Local GPU Imagegen
Server Quality Checklist
Latest release: v0.9.0
- Disambiguation5/5
Each tool has a clearly defined role in the local GPU image generation pipeline, from environment checks to run finalization. The two generation tools (generate_image and generate_round) are distinct, with one serving as a compatibility fallback and the other as part of the core workflow.
Naming Consistency5/5All tools follow a strict 'local_gpu_<verb>_<noun>' convention using snake_case. The pattern is uniform and predictable, making it easy to deduce tool behavior from the name alone.
Tool Count4/5At 17 tools, the set is slightly above the typical 3-15 range, but the complexity of the domain (workflow inspection, trust management, run lifecycle, and mask handling) justifies the count. Each tool serves a distinct purpose, so the overhead is acceptable.
Completeness4/5The toolset provides end-to-end coverage for managing local GPU image generation runs, including setup, registration, recommendation, execution, review, and cleanup. Minor gaps exist, such as no explicit list-runs tool and no update operation for run fields, but these are not critical given the immutable nature of runs.
Average 3.2/5 across 17 of 17 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 274 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository is licensed under MIT License.
This repository includes a README.md file.
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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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only mentions that model weights are not loaded and that discovery is bounded. It does not explain side effects, phases, authorization requirements, confirmation flows, or network behavior even though schema parameters hint at these. The description adds some value but is far from transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that avoids redundancy and directly conveys the core action. However, it is under-specified for the tool's complexity, but that is more a completeness issue than a structural problem. It earns its place without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 12 parameters, multiple phases, stages, and confirmation/authorization fields, the description is inadequate. It omits the meaning of 'plan' vs 'execute', the discovery stages (index/fingerprint/verify/revoke), and the scope modes. Even though an output schema exists, the description does not provide enough context to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% with 12 parameters, and the description does not explain any of them. The phrase 'bounded' and 'without loading model weights' gives general context but no specific parameter meanings. The description fails to compensate for the complete lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: planning or executing bounded local model discovery without loading model weights. The verb 'plan or execute' combined with the resource 'local model discovery' is specific, and the qualifier 'without loading model weights' adds a distinctive safety constraint. However, it does not explicitly differentiate from sibling tools like local_gpu_recommend_models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for model discovery when avoiding weight loading is desired, but it lacks explicit when-to-use or when-not-to-use guidance and does not mention alternatives. There are no prerequisites or exclusions stated, leaving the decision to the agent without additional context.
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 discloses that the result is an optional bounded JPEG preview and that rounds are 'root or immutable revision', but it doesn't explain side effects, GPU usage, idempotency behavior, or state changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the verb and object. It contains no filler, but it's so terse that it sacrifices essential context. Still, for what it includes, it's well structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 params, 7 required, enums, nested objects) and lack of annotations or parameter descriptions, the description is too thin to allow an agent to use it correctly. The existence of an output schema helps with return values but not with usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 8 parameters with 0% description coverage, and the tool description does not explain any of them (run_id, idempotency_key, action, edit_mode, plan, seed, change_summary). It only references 'round' and 'preview' without mapping to parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('generate') and resource ('one root or immutable revision round') and mentions a return value ('optional bounded JPEG preview'). It distinguishes from sibling 'local_gpu_generate_image' by focusing on 'round' rather than a single image, but the concept of 'round' is not defined, so it lacks clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 local_gpu_generate_image or local_gpu_branch_run. The description does not mention scenarios (initial vs refine vs explore) or why a 'round' is 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 provided, the description carries the full burden of behavioral disclosure. It states that the tool confirms a mask but does not explain what confirmation entails—whether it validates, records, updates state, or rejects changed masks—nor does it describe side effects, failures, or output. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant wording. It efficiently conveys the core action and condition, earning every word's place without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's role in a workflow with siblings like local_gpu_prepare_mask and local_gpu_generate_round, the description lacks contextual completeness. It does not explain how this confirmation step fits into the overall process, what happens if the mask is not unchanged, or what the output represents. The presence of an output schema does not compensate for the missing workflow and behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about run_id or mask_id. The phrase 'prepared mask' hints at mask_id but does not clarify relationships, expected values, or how the parameters interact, leaving the agent without adequate parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action (confirm), the object (an unchanged prepared mask), and the condition (after explicit overlay approval). It distinguishes this tool from siblings like local_gpu_prepare_mask and local_gpu_record_review by indicating a post-approval validation step, though it could be more explicit about the tool's unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage guidance is only implied through the phrase 'after explicit overlay approval,' which suggests a sequencing condition but does not explicitly state when to use this tool versus alternatives. No exclusions or alternative tools are mentioned, leaving the agent without clear decision-making criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states the tool 'prepare[s]' a mask, implying a state change, but does not clarify whether this modifies the run, is reversible, or requires special permissions. The return of a JPEG overlay is mentioned, but side effects, rate limits, and whether the operation is read-only or destructive are not addressed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the core purpose. It is efficient and easy to parse. However, it is so brief that it omits essential details, but that is more a completeness issue than a structure one. For what it does contain, it is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no annotations, and no output schema details in the description, the single-sentence description is insufficient. It does not explain what a 'child-run' is, how the mask is generated, what the JPEG overlay represents, or how the parameters interact. An agent would likely struggle to invoke this tool correctly without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description itself does not mention any parameters. It does not explain the role of run_id, geometry, feather_pixels, or user_mask_path, nor how they influence the prepared mask. This leaves the agent without semantic understanding of how to populate the parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Prepare an unconfirmed child-run inpaint mask and return its JPEG overlay.' It uses a specific verb ('prepare'), identifies the resource ('child-run inpaint mask'), and specifies the output ('JPEG overlay'). The term 'unconfirmed' differentiates it from the sibling tool 'confirm_mask', making its role in the workflow clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool, what prerequisites are needed, or how it relates to alternatives. It does not mention that it should be used before 'confirm_mask' or under what circumstances. The context is entirely implicit, offering no contextual cues about workflow placement.
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 discloses one behavioral trait ('immutable') but omits side effects, permissions, or how the child run relates to the workflow. For a creation tool, this is insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it is under-specified for a tool with six parameters. Conciseness should not come at the expense of necessary details; this is too terse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, nested contract, output schema, 16 siblings), a one-sentence description is completely inadequate. It lacks context on the run lifecycle, the meaning of contract fields, and when to start a child versus other run operations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage and the description adds no parameter meaning. It only implies 'parent_round' through 'reviewed parent round,' but the complex contract, edit_mode, and denoising_strength are unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and the resource ('immutable child revision run'), and it distinguishes this from sibling tools like local_gpu_start_run and local_gpu_generate_round by specifying it is a child of a reviewed parent round.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'from one reviewed parent round' provides clear context and a prerequisite, but it does not explicitly name alternatives or state when not to use. Still, it gives enough directional 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?
With no annotations, the description carries full responsibility for behavioral disclosure. It mentions removal but does not warn that this is destructive and irreversible, nor does it explain the role of the 'confirmation' parameter. The phrase 'fully confirmed' is vague and lacks details about confirmation requirements or consequences for unconfirmed runs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the key verb and resource. It is not bloated, though it could add a bit more context without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, return values need not be described. However, the tool is destructive with three required parameters and no annotations. The description omits critical context about when cleanup is appropriate, how confirmation works, and what data is affected, making it incomplete for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It partially explains the 'scope' parameter by mentioning 'intermediates' vs 'fully confirmed run directory', but gives no insight into 'run_id' or 'confirmation'. The required confirmation parameter is not addressed at all.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Remove') and resource ('run intermediates or a fully confirmed run directory'). It distinguishes from sibling tools by focusing on cleanup/removal, which is unique among the listed operations like generate, start, or inspect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, scenarios for cleaning intermediates vs full directories, or contrast with any sibling. The reader must infer usage from the name and basic purpose.
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 burden for behavioral disclosure. It only says 'record' without detailing side effects, persistence behavior, requirements (e.g., round must exist), or how the evidence is stored.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no fluff. However, given the tool's 10 parameters and nested structure, one sentence may be too terse to be truly helpful, but it earns high marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description is inadequate for a tool with this complexity. It fails to explain key concepts like stage_checks vs visual_checks, the meaning of next_action, or the relationship to generated rounds.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no parameter-level meaning. It does not mention any of the 10 parameters (run_id, round_number, scores, etc.) or explain their roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('record') and resource ('review evidence for one generated round'), clearly distinguishing this tool from siblings like local_gpu_generate_round or local_gpu_finalize_run.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a usage context (recording evidence after a generation round) but does not explicitly state when to use this vs alternatives like get_run or generate_round. No exclusions or when-not guidance provided.
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, the description carries the full burden of behavioral disclosure. 'Get the current persisted state' implies a read-only operation with no side effects, which is appropriate. However, it does not disclose error behavior, whether the state is always available, or whether any special conditions apply (e.g., whether the run must be finalized). For a simple getter, this is acceptable but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately conveys the tool's purpose. There is no redundant information, and the phrasing is direct and front-loaded with the verb.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one parameter) and the existence of an output schema (which presumably documents return values), a short description is somewhat acceptable. However, the absence of usage guidance relative to sibling tools and the lack of behavioral details (e.g., error handling) make it only minimally complete for a tool in a larger workflow context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, run_id, is documented in the schema as a required string with minLength 1, but the schema description coverage is 0% and the description adds no additional meaning. The tool name and context hint that run_id identifies a run, but there is no guidance on where to obtain it, its format, or potential constraints. The description does not compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb 'Get' and specifies the resource as 'the current persisted state of a visual-asset run.' This distinguishes it from sibling tools that start runs (local_gpu_start_run), generate images (local_gpu_generate_image), or inspect workflows (local_gpu_inspect_workflow). It could be slightly more explicit about how it differs from other 'get' or inspection tools, but it is adequately specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 such as local_gpu_inspect_workflow or local_gpu_list_profiles. It does not state exclusion criteria or mention any prerequisites. Users are left to infer the appropriate context from the tool's name and brief purpose.
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 discloses a critical behavioral requirement: trust mutations require a previously returned confirmation to be displayed to the user and repeated later. With no annotations provided, this adds important context. However, it does not explain side effects, destructive potential of revoke, or other operational details expected for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loaded with the primary purpose. It avoids unnecessary filler but is so brief that it sacrifices completeness for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 params, nested objects, output schema, multiple action enums), the description is too sparse. It does not explain the 'action' values, identity_token purpose, workflow binding fields, or the confirmation workflow beyond a single sentence. The output schema may cover return values, but the description leaves many usage gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter-related mention is the 'exact confirmation previously returned' which maps to the 'confirmation' field. With 13 parameters and 0% schema coverage, the description fails to explain identity_token, action enum values, nested objects, or other critical parameters, leaving the agent under-informed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action clearly ('Inspect, approve, or revoke one exact current local model identity') with a specific resource. It distinguishes the tool from sibling tools by focusing on trust operations. However, the phrase 'mutation boundary' is jargon and not explained.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for trust inspection/approval/revocation, but does not explicitly state when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or alternative tools for related tasks like model discovery.
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 must carry the full burden of behavioral disclosure. It states the core action (publish) but gives no information about side effects, such as whether it overwrites an existing final PNG, whether the action is irreversible, or what happens to previous rounds. It also does not explain the confirmation parameter, which appears to be a safety mechanism. This is a significant transparency gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, grammatically correct sentence that front-loads the primary action and outcome. It earns its place with no filler words. However, it is so terse that it sacrifices necessary detail, making it only slightly less than ideal in structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, a nested object with enums, and a required confirmation string) and the presence of an output schema (which is not shown but implies return values), the description provides no context about the workflow step, prerequisites, or consequences. It does not explain what 'publish' does operationally, how confirmation is used, or what happens to previous rounds. This is a finalization action that would benefit from explicit state-change semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the five parameters (run_id, round_number, summary, confirmation, postprocess). The description only implies run_id (the run) and round_number (the reviewed round), but says nothing about summary, confirmation, or the postprocess object. This provides minimal value beyond the schema and leaves most parameters unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Publish') and resource ('selected reviewed round' as 'run's final PNG'). It clearly distinguishes from sibling tools like local_gpu_record_review (which records the review) and local_gpu_generate_round (which generates a round). The purpose is unambiguous without needing the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'selected reviewed round' implies that it should be used after a round has been reviewed, but the description does not explicitly state when to use it versus alternatives or any preconditions. It does not mention that it is the final step in a run, nor does it exclude using it before review. This is merely implied context, not 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?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only describes the tool as a compatibility layer, offering no information about how invocation behaves, side effects, blocking semantics, resource usage, or error handling. This is a significant gap for a tool with 25 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the core purpose and immediately followed by exclusionary boundaries. Every word earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 25 parameters, multiple enums, an output schema, and no annotations, this description is severely incomplete. It does not cover parameter selection, backend behavior, prerequisites, or relationship to sibling tools beyond the bare exclusions. The output schema exists but the description fails to provide the contextual glue needed for correct tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides zero information about any of the 25 parameters. It does not explain which parameters are relevant for WebUI vs. Diffusers backends, how modes like txt2img/img2img/inpaint interplay, or what required versus optional parameters mean. The description adds no semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is a compatibility layer for WebUI or Diffusers image generation, which aligns with its name. It explicitly distinguishes itself from ComfyUI routes and the high-level run workflow, making its purpose and scope unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-not-to-use guidance: not for ComfyUI and never as a bypass for the confirmed high-level run workflow. However, it does not name specific alternative tools, such as local_gpu_generate_round, so the guidance is clear but not fully explicit about 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?
No annotations are provided, so the description must disclose behaviors. It only states the action without confirming read-only status, permissions, or side effects. The optional 'authorization_scope' parameter is not explained, and 'capabilities' is undefined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no redundant words. It front-loads the action and resource, making it easy to parse while conveying the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values are covered. However, the description omits any explanation of the authorization_scope parameter and provides no usage context (e.g., when to use vs. siblings). These gaps make it only minimally viable for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one optional enum parameter 'authorization_scope' with 0% schema description coverage. The description does not mention it, leaving its meaning and effect on the returned profiles completely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' with clear resources: 'registered visual-asset profiles' and 'current local backend capabilities.' This distinguishes it from sibling tools like local_gpu_generate_image or local_gpu_discover_models, which focus on generation or model discovery.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a discovery/inventory use case but provides no explicit when-to-use guidance or alternatives. It names no exclusions or conditions for choosing this over sibling tools, leaving the context 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?
With no annotations, the description carries the burden. It discloses the prerequisite of a previous recommendation and the exact-copy requirement, adding some behavioral context. However, it omits side effects, authorization needs, or what 'start_run_boundary' means, and whether the run starts a background process.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the main verb and key constraint. It avoids fluff, though phrases like 'remaining run fields' are vague. Overall, it is concise and structured enough for a short tool description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is complex (13 parameters, nested objects, enums, no parameter descriptions) but the description gives almost no guidance on how to fill parameters or what workflow precedes this call. The mismatch between 'start_run_boundary' and the actual schema further reduces completeness, leaving the description inadequate for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only references 'start_run_boundary', which is not a property in the schema (and additionalProperties is false). It vaguely says 'add the remaining run fields' without explaining any of the 13 parameters or nested objects, providing minimal semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('Create a visual-asset run') and adds a key constraint ('only after later user confirmation'), distinguishing it from sibling tools that generate images or finalize runs. It is specific about the resource and action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives explicit timing guidance ('only after later user confirmation') and instructs to copy 'start_run_boundary exactly' from a prior recommendation, which helps when to use it. It does not explicitly name alternative tools or exclusion cases, so it's one step below full guidance.
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. It does disclose key behaviors: it recommends one confirmed route plus alternatives, requires exact catalog IDs, displays the selected route and start_run_boundary, and defers execution until user confirmation. However, it leaves open what 'confirmed-capability' means, whether any state is mutated, and what happens on failure or multiple matches.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, starts with the primary action, and includes critical constraints without any fluff. Every clause adds useful information, and the structure is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description is incomplete for a tool with 11 parameters, 9 of which are required, and no annotations. It introduces undefined terms like 'start_run_boundary' and 'confirmed-capability route' without explaining them, and it gives no guidance on how to fill the required parameters or what the recommendation workflow should look like beyond the confirmation step.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 11 parameters with 0% description coverage, so the description must compensate. It only adds meaning for preferred_model_id ('must be an exact catalog ID'), while the other 10 parameters, including required ones like operation, profile, width, height, and authorization_scope, remain unexplained by the description. This is insufficient for a tool with many required parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: recommend one exact confirmed-capability route with up to two alternatives. It uses an action verb ('recommend') and references the resource (model routes), and it distinguishes itself from sibling local_gpu_start_run by explicitly saying it waits for later confirmation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use this tool: before starting a run, and it explicitly says to wait for user confirmation before calling local_gpu_start_run. However, it does not mention when to prefer sibling tools like local_gpu_discover_models or local_gpu_inspect_workflow, so it lacks full alternative differentiation.
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, the description carries full burden. It discloses 'immutably' to indicate irreversibility, and 'recheck' implies verification, but it omits details about what confirmation entails, possible side effects, or error behavior. This is adequate but has clear gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly worded sentence with no filler. It front-loads the action ('Recheck and immutably register') and immediately specifies the resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists to cover return values, the description leaves many questions unanswered: the exact sequence relative to other tools, the meaning of 'confirmation', what 'recheck' involves, and the implications of immutability. For a tool with no annotations and 0% parameter coverage, it is under-specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for missing parameter meanings. It does not explicitly explain any of the three parameters. The phrase 'previously inspected workflow proposal' vaguely hints at proposal_digest, and 'register' could relate to confirmation, but no direct mapping is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('recheck and immutably register') and the specific resource ('one exact previously inspected ComfyUI workflow proposal'). It differentiates from sibling tools by emphasizing 'previously inspected', which implies it must follow inspect_workflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'previously inspected' provides a clear precondition, indicating this tool is used after an inspection step. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It explicitly states 'without writing state,' which is a key non-mutating guarantee. However, it does not elaborate on what 'infer a safe ordinary' entails or any potential 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence of 14 words, front-loaded with the action and side-effect guarantee. Every word contributes value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description covers the essential purpose and non-mutating behavior. The vague phrase 'safe ordinary txt2img binding' leaves some ambiguity, but it is sufficient for a low-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description relates workflow_path to 'one local ComfyUI API workflow,' adding meaning beyond the bare parameter name in the schema. Yet it lacks detail about the expected path format, file type, or validity requirements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: inspecting a local ComfyUI API workflow and inferring a safe txt2img binding. The verb 'Inspect' and specific resource distinguish it from siblings like generation or registration tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 such as local_gpu_register_workflow or local_gpu_generate_image. It does not mention any context, exclusions, or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. The verb 'Check' implies a read-only diagnostic, which is a minimal behavioral signal, but the description does not explicitly state whether it modifies anything, whether packages are installed, or how it reports failure. This is adequate but leaves ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence front-loaded with the action verb, no filler or redundancy. It is concise and well-structured, with every word contributing to the meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter diagnostic with an output schema, the description states the core subject matter but omits when to run it and what the results imply for subsequent generation steps. It is minimally complete for a simple check tool but lacks fuller context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so schema coverage is 100% trivially. For a zero-parameter tool, the baseline is 4; the description adds value by clarifying what the check covers (Python packages, CUDA readiness), even though no parameters need documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Check' and names concrete resources: Python packages and CUDA readiness for local GPU image generation. Among sibling tools (generate, discover, inspect, register, etc.), no other tool is a preflight environment check, so it is clearly differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but 'for local GPU image generation' implies it is a prerequisite readiness check before generation. No exclusions or alternative tools are mentioned, providing only implied usage guidance.
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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