dashbrr-mcp

Official

by arr-mcps

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.1.1
Disambiguation5/5
Every tool targets a distinct service or resource, e.g., get_sonarr_queue vs get_sonarr_stats, and health check tools are clearly separated by target (dashbrr itself vs configured services). No two tools appear to do the same thing.
Naming Consistency5/5
All tools follow a consistent dashbrr_<verb>_<noun> pattern, with verbs like get, list, create, delete, set, save, check. The minor plural inconsistency in ui_preferences vs ui_preference doesn't affect predictability.
Tool Count3/5
At 34 tools, the count is heavy, but the server aggregates many distinct services (autobrr, Jellyfin, Traefik, etc.), so the breadth is justified. Still, the number edges into the 'too many' range for a typical MCP server.
Completeness4/5
The surface covers settings CRUD, per-service monitoring summaries, queue deletion for media managers, Overseerr approvals, and Plex auth flow. Missing are some deeper management actions (e.g., trigger scans), but the core dashboard operations are covered.
Average 4.1/5 across 34 of 34 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 12 commits in the last 12 weeks
- Last stable release on August 12, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so the agent knows it's a safe read. The description adds no behavioral context beyond that, such as what counts as an active session or whether it returns an empty list. It does not contradict annotations, but adds little value beyond them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one short phrase for purpose and one short sentence for the parameter constraint. It is front-loaded with the main point and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple read-only getter with one parameter and an output schema present, so the description need not explain return values. It covers the core purpose and the critical parameter detail. However, it lacks any additional context such as expected response shape or limitations, making it minimally sufficient but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no description for instance_id (0% schema coverage). The description compensates with the type-prefix requirement and an example ('plex-main'), which gives format guidance. However, it does not explain the semantic role of the parameter beyond what the name implies.
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 'Active Plex playback sessions' clearly identifies the resource (Plex playback sessions) and implies retrieval, especially with the 'get' in the tool name. It distinguishes from siblings by specifying Plex specifically. However, it lacks an explicit verb, so it is clear but not maximally 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?
The description provides no guidance on when to use this tool versus alternatives. It only states the instance_id type-prefix requirement, which is a parameter constraint rather than a usage scenario. There is no mention of prerequisites, exclusions, or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds no additional behavioral context beyond the type-prefix requirement, which is parameter semantics rather than behavior. It does not contradict annotations, so a mid-range score is appropriate.
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 short sentence plus an example. Every word serves a purpose, and the type-prefix requirement is front-loaded. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only queue getter with one parameter and an output schema, the description is adequately complete. It states the resource and the key parameter constraint. It does not describe queue contents, but the output schema covers that. Slight gap in not addressing any edge cases, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining that instance_id must be type-prefixed (e.g., 'lidarr-0'). This adds critical format information not available from the schema, showing meaningful effort to clarify the single parameter.
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 identifies the resource clearly as 'Lidarr download queue' and the tool name includes the verb 'get'. It distinguishes from sibling queue tools by naming Lidarr specifically. However, it lacks an explicit verb in the description, relying on the tool name for that.
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 alternative queue tools like sonarr_queue or radarr_queue. The only usage-related information is the type-prefix requirement for instance_id, which is more of a parameter detail than contextual usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds the field list (id, title, isActive, etc.) which hints at return structure, but does not disclose pagination, limits, or other behavioral characteristics. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, both useful. The first sentence states the resource and return fields, and the second covers the parameter requirement. There is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only collection tool with an output schema and annotations, the description covers the essential aspects: what data is returned and the one parameter constraint. Although usage guidelines are absent, the tool is simple enough that this description is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines instance_id as a string with no description. The description adds crucial semantic information: 'instance_id must be type-prefixed, e.g. maintainerr-0', providing an example that clarifies the expected format. This compensates well for the 0% schema coverage.
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 identifies the resource as 'Maintainerr collections' and lists the fields returned, but lacks an explicit verb like 'get' or 'retrieve' in the description itself. However, the tool name uses 'get' and sibling tools are all get_* operations, making the purpose clear enough.
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, no exclusions, and no context about appropriate scenarios. The description only provides a parameter hint, which does not serve as usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes the safety profile, and the description adds that the result includes queue and recent failures. However, it doesn't disclose other behavioral traits like data freshness, pagination, or any read-side effects. It neither contradicts nor significantly enriches the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence clearly states the tool's purpose, and the second provides the essential parameter format hint. There is no filler, repetition, or unnecessary detail, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only getter with one parameter and an output schema, the description covers the key input requirement and what the tool returns. It doesn't explain what 'recent failures' means in terms of time window, and it omits any intended usage context, but the existence of an output schema reduces the need to describe return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines instance_id as a string with no description. The description adds a critical requirement: it must be type-prefixed (e.g., 'sabnzbd-0'). This provides actionable formatting guidance beyond the schema, which otherwise leaves the parameter 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 states the tool returns 'SABnzbd queue plus recent failures', which is a specific scope and distinguishes it from sibling summary tools for other services like NZBGet or Bazarr. The verb 'get' is implied by the tool name, and the description clarifies what the summary contains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives such as dashbrr_get_nzbget_summary or dashbrr_get_bazarr_summary. It also lacks prerequisites or exclusions. The only usage-related hint is the instance_id type-prefix requirement, which is more about parameter formatting than tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context about the return payload (data array, count, next_cursor) and the required type-prefixed format for instance_id. Since readOnlyHint is already set, this supplemental information is valuable without contradicting the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. The output shape is front-loaded, and the parameter note is immediately actionable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While brief, the description covers what the tool returns and the key input constraint. With an output schema and read-only annotation present, it is sufficient for a simple retrieval tool, though details like the time window for 'recent' are not disclosed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides a bare string parameter with no description (0% coverage), but the description compensates by specifying the required format with an example ('autobrr-0'). It doesn't explain the semantic meaning of instance_id itself, but for a single-parameter tool this is adequate.
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 identifies the resource as 'Recent autobrr releases' and implies a retrieval operation, distinguishing it from sibling tools like autobrr_irc and autobrr_stats. However, it lacks an explicit verb such as 'gets' or 'lists', relying on the tool name to convey the action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like dashbrr_get_autobrr_stats or dashbrr_get_autobrr_irc. The description only states the output shape and a parameter constraint, so the agent cannot differentiate use cases.
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?
ReadOnlyHint annotation already indicates a safe read operation. The description adds content scope (badges, provider statuses, health issues) but does not disclose additional behavioral traits beyond that. The instance_id type-prefix note is more parameter semantics than behavioral transparency. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose and immediately followed by the critical parameter format. Every word earns its place, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only summary tool with a single parameter and an output schema, the description adequately covers the tool's scope and the parameter format. The presence of an output schema reduces the need to describe return values. Minor gaps remain around the meaning of 'badges' and potential error conditions, but these are not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It provides crucial syntax guidance for the single parameter: 'instance_id must be type-prefixed, e.g., bazarr-0'. This adds meaning beyond the bare string type. However, it does not explain why the prefix is needed or list possible prefixes, leaving some ambiguity.
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 the resource (Bazarr) and the content categories (badges, subtitle provider statuses, health issues), making it clear this tool retrieves a Bazarr-specific summary. It distinguishes from siblings by naming Bazarr, though it lacks an explicit verb like 'get' or 'retrieve'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied by the tool name and description (use for Bazarr summary), but there is no explicit guidance on when to choose this over alternatives or any notes on exclusions. The only additional instruction is about instance_id formatting, which is parameter guidance, not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The `readOnlyHint` annotation already establishes that this is a safe read operation. The description adds transparency by disclosing the exact fields returned and the requirement that `instance_id` be type-prefixed. This is adequate for a simple getter, though it does not mention error behavior or ordering.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence clearly states the tool's purpose and output fields, while the second provides a crucial parameter constraint. There is no redundant information.
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 covers the return fields and a key parameter detail, and an output schema exists, so return values need not be fully detailed. However, it lacks any guidance on when to choose this over a sibling like `dashbrr_get_prowlarr_stats`, which is a notable gap given many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no description for `instance_id` (0% coverage), but the description compensates somewhat by explaining the type-prefix requirement with an example. However, it does not define what constitutes a valid type prefix or how to obtain the ID, so the compensation is partial.
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 identifies the tool as returning a Prowlarr indexer list with specific fields (id, name, enable, priority, response time, grab/query counts), which is a specific resource and scope. It does not explicitly differentiate from sibling `dashbrr_get_prowlarr_stats`, but the field list implies a distinct purpose.
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 by stating it returns an indexer list and notes that `instance_id` must be type-prefixed, which is a prerequisite. However, it does not provide explicit when-to-use guidance or mention alternatives like `dashbrr_get_prowlarr_stats`, leaving the agent to infer based on tool naming.
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 readOnlyHint annotation covers the safe-read behavioral trait. The description adds the type-prefix requirement for instance_id, which is a useful constraint, but it does not disclose other behaviors such as error handling, output specifics, or any side effects. This is acceptable given the annotation but not highly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, with the purpose stated first and the critical parameter constraint second. Every word earns its place, and there is no redundancy or irrelevant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, read-only, and an output schema present), the description covers the main gotcha (type-prefix format) and states the basic purpose. It does not elaborate on what the summary contains, but the output schema exists to fill that gap, making the description sufficiently complete for a basic getter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only specifies instance_id as a string, with no description. The tool description adds crucial meaning by requiring a type prefix (e.g., 'uptimekuma-0'), giving the only parameter a concrete format and example that the schema completely lacks. This fully compensates for the 0% schema coverage.
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 identifies the resource (Uptime Kuma) and the deliverable (monitor summary), distinguishing it from sibling tools that target other services. However, it is a noun phrase rather than an explicit imperative like 'Retrieve' or 'Get', so it lacks an explicit verb, though the tool name compensates.
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 for when to use this tool versus alternatives. The description solely addresses the instance_id format, not selection criteria or exclusions. Sibling tools imply service-specific usage, but the description itself offers no contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructiveHint=true), the description discloses that api_key is write-only and can be omitted to preserve the existing key during updates. It also clarifies that access_url is optional. This adds meaningful behavioral context about update semantics.
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?
Three tight sentences. Front-loaded with the core action, followed by parameter clarifications. No redundant phrases or filler. The structure is logical and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main behavior, key parameter nuances, and safety considerations. An output schema is present, so return value details are not required. It is missing only a note about whether the operation overwrites the entire config, but 'create or update' implies that. Overall, sufficient for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates for three of five parameters: instance (type-prefixed), api_key (write-only, omit to keep), and access_url (optional). However, display_name and url are left undefined, leaving the required fields partially unexplained.
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 states 'Create or update a service configuration on the dashbrr instance', a specific verb+resource pairing. This clearly distinguishes it from sibling tools like dashbrr_get_settings or dashbrr_delete_settings, and the scope is immediately evident.
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. It does not mention that creation/update differs from deletion or that it should be used in conjunction with get_settings. The parameter examples provide some context, but there are no usage criteria or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds that the tool reads NZBGet queue, status, and recent failures, plus the parameter format requirement. It does not contradict the annotations and adds useful behavioral context, though it doesn't mention potential caveats like pagination or failure handling (output schema may cover return structure).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. The first sentence states the tool's scope, and the second delivers a critical parameter constraint. Every word contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and an output schema, the description covers the essential data categories and the required parameter format. It doesn't elaborate on what 'recent failures' means or how the summary is composed, but given the low complexity and output schema, this is only a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by explaining that instance_id must be type-prefixed and gives an example. It adds meaning beyond the bare string type, though it doesn't enumerate all valid prefixes or explain the underlying instance model.
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 identifies the resource (NZBGet) and the data it returns (queue, status, recent failures), which distinguishes it from sibling get_summary tools for other services. However, it is a noun phrase with no explicit verb like 'retrieve' or 'get', relying on the tool name for the action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides essential guidance for the instance_id parameter (must be type-prefixed, e.g., nzbget-0), which directly aids correct invocation. However, it does not explicitly state when to use this tool over alternatives or exclude any cases, so 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds useful behavioral context: the return composition (pendingCount + request list) and a concrete requirement for instance_id formatting. No contradictions exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the tool's purpose and followed by the parameter requirement. No filler or redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and an output schema, the description covers the core purpose, return content, and a critical parameter constraint. It is complete enough for an agent to safely select and invoke the tool, though it does not address potential edge cases or response pagination.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has zero description coverage (0%), so the description must compensate. It does so effectively by explaining that instance_id must be type-prefixed and providing an example ('overseerr-0'), which is essential 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 clearly identifies the resource (Overseerr media requests) and scope (pending), and the 'get_' prefix supplies the verb. It distinguishes from the sibling set_overseerr_request_status by focusing on retrieval, though it does not explicitly name an action verb in the description.
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 is implied by the 'pending' qualifier (use this for pending requests), but no explicit alternatives or when-not scenarios are provided. There is no mention of other tools like the setter for status changes, leaving the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds value by disclosing that `instance_id` must be type-prefixed (e.g., 'readarr-0'). This is a non-obvious behavioral constraint that helps prevent invocation errors. However, it does not detail the queue content or any other operational behavior, so it falls short of a 5.
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 an inline example, extremely concise and front-loaded. Every word earns its place, and it avoids redundancy with the schema or annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-queue tool with one parameter and an output schema, the description adequately covers the essential information: what the tool returns and how to pass the required parameter. It lacks background on prerequisites (e.g., instance configuration) or selection context, but given the low complexity, this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With a schema description coverage of 0%, the description fully compensates by explaining the required format for the sole parameter `instance_id`. The example 'readarr-0' clarifies the type-prefix requirement, adding meaning that the bare string type in the schema does not convey.
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 'Readarr download queue' clearly indicates this tool retrieves the download queue for Readarr, and the name 'dashbrr_get_readarr_queue' reinforces the get action. It distinguishes among sibling queue tools (sonarr, radarr, lidarr) via the explicit 'Readarr' reference, though the verb is only implied by the name rather than stated in the description.
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 sonarr_queue, radarr_queue, or lidarr_queue. There is no explicit context for selecting this tool based on the target application (e.g., books vs. movies or shows).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful behavioral context beyond the readOnlyHint annotation by noting that records are paged and that instance_id must be type-prefixed (e.g., 'sonarr-1'). These details help the agent understand data traversal and parameter formatting, which the annotation does not cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that front-load the primary purpose and immediately state the essential parameter requirement. Every word adds value, with no unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter), the presence of an output schema, and the readOnlyHint annotation, the description is nearly complete. It covers the tool's purpose, pagination behavior, and parameter format. It lacks details on pagination mechanics (e.g., page size, navigation), but the output schema likely covers response structure, so this is not a significant gap.
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?
With a schema description coverage of 0%, the description compensates by explaining the required instance_id format: 'must be type-prefixed, e.g. sonarr-1'. This adds critical meaning beyond the schema's mere 'string' type, clarifying that the instance identifier is not arbitrary.
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 'Sonarr download queue (paged records with series/episode info)' clearly indicates the tool retrieves the Sonarr download queue, distinguishing it from sibling tools for other services (Radarr, Lidarr, etc.) and from Sonarr stats. Although it lacks an explicit verb like 'get' or 'list', the noun phrase combined with the tool name makes the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when the Sonarr download queue is needed, but does not explicitly state when to use this tool over alternatives like dashbrr_get_sonarr_stats or the queue getters for other services. No exclusions or alternative recommendations are provided, leaving the agent to infer from sibling names.
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 readOnlyHint annotation already declares a safe read operation. The description adds that stats are 'queue-derived' and includes server version, providing some context about the data source. It also discloses the instance_id type-prefix constraint. However, it does not go further to describe failure modes, rate limits, or other behavioral nuances, which is acceptable given the simple read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, each with a clear purpose: the first specifies the output, the second provides a required parameter format. No unnecessary words or redundancy. This is a model of concise, front-loaded documentation.
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 low complexity (one parameter, read-only, output schema present), the description is complete. It covers the non-obvious instance_id format and the output composition. The existence of an output schema means the return values are already documented, so the description need not repeat them.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no description for instance_id (0% coverage), so the description must compensate. It does so by explicitly stating that instance_id must be type-prefixed and giving the example 'sonarr-1'. This is essential, actionable information that the schema lacks, making the parameter semantics clear.
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 that the tool returns Sonarr queue-derived stats plus server version, specifying the output shape as {stats, version}. This distinguishes it from sibling tools like dashbrr_get_sonarr_queue, which focuses on the raw queue. The purpose is immediately evident despite lacking an explicit verb, as the tool name includes 'get'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives. The description does not mention sibling tools or exclusions, and the only usage hint is the instance_id format requirement, which is more about parameter semantics than tool selection. An agent must infer usage from the tool name and output description.
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?
Annotations declare readOnlyHint=true, and the description does not contradict this. The description adds the instance_id type-prefix requirement, but there is no additional behavioral disclosure such as return format, pagination, or side effects. Since the tool is read-only and simple, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: the first states the output metrics, the second provides the critical parameter constraint. No unnecessary words, front-loaded with the most important information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description covers the core purpose and parameter constraint. It lacks explicit usage guidance relative to sibling tools, but given the straightforward nature of a stats-fetching operation, this is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden for the single parameter. It clearly explains that instance_id must be type-prefixed with an example ('autobrr-0'), which is essential for correct invocation. The example adds practical value, though the range of valid prefixes is not fully specified.
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: autobrr release counters with specific metric types (total/filtered/rejected/approved/error). It differentiates from sibling tools like dashbrr_get_autobrr_irc and dashbrr_get_autobrr_releases by naming the exact data returned.
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 retrieving release counters but does not explicitly specify when to use this tool over alternatives or provide exclusions. It gives a parameter hint (instance_id format) but lacks context on appropriate scenarios or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation readOnlyHint=true is consistent with the description's 'overview/summary' wording. The description adds a critical behavioral requirement (instance_id must be type-prefixed) beyond the annotation. It doesn't describe side effects, rate limits, or other behaviors, but with readOnlyHint the bar is lower and this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, tightly written. The first sentence front-loads the tool's purpose, and the second provides essential parameter guidance. No redundant wording or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple input schema and an output schema that likely covers return structure. The description adequately scopes the tool's function (Traefik routers/services/middleware, issue flags, certificates) and the required parameter format. It doesn't explain return values, but the output schema handles that. Minor omissions like what 'flagged issue routers' means are not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description carries the burden. It compensates well by explaining the instance_id format and providing a concrete example ('traefik-0'). This gives actionable meaning beyond the schema's plain 'string' type, making the parameter semantics much clearer.
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 returns a 'Traefik router/service/middleware overview, flagged issue routers, and certificate summary.' This is a specific verb+resource+scope, and the name reinforces it. It naturally distinguishes from sibling tools by targeting Traefik specifically.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternative guidance is given. However, the description's clear resource focus (Traefik) makes the intended use case obvious, especially given the many sibling tools for different services. Usage is implied but not explicitly contrasted with 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?
Annotations already indicate a write operation (readOnlyHint=false, destructiveHint=true). The description adds that the change is per-user and that the key identifies the panel, but it does not disclose persistence, reversibility, or potential error cases (e.g., invalid key). It adds some user-specific context but not a robust behavioral picture.
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 exactly two sentences, front-loaded with the primary action in the first sentence and parameter details in the second. There is no redundant information; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple setter with two primitive parameters and no output schema, the description covers the purpose, user scope, and parameter semantics. It omits return values and error handling, but given the low complexity of this tool, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It explains 'key identifies the panel' and 'collapsed toggles its state,' which adds meaning beyond the bare schema. However, 'toggles' is slightly ambiguous (could imply flipping current state), and it does not specify valid key values or the exact meaning of true/false for collapsed.
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 a specific action: 'Set whether a dashboard panel is collapsed for the authenticated user.' It uses a specific verb ('Set') and identifies the resource (dashboard panel collapse state) and the user scope (authenticated user), distinguishing it from sibling getters like dashbrr_get_ui_preferences_collapse and other set 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 provides clear context: this tool is for changing a dashboard panel's collapsed state for the authenticated user, and it explains the role of each parameter. However, it does not explicitly contrast with alternatives such as save_settings or the corresponding getter, nor does it state when not to use it. Thus it has clear context but no exclusions/alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare destructiveHint=true, and the description adds useful behavioral context: the `instance_id` must be type-prefixed (e.g., 'lidarr-0'), and the option flags are only applied when set to true. This goes beyond the annotation by clarifying input requirements and option semantics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, front-loaded with the primary action, and every sentence adds value. It includes a cross-reference for obtaining `id`, a format requirement for `instance_id`, and a behavioral note for the options. No waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple delete operation with no output schema and good annotations, the description covers the key aspects: what is deleted, how to get the id, the instance_id format, and option behavior. It does not mention potential side effects beyond the destructive annotation, but the destructive hint already covers that, so the description is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It names all six parameters and adds critical semantics for `instance_id` (type-prefix requirement) and the conditional behavior of the boolean options. While it doesn't explain each option in depth, the naming plus the conditional note provides enough meaning for an agent to use the tool correctly.
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+resource: 'Delete an item from the Lidarr download queue.' It clearly distinguishes this from sibling tools like dashbrr_delete_sonarr_queue_item by naming Lidarr, and from get_lidarr_queue by the delete action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating the action and providing the source of the `id` parameter (from dashbrr_get_lidarr_queue), but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. The sibling context helps, but the description itself lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, so the description doesn't need to restate that. It adds useful context about the options being 'only applied when set to true,' which clarifies their conditional behavior. However, it does not disclose potential side effects, such as whether files are removed from the client by default or what happens when remove_from_client is false. This leaves some ambiguity about the deletion's scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action. Every sentence earns its place: the first states the operation, the second clarifies parameters and option semantics. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters (2 required), no output schema, and a destructive action. The description covers all required parameters and the behavior of optional booleans, which is the core information needed to invoke it safely. It does not describe the return value or error handling, but for a simple delete operation that is often acceptable. Given the good annotation coverage, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does: it explains `id` as the queue record id from dashbrr_get_radarr_queue, `instance_id` must be type-prefixed with an example, and groups the four boolean options with a rule that they are only applied when true. This adds meaning beyond the bare schema, though it doesn't individually explain each option's effect, which is partially inferable from 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 action: 'Delete an item from the Radarr download queue.' It specifies the resource (Radarr queue) and the verb (delete). It distinguishes from siblings by naming 'Radarr' explicitly, contrasting with delete_sonarr_queue_item, delete_lidarr_queue_item, and delete_readarr_queue_item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: explains that `id` comes from dashbrr_get_radarr_queue and that `instance_id` must be type-prefixed (e.g., `radarr-1`). While it doesn't explicitly say 'use this instead of X', the Radarr-specific naming and sibling context make the intended use obvious. No exclusions are stated, but the guidance is sufficient for selecting the correct tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so the safety profile is clear. The description adds behavioral context by specifying instance_id type-prefix requirements and the exact health fields returned, which go beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and pack in the essential parameter guidance. Every word earns its place; no redundant or vague phrasing.
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 low complexity (one parameter, read-only) and the presence of an output schema, the description adequately captures purpose, key usage constraint, and return fields. No additional context is needed for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description fully compensates by explaining the only parameter (instance_id) and providing a concrete example of the required type-prefix format. This adds essential meaning beyond the schema's bare string type.
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 specifies the resource (autobrr IRC networks) and the returned health fields (name/healthy/enabled), distinguishing it from sibling tools like get_autobrr_releases. It lacks an explicit verb, but the tool name includes 'get' and the meaning is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking IRC network health but does not explicitly state when to use this tool over alternatives. It does provide a key usage constraint (instance_id must be type-prefixed), which is partially a usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description adds valuable context: the requirement that instance_id must be type-prefixed (e.g., jellyfin-main), and what data is included in the response. This exceeds bare annotation coverage, though it does not discuss error cases or response size.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. The first sentence states the main purpose and key data points; the second clarifies the critical parameter format. Information is front-loaded and each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is an output schema that documents return values, the description does not need to explain output shape. It covers what the tool does, critical parameter semantics, and safety profile via annotations. Slight gap: no mention of prerequisites (e.g., service availability), but overall complete for a single-parameter read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only a string type for instance_id with no description. The tool description compensates by explaining the required type-prefix format with a concrete example. This gives the agent actionable guidance beyond the raw schema, though it does not enumerate all valid prefixes.
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 provides Jellyfin system info plus active sessions with specific details like play state, now playing item, and transcoding. This is a specific verb+resource+scope, and it distinguishes itself from sibling tools by naming Jellyfin and listing included data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need Jellyfin system info/sessions) but does not explicitly state when to use it versus alternatives like dashbrr_get_plex_sessions. No exclusion or alternative guidance is provided, only a requirement for the instance_id format.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the readOnlyHint annotation by explaining the polling nature and the authToken completion condition. It informs the agent that repeated calls are safe and when to stop, which is valuable for a read-only polling tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that front-load the core action and provide a clear completion condition. Every sentence contributes meaningful information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter polling tool with an output schema and readOnlyHint, the description covers the purpose, prerequisite, success condition, and termination point. It does not mention rate limits or error cases, but these are not critical given the tool's simplicity and the annotation's safety profile.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one integer parameter pin_id with no description, and the description does not explicitly define it. The reference to 'Plex PIN created with dashbrr_create_plex_pin' implies pin_id is the identifier from that call, but this is left to inference. Given 0% schema coverage, the description should be more explicit.
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 polls the status of a Plex PIN created with dashbrr_create_plex_pin. This specifies the exact verb (poll), resource (Plex PIN status), and context, distinguishing it from the sibling create tool.
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 establishes the prerequisite by referencing dashbrr_create_plex_pin and clarifies the success condition, implying when to use it. It lacks explicit when-not-to-use instructions or alternative tools, but the guidance is clear enough for this context.
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?
Annotations declare readOnlyHint=true, so the read-only nature is covered. The description adds that the response is paged, which is a useful behavioral detail, and gives a precondition for the instance_id. However, it doesn't mention what happens for invalid instance IDs or that the queue is limited to Radarr downloads. With annotations doing the heavy lifting on safety, a 3 is reasonable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences. First sentence states the purpose and return shape; second sentence gives the critical parameter constraint. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple interface (1 param), an output schema, and read-only annotation. The description covers the domain, the pagination behavior, and the one parameter quirk. It could mention available instance IDs, but the output schema covers return values. Good enough for a 4.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has a single required string parameter with no description, and the tool description compensates by explaining the required type prefix format with an example. This is exactly the kind of semantic enrichment needed. Schema coverage 0%, so description carries the burden, but it does so effectively.
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 identifies the tool as retrieving the Radarr download queue, with the added detail that results are paged and include movie info. This differentiates it from sibling queue tools for Sonarr, Lidarr, and Readarr.
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 doesn't explicitly name alternatives or exclusions, but it clearly implies this is for Radarr instances. The added instruction on instance_id type-prefixing gives crucial usage guidance for the only parameter. No explicit when-not-to-use, so 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint=true in annotations, the read-only behavior is already disclosed. The description adds the contextual scope of 'for the authenticated user' and clarifies what 'collapse preferences' means (which panels are collapsed), which goes beyond the annotation. No additional behavioral details are given, but the annotation covers the main safety aspect.
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 immediately communicates what is returned and for whom. There is no wasted verbiage or repetition of schema or annotation data.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, parameterless read-only tool, the description fully covers what it returns and to whom it applies. An output schema exists and can describe the structure, so the description does not need to list return fields. The combination of description, annotations, and schema is sufficient for an agent to select and invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, which warrants a baseline of 4 per the rubric. The description does not need to explain parameter semantics since there are none, and the input schema is empty.
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 returns the current UI collapse preferences for the authenticated user, specifying which dashboard panels are collapsed. The 'get' in the tool name aligns with this, and the resource (UI collapse preferences) is distinct from sibling getters that focus on other systems like autobrr, jellyfin, or plex.
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 the tool is used when you need the current collapse state for the dashboard, but it does not explicitly mention when to use it instead of alternatives. The sibling 'set_ui_preference_collapse' indicates there is a counterpart for changing the preference, but no when/when-not guidance is provided beyond the straightforward purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes safety. The description adds valuable behavioral context by specifying the exact metrics (grab/fail counts, indexer count) and the critical type-prefix requirement for instance_id. It does not disclose additional side effects, but none are expected for a read-only stats endpoint with an output schema.
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 consists of two purposeful sentences: the first front-loads the tool's output, the second details the critical input constraint. No wasted words, perfectly sized for the tool's simplicity.
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 only one parameter, an output schema, and a read-only annotation, the description covers all necessary context: what data is returned and how to properly specify the instance_id. There are no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema only defines instance_id as a string with no description, the description compensates fully by explaining that it must be 'type-prefixed' and providing a concrete example ('prowlarr-0'). This is essential information for correct invocation and adds meaning well beyond the raw 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 tool returns 'Prowlarr grab/fail counts and indexer count', specifying both the resource (Prowlarr) and the exact data. This distinguishes it from sibling tools like get_prowlarr_indexers that likely return indexer lists rather than aggregate stats.
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 the use case (retrieving Prowlarr stats) but does not explicitly state when to use this tool over alternatives or mention exclusions. The instance_id format requirement is a usage detail, but there is no explicit guidance on tool selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds meaningful context by specifying the exact return JSON structure and the parameter fallback logic. It does not cover error behavior (e.g., when no Tailscale instance exists), but for a simple read-only list tool, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every clause adds value (return format, parameter options, fallback). No filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only list tool with output schema and readOnlyHint annotations, the description covers the essential aspects: purpose, parameters, fallback, and return shape. It omits edge cases like missing configuration or error responses, but these are minor for this tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains both parameters: instance_id (a type-prefixed Tailscale instance from settings) and api_key (raw Tailscale key), and clarifies the either/or relationship with fallback. No examples or detailed format are given, but the meaning is clear.
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 identifies the resource ('Tailscale devices on the tailnet') and the operation is a get/list, implied by the tool name and the return format shown. It distinguishes unambiguously from sibling tools, which all target different services (Plex, Sonarr, Traefik, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on how to invoke the tool: pass either instance_id or api_key, with a fallback to the first Tailscale-configured instance if neither is given. It does not explicitly state when not to use it or name alternatives, but the tool's scope is self-evident from the name and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the return values (pin id and code) and the polling requirement, adding behavioral context beyond the annotations. Annotations only indicate readOnly=false and destructiveHint=true; the description explains the actual state-changing nature via authentication flow. No contradiction.
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, compact sentence conveying purpose, return values, and next steps without 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?
With no parameters and an existing output schema, the description covers the essential flow: creation, returned data, and polling handoff. It is fully sufficient for an agent to invoke and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100%, so the description is not required to provide parameter semantics. The empty schema is clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a specific action 'create a Plex PIN' and clearly identifies it as starting a Plex authentication flow. This distinguishes it from the sibling 'dashbrr_get_plex_pin' which polls the PIN.
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 states that after creation, one should poll with dashbrr_get_plex_pin until an authToken is returned, setting clear context for the tool's role in the flow. However, it does not provide explicit exclusions or alternative scenarios, though the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, and the description adds meaningful context: the boolean options (remove_from_client, blocklist, etc.) are only applied when set to true. This clarifies behavior beyond schema defaults and confirms the deletion target. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the main purpose, followed by essential parameter usage. Every sentence earns its place with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
All 6 parameters are addressed in the description, and the operation is clearly a destructive delete with options. No output schema exists, but for a delete tool the return value is typically minimal. Minor gaps like error handling are not critical here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining the semantics of `id` (queue record id from a specific endpoint), `instance_id` (type-prefixed format), and the four boolean options (only apply when true). This goes far beyond the bare 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 opens with a specific verb and resource: 'Delete an item from the Readarr download queue.' This clearly distinguishes it from sibling tools like delete_sonarr_queue_item or delete_radarr_queue_item by naming Readarr explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context by explaining how to obtain `id` (from dashbrr_get_readarr_queue) and requiring `instance_id` to be type-prefixed. It does not explicitly mention alternatives or when not to use, but the Readarr-specific wording makes the intended use unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds context about the return value ({"status": "ok"}) and clarifies the scope (instance itself vs. monitored services), which is useful. It does not disclose behavior when down, but this is minor for a simple liveness probe.
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, tightly constructed sentence that front-loads the core purpose and includes the key return detail. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless, read-only liveness probe with an output schema, the description fully covers the tool's purpose, scope, and expected output. No gaps remain for a competent agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema fully covers everything. Per rubric, a baseline of 4 applies for 0-param tools; the description adds no parameter info but none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states this is a liveness probe for the dashbrr instance itself, with a specific verb ('probe') and resource ('dashbrr instance'). It explicitly distinguishes from monitored services, aligning with sibling tools like dashbrr_check_service_health. The return payload is also specified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides an explicit exclusion ('not any monitored service'), telling the agent when not to use this tool. However, it does not name the alternative tool (e.g., dashbrr_check_service_health) for monitored service health checks, so it stops short of full alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a destructive mutation (destructiveHint: true, readOnlyHint: false). The description adds valuable behavioral constraints: the type-prefix requirement for `instance_id` ('must be type-prefixed, e.g. `overseerr-0`') and the exact status code mapping. These details go beyond the annotations and help the agent understand the expected input and operation. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is composed of three short, information-dense sentences. It leads with the primary purpose, then adds parameter details in the order they appear in the schema. Every word earns its place; there is no repetition of schema types or annotations. Perfectly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive action tool with no output schema and three required parameters, the description is nearly complete. It explains all inputs and their origins, and the annotations cover safety expectations. It stops short of describing the response format or edge cases (e.g., what happens if the request isn't pending), but this is not critical for basic invocation. Overall, the description is sufficiently complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions are completely absent (0% coverage), so the description carries full responsibility. It explicitly explains all three parameters: `instance_id` format, `request_id` provenance (from dashbrr_get_overseerr_requests), and `status` numeric mapping. This clarifies the otherwise opaque string/integer types and provides the enum-like values even though no enums are declared.
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 opens with a specific action: 'Approve or decline a pending Overseerr media request.' It clearly identifies the resource (Overseerr media request) and the verb (approve/decline), distinguishing it from sibling read-only get_* tools and delete_* tools. The rest of the description reinforces purpose by detailing the required parameters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage guidance: `request_id` comes from dashbrr_get_overseerr_requests, establishing a specific workflow. It also specifies allowed status values (`2` or `3`). While it doesn't explicitly mention alternatives or when not to use it, the sibling context and the tool's unique action make the intended use unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds value by explaining the optional url/api_key behavior and the stored-vs-unsaved distinction. It also provides the service parameter format with concrete examples, enriching the behavioral model beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main action, and each sentence earns its place—purpose then parameter semantics. No redundant phrasing or unnecessary detail.
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?
With an output schema present and a simple read-only tool, the description covers purpose, parameters, and usage modes. It doesn't need to explain return values, making it complete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully explains service as an instanceId and clarifies the conditional relationship between url and api_key (both empty vs provided). This directly compensates for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Run a health check for one configured service' with a specific verb and resource. It also specifies scope ('one configured service') and provides example instanceIds, distinguishing it from broader sibling tools like dashbrr_get_health.
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 clearly explains the two usage modes: checking a stored service or testing an unsaved one with url/api_key. It gives explicit parameter-related guidance but doesn't mention alternative tools or exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true, and the description adds context by stating 'This removes the service from the dashboard', clarifying the exact destructive effect. The prerequisite to list settings first also adds useful behavioral context beyond the annotation, though it does not detail irreversibility or 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 two sentences, front-loaded with the purpose, then adds the parameter detail and prerequisite. Every sentence serves a purpose with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter destructive tool with annotations already declaring destructive behavior, the description provides the necessary action, parameter semantics, and a safety prerequisite. No output schema is present, so return values need not be detailed. The tool is fully understandable and actionable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines 'instance' as a string with no description, so the description carries the full burden. It explains that 'instance' is the type-prefixed instanceId and gives the example 'sonarr-1', fully compensating for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Delete a service configuration from the dashbrr instance' with a specific verb and resource. It distinguishes from sibling tools like dashbrr_delete_sonarr_queue_item by specifying service configuration, and provides the instance format example.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a clear prerequisite: 'use dashbrr_list_settings first'. This gives explicit when-to-use guidance for discovering valid instance IDs. However, it does not explicitly mention when not to use the tool or alternatives (e.g., using dashbrr_save_settings for modifications), so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already flag this as destructive and not read-only. The description adds valuable context by explaining that options are applied only when set to true and detailing the effect of each flag (e.g., remove_from_client, blocklist). It does not discuss all consequences, but together with annotations it sufficiently discloses behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three focused sentences, with the main action first, then prerequisites, then option explanations. No unnecessary information; the description is efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 6-parameter destructive tool with no output schema and no schema descriptions, this description covers all parameters, provides usage prerequisites, and explains option behavior. It is sufficiently complete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates fully by defining `id`, `instance_id`, and all four boolean flags, including their semantics. Every parameter from the schema is explained, making the parameter set unambiguous.
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 an item from the Sonarr download queue, using a specific verb and resource. It distinguishes from sibling tools like dashbrr_delete_radarr_queue_item by naming Sonarr explicitly.
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 specifies that `id` comes from dashbrr_get_sonarr_queue and that `instance_id` must be type-prefixed (e.g., sonarr-1), providing clear context for when and how to use it. It does not explicitly contrast with sibling delete tools, but the name and prerequisite make appropriate usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, already indicating a safe read operation. The description adds valuable context by disclosing that API keys are stripped from the response and that the response is keyed by instanceId. This goes beyond the basic annotation while remaining appropriate for a simple list tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each serving a distinct purpose: listing the action, noting the security behavior, and giving a usage pointer. No redundant or filler content; the description is front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only tool with an output schema present, the description covers the core behavior (list all services), the keying convention, a security disclosure, and a clear link to sibling tools. Nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is trivially 100%. The description adds value by explaining the output key structure (instanceId examples), which helps the agent understand the response even though the schema has no parameters to document.
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 the specific verb 'List' with the resource 'every configured service' and clearly states the response is keyed by instanceId with examples. This distinguishes it from the many per-service sibling tools (e.g., dashbrr_get_sonarr_stats) that query individual services.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs the agent to 'Use the instanceId keys here as the instance_id argument to the per-service tools,' establishing this as a discovery/prerequisite step. This provides clear when-to-use guidance and implicitly explains when not to use it (for specific service data).
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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