AlbumentationsX MCP

by dKosarevsky

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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Latest release: v1.21.0
Disambiguation2/5
Many tools have overlapping purposes, such as render_preview vs run_first_preview, recommend_recipe vs recommend_pipeline, and plan_augmentation_policy vs plan_augmentation_policy_candidates. While descriptions help, the boundaries between several tools are unclear, leading to potential misselection.
Naming Consistency4/5
All tool names follow a consistent snake_case verb_noun pattern, which is a solid structure. However, the variety of verbs for similar actions (e.g., render vs run, recommend vs plan) and some compound names introduce minor inconsistencies in predictability.
Tool Count2/5
With 47 tools, the server exceeds the 'too many' threshold (25+). The scope could be covered by a smaller, more focused set of tools, and the excessive count suggests over-engineering.
Completeness4/5
The tool surface covers the full workflow: pipeline recommendation, validation, export, preview rendering, feedback collection, tuning sessions, decisions, and environment diagnostics. No obvious gaps exist, though the redundancy in tools masks some minor missing operations like direct update/delete for certain entities.
Average 2.8/5 across 47 of 47 tools scored. Lowest: 2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 531 commits in the last 12 weeks
- Last stable release on August 14, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 fully disclose behavior. It only says 'plan', which is vague and does not clarify if the tool is a read or write operation, what side effects occur, or what the result means. This is insufficient for an agent to understand the tool's impact.
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 single sentence is concise but at the expense of critical information. It fails to front-load key details and wastes the opportunity to add value beyond the name.
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?
For a tool with 6 parameters and no param descriptions, the description is severely incomplete. It does not integrate the output schema (though present) or provide enough context for correct invocation, especially given the complex sibling landscape.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain any of the 6 parameters (e.g., 'accepted', 'feedback_note', 'quality_profile'), leaving the agent without clues about their meaning or required format.
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 verb 'Plan' and a resource 'baseline-to-candidate preview comparison', giving a basic sense of purpose. However, it does not specify what 'planning' entails (e.g., suggesting acceptance, capturing feedback) and fails to differentiate from sibling tools like 'record_preview_feedback' or 'compare_preview_runs', leaving ambiguity.
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 (e.g., when to plan versus record feedback). The description lacks context for appropriate usage, exclusions, or prerequisites.
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 present, and the description only states the action without disclosing side effects, permissions, or return behavior. It does not clarify whether the tool is read-only or if it modifies state.
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 extremely concise (one sentence) but critically under-specified. It lacks essential details like what 'rank' means or what the tool returns, making it insufficient for correct invocation.
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 complexity (5 parameters, 1 enum, no schema descriptions, and sibling tools), the description is profoundly incomplete. It fails to explain how ranking works, what output to expect (despite an output schema existing), or how parameters like feedback_tags_by_candidate influence the ranking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does 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 any of the five parameters (e.g., baseline_run_id, candidate_run_ids, feedback_tags_by_candidate, accepted_candidate_ids, quality_profile). The agent cannot infer the meaning or required formats.
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 'Rank multiple candidate preview runs against one baseline' clearly states the action and resources, but 'rank' is ambiguous and does not differentiate from sibling tools like 'compare_preview_runs' or 'score_dataset_preview_candidates'.
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 such as compare_preview_runs. The description lacks context on prerequisites or 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?
The description implies mutation but does not disclose side effects, such as whether the session is final or can be reopened. With no annotations, the description fails to provide sufficient 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short but under-specified. Conciseness is not valuable when essential information is omitted.
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?
For a tool with 4 parameters, 2 required, and no schema descriptions, the description is far too minimal. It does not cover parameter roles, output, or behavioral nuances.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about parameters. It does not explain the purpose of session_id, status, accepted_candidate_run_id, or note.
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 (close) and the resource (interactive tuning session) with specific outcomes (accepted or rejected). It is somewhat distinguishable from siblings like archive_tuning_session, but could be more explicit.
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 like archive_tuning_session. No preconditions or context provided.
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 must disclose behavioral traits but only says it recommends a pipeline. It does not mention whether it is read-only, requires special permissions, or what the output format is. The output schema exists but is not referenced.
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, but it is too brief and lacks important details. It earns its place but could be expanded without becoming verbose.
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 3 parameters (1 required) and an output schema, the description omits input semantics and return value. It is insufficient for an agent to correctly invoke the tool without additional schema inspection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters (task, intensity, targets). Even though 'task' is implied by 'CV task', no details are given about the enum values of intensity or the optional targets.
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 recommends a conservative starter pipeline for a CV task. The verb 'recommend' and the resource 'pipeline' are specific. However, it does not differentiate from sibling tools like adjust_pipeline or explain_pipeline.
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 alternatives. No context on prerequisites, when not to use, or how it compares to siblings.
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 action but does not mention side effects, authorization requirements, rate limits, or any constraints. The agent cannot assess whether invoking this tool is safe or appropriate.
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, but it sacrifices clarity and completeness. It front-loads the core action but misses crucial details, making it minimally useful.
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 5 parameters, no parameter descriptions, an output schema (unseen), and a large sibling set, the single-sentence description is far from complete. It fails to address parameter usage, output expectations, or when to invoke this tool over alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 5 parameters with 0% description coverage, and the tool description does not explain any parameter meaning, defaults, or usage. Parameters like 'targets', 'intensity', and 'max_images' are left entirely unexplained.
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 specifies a concrete action ('Build one host-facing first-preview handoff') and the scope ('for one image or an image directory'). It distinguishes from sibling tools like 'render_preview' or 'plan_preview_review' by focusing on the handoff context, though the term 'handoff' may be slightly ambiguous.
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 many sibling tools (e.g., 'render_preview', 'plan_preview_review'). An agent would have no basis to choose this over alternatives 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 must carry the full burden. It only states the action (compare) and broad purpose, but does not disclose whether the operation is read-only, destructive, or requires specific permissions, nor does it describe what the output represents beyond 'comparison'.
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 extremely concise (one sentence, 7 words), but this brevity comes at the cost of important details. For a tool with 3 parameters and an output schema, the description is underspecified and does not earn its place—it should provide more 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?
Given the complexity of comparing manifests (with optional quality profiles) and the existence of many sibling tools, the description is too minimal. It does not cover prerequisites, error conditions, or the nature of the comparison result, even though an output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and no parameter explanations in the description, the agent receives no added meaning beyond the parameter names. The meaning of 'baseline_run_id', 'candidate_run_id', and especially 'quality_profile' (with its enum values) remains entirely opaque.
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 compares two preview manifests, and the purpose 'to guide structured feedback and reproducible tuning' adds context. However, it does not explicitly differentiate from sibling tools like get_preview_manifest or rank_preview_candidates, leaving room for ambiguity.
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 (e.g., when to compare vs using get_preview_manifest or rank_preview_candidates). The description lacks any contextual usage advice.
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 present, so the description carries full burden. It discloses the diagnostic areas but does not state whether the tool is read-only, destructive, or requires special permissions. The behavioral implications of 'diagnose' (e.g., side effects, rate limits) are left unclear.
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 that covers multiple points, but it is somewhat dense and lacks structure (e.g., bullet points or clear separation of concerns). It could be more readable.
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 an output schema, the description fails to cover the input parameter or differentiate from related tools. Given the tool's apparent complexity (multiple diagnostic areas), more context is needed for the agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description completely ignores the only parameter 'include_write_probe'. The parameter's purpose and effect are entirely undocumented, leaving the agent without guidance on how to use it.
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 purpose: to diagnose local MCP setup, root access, artifact writes, and public surface discovery. It uses a specific verb ('diagnose') and lists distinct areas, distinguishing it from the many pipeline- and preview-focused sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool instead of alternatives. There is a sibling tool 'run_host_smoke_check' that may overlap but no explicit differentiation or usage context is provided.
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 provided, and the description does not disclose side effects, whether it creates files, requires permissions, or is read-only. The word 'export' implies generating a file, but details are missing.
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?
Single sentence is too minimal given the tool's complexity. While not verbose, it lacks necessary detail; front-loading is absent as the entire description is one line. The length is not justified by the content provided.
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?
Output schema exists but description does not explain return format or how results are delivered. No context on when to use among 30+ sibling tools, nor what constitutes a valid baseline/candidate run ID.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 7 parameters with 0% coverage in description. The description does not mention any parameters, defaults, or how they affect the output (e.g., 'baseline_run_id' and 'candidate_run_ids' are required but not described).
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 (export), the resource (visual preview report), and specific contents (ranking, contact sheets, decisions). However, it does not differentiate it from sibling tools like 'export_pipeline' or 'export_tuning_report' which have similar names and 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 on when to use this tool over siblings. For example, when to export a preview report vs. a tuning report or pipeline export is not mentioned. Also lacks prerequisites or context for usage.
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 fails to disclose ordering, pagination, default behavior for limit, or whether the operation is read-only. Only states 'recent preview runs' without clarifying recency criteria.
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 clear sentence (9 words), but it sacrifices necessary information for brevity. For a simple list tool, this is minimally adequate but could be expanded slightly without losing conciseness.
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 output schema exists (though not shown), the description might be partially complemented, but it still lacks essential context like sorting, filtering scope, or relationship to other preview tools. The single parameter and lack of details make it incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the 'limit' parameter beyond its name. The schema provides a default but no semantic meaning, leaving agents uninformed about its effect (e.g., max records, pagination).
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 resource ('preview runs'), with qualifiers 'recent' and 'under the configured artifact root'. It distinguishes from sibling tools like 'render_preview' which likely produce a visualization, though no explicit differentiation is given.
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 (e.g., 'get_preview_manifest' for manifest details, 'render_preview' for rendering). The description does not mention contexts, prerequisites, 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?
With no annotations, the description must fully disclose behavior. It only states that the tool 'plans' a policy, omitting whether it is read-only or mutating, what side effects exist, or what happens to existing policies. The term 'preview-gated' is not explained, leaving 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but too brief. It front-loads the main purpose but sacrifices necessary detail, failing to provide adequate context.
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, the description does not explain return values. With 0% parameter coverage, no behavioral transparency, and no usage guidance, the description is severely incomplete for a tool with five parameters and multiple sibling alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only mentions two parameters (task and objective) while there are five parameters total (task, targets, intensity, objective, feedback_tags). The description adds no meaning to the undocumented parameters.
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 plans an augmentation policy for a task and objective. However, it does not differentiate from sibling tools like plan_augmentation_policy_candidates or plan_policy_iteration, and the term 'preview-gated' is unexplained jargon.
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 such as plan_augmentation_policy_candidates or plan_policy_iteration. There is no context on prerequisites or typical usage scenarios.
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, and the description does not disclose behavioral traits such as idempotency, required permissions, or side effects. It omits what 'planning' entails and what happens during execution.
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. However, it is so brief that it sacrifices necessary detail; it is under-specified rather than efficiently informative.
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 5 parameters, no descriptions, no annotations, and a non-trivial output schema (not shown), the description is severely incomplete. It does not explain what the plan generates, how images are selected, or what constraints exist.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate but fails. Only dataset_path is implied via 'local image or an image directory'; the remaining four parameters (task, targets, intensity, max_images) are completely unexplained.
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 specifies a clear action ('plan the first safe preview') and resource ('one local image or an image directory'). Although the verb 'plan' is abstract, it distinguishes from sibling tools focused on policies or reviews.
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 like plan_augmentation_policy or plan_preview_review. The phrase 'first safe preview' hints at initial exploration but does not explicitly state exclusivity or conditions.
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?
No annotations provided. The description fails to disclose any behavioral traits such as side effects, idempotency, permissions, or what happens on invalid inputs. It only states the purpose without 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no waste, clearly stating the core purpose. However, it is under-specified for a tool with multiple parameters and no schema descriptions, making it too concise.
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 and 3 parameters with no descriptions, the description provides no details on return values, usage scenarios, or mapping to sibling tools. The tool is one of 32 siblings, yet no context is given for selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
0% schema description coverage. The tool description does not explain any of the three parameters ('task', 'intensity', 'targets'). 'task' is only mentioned implicitly, and 'intensity' enum values are unexplained. No value added beyond the schema structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Recommend' and the specific resources: 'starter pipeline, quality profile, and preview workflow'. It distinguishes from sibling 'recommend_pipeline' by including quality profile and preview workflow.
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 like 'recommend_pipeline' or others. No context for prerequisites 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 must fully disclose behavior. It only says 'persist,' implying a write operation, but omits details like idempotency, side effects, authentication requirements, or return value structure. The output schema exists but is not mentioned.
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 (one short sentence), but its brevity sacrifices usefulness. It could be structured with key details like parameter roles or usage notes without becoming verbose.
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 complexity of 6 parameters, many sibling tools, and an existing output schema, the description is incomplete. It does not explain what the tool returns, how it integrates with other tools, or what constitutes a valid tuning decision.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (no descriptions in the input schema), and the tool description adds no explanation of the 6 parameters, including the 2 required ones (baseline_run_id, candidate_run_id). The agent has no semantic help beyond property names.
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 verb 'persist' and the resource 'a local tuning decision for one preview comparison,' distinguishing it from sibling tools like 'compare_preview_runs' or 'record_preview_feedback.' However, it lacks specificity about what a 'tuning decision' entails.
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. With many related siblings (e.g., compare_preview_runs, record_preview_feedback, record_tuning_session_step), the description should indicate prerequisites or typical workflow position.
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 fails to disclose behavioral traits such as side effects, mutability, or dependencies. It only states the action without any context on consequences 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, but it sacrifices valuable information. It could be slightly expanded to include parameter context or usage tips without becoming verbose.
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 complexity (7 parameters, 3 required) and lack of parameter documentation, the description is incomplete. Although an output schema exists, the description does not help the agent understand when and how to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation for the 7 parameters. The agent must infer meaning from parameter names alone, which is insufficient for correct usage.
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 verb 'record' and resource 'candidate comparison' within a specific context 'inside an interactive tuning session', which distinguishes it from sibling tools like 'record_tuning_decision' or 'record_preview_feedback'. However, it does not explicitly differentiate from similar recording tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, or when not to use it. The description implies existence of an interactive tuning session but does not explain prerequisites or required prior actions.
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 adds the behavioral trait 'deterministic', which implies idempotency and predictability. However, with no annotations provided, there is no disclosure of side effects, permissions, or whether artifacts are stored/cached.
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 single sentence is concise but lacks necessary detail. It does not fully leverage the space to explain parameter structure or output, making it under-specified rather than efficiently compact.
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?
With a complex nested input schema and no explanation of the request structure, the description is incomplete. The agent cannot determine required properties or format, rendering the tool difficult to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not elaborate on the 'request' parameter. It mentions 'local input images' but does not specify how to structure the request object, leaving the agent without sufficient guidance.
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 verb 'render' and resource 'preview artifacts', with qualifiers 'deterministic' and 'for local input images'. This distinguishes it from sibling tools like export_pipeline or explain_pipeline, but does not elaborate on what preview artifacts are.
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 like get_preview_manifest or list_preview_runs. The description does not mention conditions 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 must disclose behavioral traits. It only states it operates as a 'dataset-level decision set' but does not mention side effects, required permissions, or whether it records data. The agent gains minimal understanding of the tool's impact beyond its primary action.
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, which is concise, but it sacrifices clarity and completeness. It contains no wasted words, but the brevity undermines its utility. A more structured description could provide the same conciseness with added value.
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 complexity (5 parameters, many sibling tools, no annotations), the description is inadequate. It fails to explain input semantics, output structure, or behavioral context. An output schema exists but is not leveraged in the description. The description is too sparse to support correct agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no parameter explanations. Of the 5 parameters (baseline_run_id, candidate_run_ids, feedback_tags_by_candidate, accepted_candidate_ids, quality_profile), only 'candidate_run_ids' is vaguely implied. The enum for quality_profile and optional parameters for feedback and acceptance are completely unaddressed.
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?
Description states 'Score several preview candidates as one dataset-level decision set', clearly indicating a batch scoring operation on preview candidates. It distinguishes from sibling tools like 'rank_preview_candidates' by emphasizing the dataset-level decision aspect, but the verb 'score' is somewhat ambiguous without further 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 on when to use this tool versus alternatives such as 'compare_preview_runs' or 'record_preview_feedback'. The description does not specify prerequisites, typical workflows, or exclusions, leaving the agent to infer usage context from the name alone.
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 provided, so description carries full burden. It simply says 'search' without disclosing behaviors such as read-only nature, pagination, authentication requirements, or what happens on no results. Very minimal transparency.
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?
Single sentence is concise and front-loaded, but it is too brief to be sufficiently informative. Conciseness is achieved at the expense of utility.
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 an output schema, the description lacks context about what the search returns, how results are ordered, or how it integrates with other pipeline tools. For a tool with 5 parameters, the description is too sparse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and description adds no meaning to any of the 5 parameters. Parameters like 'query', 'targets', 'transform_type' are left completely unexplained.
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?
Description states verb 'Search' and resource 'AlbumentationsX transform metadata', which is clear. However, it does not distinguish from sibling tools like 'get_transform_schema' or 'list_feedback_tags' that also deal with transform-related information.
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. No prerequisites, use cases, or exclusions 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?
No annotations are provided, so the description bears full responsibility. It mentions 'persistent multi-step preview tuning session' but does not disclose side effects, required permissions, or lifecycle implications. The behavioral traits are insufficiently described.
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 unnecessary words, but it is too terse to convey required information. It lacks structure and fails to provide value beyond the tool name.
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 four parameters (one required), an enum, and an output schema, the description provides no information about the output, session management, or how parameters relate to the tool's purpose. It is severely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention or explain any of the four parameters (task, targets, baseline_run_id, quality_profile). The agent must rely solely on parameter names, which are insufficient for correct invocation.
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 specific verb 'start' and resource 'tuning session', and the modifier 'persistent multi-step preview' helps distinguish it from other tools. However, it does not elaborate on what the session entails, leaving some ambiguity.
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 or when not to. Since there are no siblings that start a session, usage is implied but not explicitly stated. No alternatives or context provided.
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 provided, so description carries full burden. It does not disclose if the tool is read-only, modifies state, requires specific permissions, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and front-loaded with the main purpose. However, it is slightly vague, costing the top score.
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 an output schema, the description is too brief given the tool's complexity and nested object parameters. It does not provide enough context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters 'pipeline' and 'target'. It fails to 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool explains pipeline effects, risks, and feedback tags. It distinguishes from siblings like validate_pipeline and recommend_pipeline. However, it could be more specific about the scope of effects and risks.
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 siblings. There is no explicit when-to-use or when-not-to-use 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 must fully disclose behavior. It only states that the tool 'summarize[s]' but does not explain side effects, authorization needs, or whether it modifies state. Parameters like 'accepted' suggest potential state changes, but this is 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise at one sentence, but it is under-specified. Every word counts, but the lack of detail impacts usefulness. It could be restructured to include key behavioral notes without adding length.
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 5 parameters, 2 required, and an output schema, the description is insufficient. It does not describe the return value, the effect of 'accepted' or 'feedback_tags,' or how the output schema relates to the summary. The description leaves significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does not explain any parameters, leaving the agent to rely on parameter names alone. While names like 'baseline_run_id' and 'candidate_run_id' are somewhat self-explanatory, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'summarize' and the resource 'baseline-to-candidate preview tuning step.' However, it does not differentiate from sibling tools like 'compare_preview_runs' or 'record_tuning_session_step,' which have similar 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?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The single sentence lacks usage 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 exist, and the description does not disclose behavioral traits such as side effects, destructive potential, or required permissions. For a validation tool, it likely does not mutate state, but this is not explicitly stated.
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, which is concise but fails to convey essential information. It is under-specified rather than efficiently written.
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 tool has two parameters (one required) with no schema descriptions, nested objects, and an output schema (not shown). The description is insufficient for an agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the meaning, structure, or constraints of the 'request' and 'target' parameters. These parameters are complex (nested objects) but remain undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'validate' and the resource 'preview request', and provides context 'before rendering local preview artifacts'. It distinguishes this tool from sibling tools like render_preview or render_preview_batch.
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 (e.g., validate_pipeline, render_preview). There are no explicit when-to-use or when-not-to-use instructions.
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. It only mentions 'export', which implies a read operation, but does not state whether it modifies state, requires authentication, or any side effects. Lacks transparency on 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 a single sentence, making it very concise, but it lacks structure (no front-loading of key info) and is too minimal, omitting important details. It is not wasteful but underspecified.
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 4 parameters and existence of an output schema, the description is incomplete. It fails to explain what 'tuning decisions' are, when to use this tool versus similar ones, and how parameters affect output. The output schema mitigates but does not compensate for lack of description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 4 parameters except indirectly mentioning output formats. Parameters like 'limit', 'accepted_only', and 'ranked' are left entirely to the schema, providing no additional meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool exports persisted tuning decisions and specifies the output formats (markdown or JSON). It uses a specific verb and resource, distinguishing it from siblings like 'export_tuning_session' and 'export_preview_report'.
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 vs alternatives (e.g., export_tuning_session), no prerequisites, and no hints on context or when not to use it. The description is silent on usage scenarios.
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 states 'inspect' (read-only implied) but does not clarify side effects, permissions, or whether it modifies any state. The agent cannot determine safety or constraints from this description alone.
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?
Description is very concise (one sentence) and front-loaded with the action, but it lacks necessary detail. While efficiency is good, the trade-off with completeness reduces its overall helpfulness.
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 an output schema, the description does not indicate what quality metrics or results are returned. The agent cannot form accurate expectations about the tool's output, making it incomplete for informed tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and description adds no meaning for the two parameters (dataset_path, max_images). The agent must rely on the schema alone, which only provides names, types, and defaults. No indication of how max_images affects inspection or the format of dataset_path.
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?
Description clearly states the tool inspects local dataset image quality with a specific temporal context ('before first preview rendering'), which helps differentiate it from related tools like list_quality_profiles or score_dataset_preview_candidates. However, it could more explicitly distinguish itself from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage before first preview rendering, but no explicit guidance on when to use this tool versus alternatives (e.g., score_dataset_preview_candidates) or when not to use it. The agent lacks context on prerequisites 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 exist, so the description carries full burden. It states the conversion but omits behavioral details such as whether it overwrites existing tags, requires pre-recorded feedback, or operates server-side.
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, but it is not very informative. Conciseness is present but at the expense of necessary detail. Stucture is acceptable but minimal.
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 an output schema (not shown), the description is incomplete. It does not explain the conversion process, dependencies on existing feedback, or side effects. More context is needed for a single-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'feedback_note' has a schema with 0% description coverage (only title). The description adds no meaning beyond the property name, lacking format, constraints, or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'convert' and the resource 'free-form preview feedback into structured feedback tags,' effectively distinguishing it from siblings like record_preview_feedback (which records raw feedback) and list_feedback_tags (which lists existing tags).
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 (e.g., record_preview_feedback for initial recording, list_feedback_tags for listing results). The description does not indicate prerequisites 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?
With no annotations, the description should disclose behavioral traits like pagination behavior, ordering, or what 'concrete' means. It does not; it only restates the tool's basic function. No mention of output format or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. However, it sacrifices completeness for brevity, which is acceptable but not optimal.
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 three parameters and no schema description coverage, the description lacks essential context. It does not explain how to use run_id for filtering, the meaning of limit, or the effect of accepted_only. The presence of an output schema is not leveraged.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the three parameters (run_id, limit, accepted_only). Their purpose (e.g., filtering, pagination) remains unclear without external knowledge.
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 'List concrete preview feedback records' clearly states the action (list) and the resource (preview feedback records). The word 'concrete' hints at non-aggregated records, distinguishing it somewhat from sibling tools like record_preview_feedback or list_feedback_tags, though not explicitly.
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 such as list_feedback_tags or get_preview_manifest. No context about prerequisites or typical use cases is provided.
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 burden, but it only says 'List' implying a read operation. No details on authentication, rate limits, or data scope are provided.
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 but lacks necessary detail. It is concise but at the expense of completeness.
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 two parameters (limit, status) and no required fields, the description should explain filtering and output format. It misses high-level context like what a tuning session is and how status values differ.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no information about the 'limit' or 'status' parameters. It fails to explain how they affect the query or expected values.
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 ('List') and the resource ('persisted interactive preview tuning sessions'). Among sibling tools like archive_tuning_session and start_tuning_session, this uniquely identifies a listing operation.
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 alternatives like list_preview_runs or list_tuning_decisions. No context on scenarios or exclusions is given.
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?
Without annotations, the description must disclose behavioral traits. It lacks information about whether feedback can be overwritten, whether it triggers any side effects (e.g., updating preview state), or any authorization needs. The brief description does not compensate for the missing annotations.
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, but at the cost of omitting crucial information. There is no filler, but it could be expanded to cover essential details without becoming verbose.
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 description is insufficient for the tool's complexity. It lacks context about when this tool is called in the workflow, what the output schema contains, and how to properly use the parameters. A complete description would mention that this is typically called after getting a preview and that the output confirms the recording.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should clarify parameter roles. It fails to define any of the 6 parameters, leaving the agent to infer from names alone. For example, it's unclear whether 'accepted' means the image is accepted or the feedback is accepted.
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 (persist), the resource (user feedback), and the specificity (one concrete preview image variant), effectively differentiating it from related tools like list_feedback_tags and list_preview_feedback.
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 does not provide any usage guidelines, such as when to use this tool over alternatives (e.g., recording batch feedback or adjusting pipeline). It lacks context about prerequisites or expected flow.
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 but only mentions 'deterministic' and 'local input images'; it does not disclose side effects, auth needs, or rate limits.
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, but it lacks necessary detail to be effective; it is under-specified.
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 an output schema and complex input, the description does not explain what the artifacts or contact sheets are, nor how to use the request object, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of the 'request' parameter's structure or semantics beyond its name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Render' and the resource 'batch preview artifacts and contact sheets', and specifies 'for local input images', which distinguishes it from sibling tools like 'render_preview' and others.
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; no mention of prerequisites 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?
The description does not disclose any behavioral traits such as read-only nature, pagination behavior, or potential side effects. As no annotations exist, the description carries the full burden but provides minimal information.
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 with a single sentence, but it sacrifices informative content at the cost of brevity.
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 presence of an output schema, the description does not need to explain return values, but it fails to provide essential context such as filtering or ordering capabilities. The tool has many siblings, and the minimal description does not aid in correct selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not mention any of the three parameters (limit, accepted_only, ranked). The description adds no value beyond the input 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 clearly states the action ('List') and the resource ('persisted local tuning decisions'), distinguishing it from sibling tools like 'record_tuning_decision' and 'list_tuning_sessions'.
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 other list tools (e.g., list_tuning_sessions) or under what circumstances to avoid 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Adjust' implies mutation, but there is no mention of side effects, permissions, reversibility, or what changes occur. The description is too minimal 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the purpose. No redundant text. However, it could include more detail without becoming verbose.
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 two required parameters (one nested object), an output schema, and 10 sibling tools, the description is too brief. It fails to explain how feedback tags adjust the pipeline, what the output contains, or any constraints. The existing output schema partially compensates, but the description is still incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description only names the parameters (pipeline, feedback_tags) but does not explain their structure or allowed values. For example, what is the format of feedback_tags? What properties does the pipeline object need? The output schema exists but does not help parameter semantics.
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 verb 'adjust' and resource 'pipeline', and specifies it uses 'structured preview feedback tags' as input. However, it does not differentiate from sibling tools like 'recommend_pipeline' or 'update_pipeline' (if any), and the meaning of 'adjust' could be more specific.
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: use when you have feedback tags from previews. There is no explicit guidance on when to prefer this over siblings like 'validate_pipeline' or 'explain_pipeline', nor any exclusions or prerequisites.
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 fully convey behavioral traits. It notes that runs are deleted based on a retention count, but does not disclose whether deletion is permanent, any required permissions, side effects, or what happens to dependent data. This lack of detail leaves the agent uncertain about the tool's impact.
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 (8 words). While concise, it is under-specified, lacking important details that would make it efficiently informative. It could benefit from a brief explanation of the parameter or expected outcome.
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 one parameter and an output schema, the description should at least explain the parameter and indicate what the output contains. It does neither, leaving significant gaps about how to use the tool correctly and what to expect from the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter, keep_last, with 0% schema description coverage. The description mentions 'beyond a retention count' but does not explicitly link to keep_last or explain its meaning (e.g., number of runs to keep). No default behavior or constraints are clarified, requiring the agent to infer the parameter's role.
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 'Delete older preview runs beyond a retention count' clearly states the action (delete), resource (preview runs), and the selection criterion (retention count). It distinguishes itself from siblings like delete_preview_run (single deletion) and list_preview_runs (listing).
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 like delete_preview_run. There are no prerequisites, exclusions, or usage context provided. The description solely states what the tool does without any usage recommendations.
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 transparency burden. It mentions 'guarded CPU Tensor Python handoff,' which hints at some output behavior, but it does not disclose side effects, permissions, output destination, or error conditions. For an export operation with no annotation support, this is insufficient.
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, which is concise and front-loaded with the core action. The only downside is the cryptic phrase 'guarded CPU Tensor Python handoff,' which may reduce clarity, but overall it avoids unnecessary 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?
The tool has 4 parameters including an enum and nested objects, and no annotations. The description does not mention the output format options, the role of the target/input_contract, or any preconditions beyond validation. While an output schema exists, the description still fails to cover essential contextual information for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description needs to explain the parameters. It only references 'pipeline' and the concept of a guarded Python handoff, but does not clarify the meaning of 'target', 'output_format', or 'input_contract'. Some value is added by implying the pipeline is validated, but most parameter semantics remain undocumented.
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 specific verb and resource: 'Export a validated pipeline.' The optional 'guarded CPU Tensor Python handoff' adds a distinctive detail, though it is somewhat jargon-heavy. It is clear enough to distinguish from sibling tools like export_tuning_session.
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 'validated pipeline' implies the pipeline should be validated before export, which provides some usage context. However, there is no explicit statement of when to choose this tool over alternatives or when not to use it, so guidance remains 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?
No annotations are provided, so the description must fully disclose behavior. It only indicates a read operation but omits details like error handling, idempotency, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that efficiently conveys the core purpose with no extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists, return values need not be explained. However, the lack of usage context and behavioral details makes the description barely adequate for a tool with one parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds no meaning beyond the parameter name 'run_id'. It does not explain what constitutes a valid run_id or how to obtain it.
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 returns the manifest JSON for one recorded preview run, using a specific verb and resource. However, it does not differentiate from sibling tools like list_preview_runs or render_preview.
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 such as list_preview_runs or how to interpret IDs. The description lacks 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?
No annotations are provided, so the description carries full burden but reveals no behavioral traits (e.g., side effects, permissions, rate limits). The verb 'plan' implies a non-destructive operation, but this is not confirmed, and no additional context is given.
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—one sentence with no filler. It front-loads the purpose and resource, making it quick to parse. Every word adds value.
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 an output schema, the description fails to provide parameter context for the 8-parameter schema. With 0% schema coverage, the agent must guess parameter meanings, leading to likely incorrect invocations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (no parameter descriptions in the schema), and the description does not mention any parameters. The agent receives no guidance on parameter semantics, leaving all 8 parameters (including 'task' and optional ones) undefined.
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 ('plan') and specific resource ('preview-gated policy iteration'), sourced from 'concrete review feedback'. This distinguishes it from sibling tools like 'plan_augmentation_policy' or 'plan_preview_review' by specifying the iteration 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 on when to use this tool versus alternatives. The description does not mention scenarios, prerequisites, or exclusions, leaving the agent without context 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 present, so the description must carry the behavioral burden. 'Bounded, validated' hints at constraints and input validation, but it does not disclose side effects, persistence, permissions, failure modes, or what 'bounded' means concretely (e.g., the max_images cap).
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 one short, front-loaded sentence with no filler. It is efficient, but for a 5-parameter tool with no schema descriptions it is under-specified rather than ideal.
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 does not provide enough context for selecting among many sibling tools or understanding the main optional parameters. It lacks prerequisites, when-to-use guidance, and parameter semantics, so it is incomplete given tool complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only dataset_path is implied by 'local image or image directory'; the four other parameters (task, targets, intensity, max_images) are neither described nor linked to the high-level purpose. Since schema descriptions are absent (0% coverage), the description fails to compensate.
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 specific verb ('Run') and identifies a clear resource ('one bounded, validated first preview') for a local image or directory. It conveys scope but does not explicitly distinguish it from sibling preview tools like render_preview or render_preview_batch.
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 'first preview' weakly implies this is for an initial exploratory run, but there is no explicit guidance on when to use this tool versus the many preview-related siblings. No exclusions or alternative recommendations are 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?
The description explicitly states the tool is read-only, which is a key behavioral trait. However, with no annotations provided, the description does not cover other behavioral aspects like error handling, rate limits, or specific side effects beyond being read-only.
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 very short and front-loaded with the main action. It wastes no words, but the second part about the optional resource might be better placed elsewhere. Overall, it is 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?
Given that there are four parameters with zero schema descriptions and an output schema exists but is not described, the description is insufficient. It does not explain what the tool returns, how to configure parameters, or how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should add meaning to parameters. However, it only vaguely references 'reading the client-smoke resource' without connecting to any specific parameter. The four parameters (task, targets, intensity, include_write_probe) remain largely unexplained.
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 runs a 'read-only host preflight', which is a specific verb and resource. However, it does not differentiate from sibling tools like 'diagnose_environment' or 'validate_preview_request', leaving some ambiguity about when to use this tool specifically.
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. The description mentions that reading the client-smoke resource is optional, but does not explain context, prerequisites, 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?
With no annotations provided, the description must disclose behavioral traits itself. It only states that it validates, but does not explain side effects (e.g., whether it reads or writes, returns errors on failure, or is safe/destructive). The lack of any behavioral detail beyond the validation action is a significant gap for a tool with no annotation coverage.
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 filler words. It front-loads the key action and resource, making it efficient. However, it may be too terse for the tool's complexity, but conciseness itself is well-handled.
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 has three parameters with nested objects, no annotations, and no schema descriptions, the description is woefully incomplete. It provides no context on return values, validation failure behavior, prerequisites, or how it fits into the broader export workflow. Although an output schema exists, the absence of parameter explanations and behavioral guidance leaves the agent unable to invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining the parameters. It mentions 'pipeline spec' and 'optional CPU Tensor boundary' but doesn't explicitly map these to the three schema properties (pipeline, target, input_contract). The parameter meanings remain ambiguous (e.g., which parameter is the 'CPU Tensor boundary'?), adding minimal value beyond the schema field names.
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: 'Validate a pipeline spec and optional CPU Tensor boundary before export.' It uses a specific verb ('validate'), specifies the resource ('pipeline spec'), and provides temporal context ('before export') that distinguishes it from related tools like export_pipeline.
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 'before export' implies when to use this tool (as a pre-export step), but it provides no explicit guidance on when not to use it or how it compares to alternatives such as adjust_pipeline or explain_pipeline. There are no exclusions or alternative tool references, so the usage context is only 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, and the description does not disclose behavioral traits such as side effects, prerequisites, or the meaning of 'preview-gated'. The description is insufficient for understanding the tool's operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words, making it efficient and easy to read.
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 5 parameters, no schema descriptions, no annotations, and an existing output schema, the description is too sparse. It does not explain the return value or the meaning of 'preview-gated', leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only hints at candidate_count (3-5) but fails to explain 'task', 'targets', 'objective', or 'feedback_tags', leaving most parameters ambiguous.
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 verb 'plan' and the resource 'preview-gated augmentation policy candidates for side-by-side review', distinguishing it from siblings like 'plan_augmentation_policy' which likely plans a single policy. However, it does not explicitly differentiate from other planning 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 description implies usage for planning multiple policy candidates for comparison, but lacks explicit guidance on when to use alternatives like 'plan_policy_iteration' or when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds some behavioral context by stating the audit trail is preserved, but with no annotations provided, it fails to disclose other important aspects such as whether the session becomes read-only, reversibility of archiving, or required permissions.
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, efficient sentence (10 words) that is front-loaded with the action. Every word adds value, with no redundancy.
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 a required parameter and belongs to a large set of siblings, the description provides insufficient context. It omits mention of required fields, optional parameters, and expected usage patterns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not elaborate on either parameter. While session_id is self-explanatory, the note parameter's purpose and usage remain unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'archive' and the resource 'interactive tuning session', and distinguishes from siblings by specifying 'without deleting its audit trail', which differentiates it from deletion-focused tools like delete_preview_run and cleanup_tuning_sessions.
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 explicit guidance on when to use this tool versus alternatives like close_tuning_session or summarize_tuning_session. The description does not mention prerequisites, exclusions, or contextual triggers.
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 provided, so description must disclose behavioral traits. It only states what is retrieved, not side effects or auth needs. 'Get' implies read-only but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with purpose. Efficient, but could add more context without losing conciseness.
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?
Tool is simple with one parameter and output schema exists. Description covers the basics but lacks explanation of return structure or 'target support' and 'summary'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and description adds no meaning for the 'name' parameter beyond implying it identifies a transform. No details on format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Get' and the resource 'parameter schema, target support, and summary for one transform'. It distinguishes from sibling tools which deal with pipelines and previews, not transform schemas.
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 guidance on when to use this tool versus alternatives. The purpose is implied, but there is no mention of prerequisites 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 must disclose behavior. It only states the return action and condition, but doesn't mention any side effects, permissions, errors, or output format, leaving the agent without full 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 a single sentence that is front-loaded with the action and condition. Every word is necessary, achieving excellent conciseness.
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. However, the description lacks information about what constitutes an 'active-profile workflow example' and how to choose an example_id, making the description incomplete for a fallback tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter example_id has an enum in the schema, but the description provides no explanation of these values or how to select one. With 0% schema description coverage, the description fails to compensate, leaving the parameter's meaning unclear.
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 returns a workflow example, with the specific context of when the host cannot read resources. This distinguishes it as a fallback tool, though it doesn't name any sibling tools.
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 mentions the condition for use: 'when the MCP host cannot read resources.' This provides a clear trigger, though it doesn't explicitly state when not to use it or name alternatives.
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's 'Read' implies a non-mutating operation, but it does not disclose other behavioral details like scope, error conditions, or whether the trace is post-transform. The output schema may cover return values, but the description alone is minimal.
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. It efficiently conveys the core purpose without wasted words.
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 tool has three required parameters with no schema descriptions and no annotations, yet the description only establishes the purpose. It lacks essential context about parameter semantics and usage, making it insufficient for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only hints at a 'rendered preview variant.' It does not define run_id, image_index, or variant_index, or explain how they combine to identify the trace.
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 'Read' and a specific resource 'applied-transform trace for one rendered preview variant,' clearly distinguishing it from siblings like render_preview or get_preview_manifest. It explains exactly what the tool accesses.
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 alternatives. It does not mention use cases, prerequisites, or exclude any sibling tools such as get_preview_manifest or compare_preview_runs.
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 the destructive action ('delete') and the default protection of active sessions. However, it does not detail whether deletion is permanent, if there are side effects, or required permissions. With no annotations, the description carries the burden but provides only minimal 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?
A single, well-structured sentence that conveys the core action and a key detail (default protection). No unnecessary words, making it easy to parse quickly.
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 two-parameter cleanup tool, the description covers the primary purpose and default behavior. However, it omits details about the return value (output schema exists but not explained) and potential failure cases. The description is adequate but not thorough, especially given no annotation support.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has two parameters (keep_last, include_active) with defaults but no descriptions. The schema coverage is 0%, and the description does not explain their meaning or usage beyond a hint about protecting active sessions. This leaves the agent to infer semantics from parameter names and defaults, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool deletes older tuning sessions and protects active ones by default. It uses specific verb 'delete' and resource 'tuning sessions', distinguishing it from siblings like archive_tuning_session.
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 explicit guidance on when to use this tool versus alternatives. The description only implies it's for cleanup, but does not mention when not to use it or list sibling tools like archive_tuning_session as 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 behavioral traits. It only states the core action without details like required session state, data completeness, size limits, or side effects. Minimal 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?
The description is a single sentence with no wasted words. It captures the essential purpose and output formats efficiently.
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 adequate for a simple two-parameter tool with an output schema. However, it lacks context on when to use the tool, prerequisites, or behavioral details. It is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the description adds no parameter-specific context beyond the schema. The schema already defines session_id and output_format with enum/default; description does not elaborate on syntax, valid values, or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Export', the resource 'interactive tuning session', and the output formats 'Markdown or JSON'. It distinguishes from sibling tools like export_pipeline and export_tuning_report by specifying the session type.
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 (exporting a session) but does not provide explicit guidance on when to use it versus alternatives (e.g., export_pipeline for pipelines). No prerequisites or conditions 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?
With no annotations, the description carries the burden. It discloses that the operation deletes artifacts, indicating destructiveness, but does not detail irreversibility, permissions, or side effects. It adds some value beyond the schema.
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, front-loaded sentence that efficiently states the action and scope. It wastes no words but could include more detail without significant bloat.
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 deletion tool with one parameter and an output schema (not shown), the description is minimally adequate but lacks completeness on aspects like permanence, prerequisites, or confirmation steps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the 'run_id' parameter, and the tool description adds no additional meaning. It does not specify format, source, or constraints, leaving the agent to infer from title alone.
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 specifies the verb 'delete', the resource 'preview run and its artifacts', and the location 'from the configured artifact root'. It distinguishes itself from siblings like 'cleanup_preview_runs' which operates on multiple runs.
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 deleting a single preview run but provides no explicit guidance on when to use it versus alternatives or when not to use it. It lacks context for decision-making.
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 states the tool 'list's, indicating a read-only operation, but lacks disclosure of any behavioral traits such as caching, authentication requirements, or rate limits. Minimal transparency for a simple list operation.
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 (10 words) that is front-loaded with the primary action and resource. Every word is necessary and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and the output schema exists (which handles return value documentation), the description is complete. It adequately explains what the tool does and its context for 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?
There are no parameters (0 params), and the description adds no parameter information, which is acceptable. According to guidelines, 0 params baseline is 4, and the description does not need to compensate for missing param details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states that the tool lists task-aware quality profiles accepted by preview comparison tools. It uses a specific verb ('list') and resource ('quality profiles'), and distinguishes from sibling tools that list other entities like preview runs or feedback tags.
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 ('accepted by preview comparison tools') but does not provide explicit guidance on when to use this tool versus alternatives, nor any when-not scenarios. The context is clear but lacks explicit 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. It only says 'list', which implies a read-only operation, but does not explicitly disclose any behavioral traits, such as side effects, idempotency, or data sensitivity. The description is minimal and lacks 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?
The description is a single sentence that is concise and front-loaded. It contains no unnecessary words and efficiently conveys the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are no parameters, an output schema exists, and the tool is simple, the description is sufficiently complete. It clearly explains what the tool does without needing further elaboration.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and schema description coverage is trivially 100%. The description does not need to add parameter information. The baseline for no parameters is 4, and the description meets that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'structured feedback tags accepted by adjust_pipeline.' It distinguishes the tool from siblings by specifying its role as a helper for adjust_pipeline, which is among the sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that this tool is used to retrieve valid feedback tags before using adjust_pipeline. It provides clear context but does not explicitly state when not to use it or mention alternatives.
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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