini model.' It specifies a verb (start), a resource (deep research task), and the method (multi-step web research). This distinguishes it from siblings like gemini_search_tool or gemini_query_tool by emphasizing deep, multi-step research for complex questions.
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 phrase 'answer complex questions' implies usage for complex, multi-step research topics, but it does not explicitly state when to use this tool versus alternatives like gemini_search_tool or gemini_check_research_tool. No exclusions or alternative references are provided. This is implied usage rather than explicit guidance.
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?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states 'List' but doesn't explicitly confirm this is a read-only operation, how 'active' is defined (e.g., not yet ended, currently running, not expired), or whether listing has any side effects. The description adds no behavioral context beyond the literal action.
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 fluff. Every word contributes to meaning and it is appropriately concise for such a simple tool.
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?
For a zero-parameter tool with an output schema, the description is minimal but not fully complete. It leaves 'active' undefined and doesn't explain how sessions are scoped or whether they are cleared after listing. The output schema likely covers return structure, but the lack of context around session lifecycle and usage flow makes this merely adequate.
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 accepts zero parameters, so the input schema is already complete. The description has no parameter details to add, and the baseline for zero-parameter tools is 4. No additional explanation is needed.
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's function: 'List all active image editing sessions.' It uses a specific verb (list) with a distinct resource (image editing sessions) and a qualifier ('active'). This distinguishes it from sibling tools like gemini_start_image_edit_tool and gemini_list_voices_tool.
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 about when to use this tool versus alternatives. It doesn't mention that it could be used to retrieve session IDs before continuing or ending edits, or any workflow context. The description simply states the action without any clues about prerequisites or typical use cases.
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?
No annotations are provided, so the description carries the full burden, and it only says 'Ask a follow-up question.' It does not disclose whether the tool reuses prior research context, performs additional computation, can be called multiple times, or has cost/latency implications.
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 filler or repetition. Every word adds purpose.
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?
The tool is simple and has a full input schema plus an output schema, but the description itself leaves important behavioral context (what 'follow-up' entails and what state is required) to inference. It is minimally viable but not rich enough to be considered fully complete without annotations.
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 both parameters already have descriptions, so the baseline is 3. The description's phrase 'completed research' adds slight context linking research_id to prior research, but it does not meaningfully extend 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?
The description uses a clear verb ('Ask') and names the specific resource ('follow-up question about completed research'), so an agent can tell this is for post-research follow-up rather than a new query. It does not explicitly contrast with sibling tools like gemini_query_tool or gemini_deep_research_tool, but the wording is specific enough to avoid major confusion.
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 frames the correct usage moment: after research is completed, ask a follow-up question. It does not list when not to use it or name alternatives, but for a simple follow-up tool the timing and context are clear.
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?
With no annotations, the description carries the full burden. It discloses that 'Gemini writes and runs Python code', which is a useful detail, but it omits any safety context: no mention of sandboxing, code execution risks, timeouts, or side effects. An agent gets no warning about executing potentially arbitrary code, which is a significant gap for a code execution tool.
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 two sentences, front-loaded with the core action, and contains no filler. Every word adds value, making it highly concise and easy to scan.
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?
The tool has an output schema, so return values are covered. The description is adequate for a simple tool, but could be more complete by noting that code runs in a sandbox, that execution is limited to Python (already implied), and any relevant constraints. It's not incomplete enough to fail, but lacks rich contextual detail.
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% (all three params have descriptions). The description adds minimal extra meaning by linking the 'prompt' (description of code to write) and 'data' (optional data to process) to the stated use cases. This is baseline-appropriate but adds little beyond 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?
The description begins with a specific verb 'Execute' and a clear resource 'code', naming 'Gemini's built-in code execution'. It also lists concrete use cases (answer questions, perform calculations, process data). This clearly distinguishes it from siblings like gemini_analyze_code_tool, which analyzes code rather than executing it.
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 when to use the tool by mentioning 'to answer questions, perform calculations, or process data'. However, it does not explicitly contrast with alternatives (e.g., gemini_query_tool for simple Q&A) or state when not to use it. The guidance is implied but not fully explicit.
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?
No annotations are provided, so the description must carry the behavioral burden. It only says 'Continue editing in an active image session' but does not disclose what happens to the image/session, whether the operation mutates state, what errors could occur, or what the return value represents. This is a minimal non-behavioral statement.
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 short sentence with no filler. It is front-loaded with the action and resource and contains only the necessary information.
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?
This is a simple two-parameter tool with an output schema and clear schema descriptions. The phrase 'active image session' plus the schema's `session_id` reference to gemini_start_image_edit gives sufficient operating context. It does not spell out lifecycle ordering or error handling, but for this small tool the overall context is adequate.
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%, and the schema already defines both parameters clearly: prompt as editing instructions and session_id as the session from gemini_start_image_edit. The narrative description adds no extra parameter semantics, so 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 uses a specific verb ('Continue editing') and a clear resource ('an active image session'), which cleanly distinguishes this tool from its siblings like gemini_start_image_edit or gemini_generate_image. It matches the tool's name and states exactly what action is performed.
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 phrase 'in an active image session' implies the tool should be used only after a session has been started, but the description does not explicitly say when to use this over gemini_start_image_edit or when not to use it. No exclusions or alternative tool names are mentioned.
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 full burden of disclosure. The description states it lists voices, which is a read operation, but doesn't clarify safety profile (e.g., whether it makes network calls, performance characteristics, or response format). With zero annotationsarena, the description could add more behavioral context but doesn't.evetude
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 with zero waste. It front-loads the action (List) and resource (available voices for text-to-speech). Perfectly concise for a zero-parameter read-only list operation.
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 that this is a zero-parameter, read-only list operation with an output schema (which presumably describes the voices returned), a one-sentence description may be sufficient. The output schema provides return value details. The description is complete enough for the tool's simplicity, though mentioning typical use cases (e.g., before calling gemini_speak_tool) could add value. This edges above a minimum viable 3.
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 0 parameters chip with 100% schema description coverage (vacuously true since no properties exist). With no parameters, the schema cannot contribute meaningr temp, so the baseline is 4. The description doesn't need to explain parameters since there are none, and it clearly states the resource being listed.
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 the action (List) and the resource (available voices for text-to-speech). It distinguishes from siblings well since no other sibling tool deals with voice listing. However, it doesn't mention details like whether the output includes voice names, languages, or other attributes, which would enhance purpose clarity.
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 context (when you need to know available TTS voices) but does not explicitly state when to use this vs alternatives or when not to use it. For a simple list tool with no parametersinates, this is adequate but could be improved by noting that it should be called before using gemini_speak_tool with a specified voice.
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?
There are no annotations provided, so the description carries the full burden. It states the grounding mechanism ('with Google Search grounding'), which hints at possible rate limits or real-time behavior, but doesn't disclose specifics like pagination, result count, or whether caching applies. The description adds some context but lacks depth regarding response handling.
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 a single sentence that front-loads the primary action and includes grounding detail. It is concise and structured effectively, with no wasted words. Slightly higher than minimal because it packs relevant information efficiently.
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?
A simple tool with an output schema present, meaning return values don't need description. The description, though brief, likely suffices for a straightforward search tool. However, it might benefit from noting result limits or speed, but given full schema coverage and output schema, completeness is adequate. Slightly lower because the tool's complexity is moderate (it involves web grounding which could have variants).
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% (both parameters have descriptions), so baseline is 3. The description doesn't clarify how 'model' default 'flash' affects behavior or what query formats are accepted, so it adds no extra value. Given the simple schema, a 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?
The description clearly states the tool's purpose: searching the web, using Gemini, with Google Search grounding. This distinguishes it from siblings like gemini_query_tool (which likely queries Gemini without web search) and web-page analysis tools (gemini_analyze_url_tool). The verb 'Search' and resource 'the web' are 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: for web search needs. However, it doesn't explicitly explain when not to use it or which alternative tools to consider for other scenarios-material that could clarify choices among the many related tools.
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?
The description clearly indicates a non-destructive read operation ('analyze and describe'), and 'local' constrains the input location. However, with no annotations provided, the description does not disclose output format, supported image types, model behavior, or potential limitations, leaving much of the behavioral burden unmet.
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 filler or redundancy. Every word adds meaning, and 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward image-analysis tool, the description is minimally sufficient, especially with full schema coverage and an output schema present. It lacks explicit sibling differentiation and behavioral caveats, but these are not severe gaps for such a simple 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 description coverage is 100%, and all three parameters (image_path, model, query) are already described in the input schema. The description adds no parameter-level detail, so it stays at the schema-heavy baseline of 3.
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 action ('Analyze and describe') with a clearly scoped resource ('local image file'). The 'local' qualifier distinguishes it from sibling URL/document/code/text analysis tools.
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 'local image file' wording implies the intended input, but there is no explicit when-to-use or when-not-to-use guidance, nor any mention of alternatives such as gemini_analyze_url_tool or gemini_analyze_document_tool. Usage context is inferable rather than stated.
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 does disclose that resources are freed and the session is ended, which is useful behavioral context. But it omits other important traits such as whether the action is irreversible, whether pending edits are lost, or whether any special permissions are required.
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 filler. Every word contributes: the verb identifies the action, the object identifies the resource, and 'free resources' adds behavioral context.
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?
For a simple one-parameter lifecycle tool with an output schema, the description is mostly complete: it states the action and a key side effect. It could be improved by noting that ending is terminal or that the session cannot be reused afterward, but the current scope is adequate for this complexity level.
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%, and the single parameter's description ('The session ID to end.') already fully communicates its meaning. The tool description adds no further parameter-level detail, so the baseline score of 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?
The description uses a specific verb ('End') with a clear resource ('an image editing session') and adds a meaningful consequence ('free resources'). It clearly distinguishes from sibling tools like start_image_edit, continue_image_edit, and list_image_sessions by marking the terminal lifecycle action.
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?
Usage context is implied by the verb and the session-based sibling tools: an agent would call this after finishing edits. However, the description does not explicitly state when to use it versus alternatives, nor does it mention any preconditions or side effects such as the loss of ability to continue the session.
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?
With no annotations provided, the description carries the full burden of disclosing behavior. It implies a generative/editing operation but does not state side effects (e.g., whether the original file is modified, what output format/URL is returned), limitations, or prerequisites. It mentions that the aspect ratio parameter is 'currently unused,' which is a start, but more transparency is needed for a mutation-type tool.
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, starting with the core action, followed by usage instructions and example use cases in a compact list. Every sentence adds value without redundancy. It is appropriately sized for a tool with two required parameters.
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 that an output schema exists (so return values need not be described) and the parameter schema covers all inputs, the description is largely complete for its scope. It clearly states the input type (local file) and typical modifications. It could note any constraints like file format or size, but that is beyond what most descriptions provide; the current content is adequate.
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 both required parameters, so the baseline is 3. The description does not add extra parameter-level nuance beyond the schema's definitions; it emphasizes general use cases but doesn't elaborate on how to construct the prompt or path requirements. It neither helps nor hinders interpretation, hence the baseline score.
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 purpose: 'Generate/edit an image using a local image file as input.' It explicitly differentiates from sibling tools like gemini_generate_image_tool (no input) and edit-session tools by focusing on a standalone edit with a local file. Use cases (watermarks, style changes, compositing) further clarify its utility.
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 provides clear context on when to use it ('Upload a local image and give Gemini instructions for how to modify it') and lists typical use cases. However, it doesn't explicitly contrast it with alternative image-editing workflows (e.g., session-based editing via start/continue/end tools), so the guidance is good but not exhaustive.
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 behavioral-disclosure burden. It does disclose the async nature via 'Returns an operation ID to poll,' which is useful, but it omits details like expected duration, failure modes, or resource side effects of generating a video.
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 two short, front-loaded sentences with no filler. It packs the core action, the backend name, and the critical async response detail into minimal space.
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 fully described parameters and presence of an output schema, the description is largely complete for an async generation tool. It could name the polling companion tool or mention the long-running nature explicitly, but the current description leaves little ambiguity about what the tool does.
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 all parameters already have meaningful descriptions. The tool description adds no extra parameter nuance beyond indicating the core purpose, which is acceptable but not additive.
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 action ('Generate'), the resource ('a video'), and the technology ('Veo'). It also distinguishes this tool from sibling image/text tools by focusing on video generation and noting the operation-ID response.
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 intended use case is implied through 'Generate a video using Veo,' but the description does not explicitly state when to use this tool vs alternatives or cross-reference the related polling tool. 'Returns an operation ID to poll' hints at the async workflow but gives no direct guidance on next steps.
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?
With no annotations provided, the description carries the full burden. It only mentions model options and pricing but fails to disclose output format, whether generation is synchronous, or any rate limits or auth requirements. This is a significant gap for a mutation-like tool.
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 efficient: two sentences. The first states purpose, the second lists models in a clear bullet-like format. No redundant or excessive text. Front-loaded with the core 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?
The tool is simple, and the schema plus output schema cover return details. The description includes model selection context (prices/speed) which is essential for informed use. However, it doesn't mention interactions with other tools or whether this is part of a session flow, but that's not strictly required for this standalone generation 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?
Schema description coverage is 100%, so the baseline is 3. The description adds meaningful value by sorting models by price and highlighting speed/quality trade-offs, which helps agents choose the right model parameter. Other parameters (aspect_ratio, number_of_images) are adequately covered by schema and need no extra explanation.
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 generates images using Google Imagen 4 models. It lists specific model variants with pricing and speed, which differentiates it from sibling tools like gemini_generate_image_tool. The verb+resource phrasing 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Imagen-based image generation but doesn't explicitly contrast with other image generation tools (e.g., gemini_generate_image_tool) or state when to choose this tool over alternatives. There are no exclusions or prerequisites mentioned, so guidance is only implicit.
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?
There are no annotations, so the description carries the full behavioral disclosure burden. It does state the operation is a read-oriented 'List' and applies an 'active' filter, but it does not explain what 'active' means, whether permissions are needed, or any other behavioral traits.
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 filler or redundant information. Every word contributes to clarifying the tool's behavior.
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?
For a zero-parameter list operation with an output schema present, the description covers the core purpose and the 'active' filter sufficiently. Additional context about cache lifecycle could help, but the simplicity of the tool reduces the need for extensive prose.
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 zero parameters, so the baseline is 4 and the description does not need to add parameter-level detail. The 'active' qualifier describes result scope rather than parameter semantics, which is appropriate for a parameterless tool.
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') with a clear resource ('content caches') and a meaningful qualifier ('active'), making the operation unambiguous. It also distinguishes itself from sibling cache tools such as create, query, and delete caches.
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, and no exclusions or alternative tool names are mentioned. The intended use must be inferred from the tool name and sibling list rather than from the description itself.
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?
No annotations are provided, so the description carries full burden. It explains the basic start behavior but fails to disclose session lifecycle (e.g., that sessions need to be ended with gemini_end_image_edit_tool), or any other side effects like cost, rate limits, or what the return object contains. This is a significant gap.
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 three sentences, directly addresses the purpose, and adds no fluff. It is well-structured and front-loaded with the core action.
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?
While the output schema exists (reducing need to describe return values), the description omits crucial workflow details like ending the session or that the session persists across calls. It does mention the continuation tool, but not the full lifecycle. Given the multi-turn nature, more context would be helpful.
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 schema already covers all parameters (100% coverage). The description adds meaningful context for file_path: 'Without file_path, Gemini generates a new image from the prompt,' which clarifies the conditional behavior. This goes beyond the schema's 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 the tool's purpose: 'Start a multi-turn image editing session.' It also explains the distinction between providing an existing image versus generating from prompt, and explicitly names the continuation tool, distinguishing it from siblings like gemini_generate_image_tool.
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?
It instructs to use gemini_continue_image_edit_tool for further edits, providing an explicit alternative. It also describes when to use without file_path, giving clear usage context for both modes of operation.
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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