Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral disclosure burden. It transparently states the actions: audits, flags failures/bans, and reports system health warnings. This conveys a read-only monitoring operation and makes side effects (or lack thereof) reasonably clear. No contradiction exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, well-structured sentence that leads with the action verb 'Audits' and packs all relevant details without redundancy. Every word earns its place; there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter tool with no output schema, the description fully covers what the tool does and what it reports. An agent has everything needed to invoke and interpret the result. No gaps that would hinder correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema is empty (100% coverage). The description adds meaning by explaining the tool's purpose, but since there are no parameters to document, the baseline of 4 applies. Nothing more is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Audits'), a specific resource ('Usenet indexers and torrent trackers configured in Prowlarr'), and a precise outcome (flag connection failures/bans, report health warnings). This clearly distinguishes it from siblings like get_cluster_infrastructure_health, which targets a broader infrastructure scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context: this tool is for auditing indexer/tracker connectivity in Prowlarr. It does not explicitly name alternatives or when-not conditions, but the context is specific enough that an agent can infer when to use it. Lacks the explicit routing that a 5 would require.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must carry the behavioral burden. It conveys a read-only check and names the output (monitoring status and artwork), but it does not describe behavior when the movie is absent, error conditions, or explicitly confirm no side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that states the action, resource, and output with no filler or redundancy. Every phrase earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description should clarify the return contract more fully. It says monitoring status and artwork are returned, but not what the output looks like when the movie is not found or how 'monitoring status' is represented. This is adequate but has clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the parameter is already documented as 'The exact title of the movie to search for.' The description adds context about the Radarr library but does not meaningfully enrich the title parameter beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific action ('Checks if a specific movie exists'), a concrete resource ('Radarr library on the Ubuntu cluster'), and a distinct outcome ('returns its monitoring status with artwork'). This clearly differentiates it from siblings like search_and_select_movies or diagnose_missing_media.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The intended use is implied: call it when you need to verify a movie's presence and monitoring status. However, the description never explicitly says when to prefer this tool over siblings, nor does it mention alternatives or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it discloses key behaviors: adding monitored movies, starting download searches, avoiding duplicate additions, and default quality profile/root folder fallbacks. It could go further by describing result reporting format, but the core side effects are transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences cover the main action, duplicate handling, and defaulting logic without waste. The most important purpose 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is largely complete for a mutating workflow tool: it explains what happens, the dependency on a prior search grid, and fallback defaults. It does not describe the output/report format, and with no output schema this is a minor gap, but the essential invocation context is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds meaning beyond the schema by explaining the fallback order for qualityProfile and the default rootFolder behavior. It also ties chosenIndexes to the user's numbered selections from the search grid.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Adds the user's numbered choices... to Radarr as monitored movies and starts a download search for each.' This clearly distinguishes it from siblings like search_and_select_movies and check_movie_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Establishes clear context by referencing 'the last search_and_select_movies grid,' indicating this is a follow-up to that specific sibling tool. It does not explicitly state exclusions or alternatives, but the workflow context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It discloses that the tool reads multiple sources (metadata, history, download client queues) and produces a diagnosis, which is useful. However, it doesn't disclose whether the tool performs any mutations (e.g., triggering searches, changing statuses), what the output format is, or whether it can take actions beyond diagnosis. The word 'Traces' suggests read-only, but that is not explicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, front-loaded with the action and resources, no filler. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter diagnostic tool, the description is mostly complete. However, with no annotations and no output schema, an agent doesn't know whether the tool is read-only or may trigger actions, nor what the diagnosis result looks like. Given the tool's complexity (tracing through multiple systems), a bit more context about side effects or output would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the only parameter 'title' is described as 'The title of the media to diagnose.' The description adds the context that the title refers to a movie, which is slightly more specific than the schema's 'media.' This is a minor addition; the schema already carries the meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Traces') and names the exact resources it inspects (Radarr metadata, history, active download client queues) and the goal (pinpoint why a movie is missing). This clearly distinguishes it from siblings like check_movie_status or manage_stalled_downloads.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a diagnostic use case: when a movie is missing and the cause is unknown. It doesn't explicitly name alternatives or when-not-to-use, but the context of tracing through multiple sources makes the intended scenario clear. A small gap is not stating when to prefer check_movie_status or manage_stalled_downloads instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the disclosure burden. It usefully discloses that exactly one sequential block item is processed, that the job must be active, and that auto-advance already occurs. But it does not mention side effects on job state, error conditions, reversibility, or what happens when no steps remain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The first sentence front-loads the action and purpose; the second adds relevant automatic-advancement context. Appropriately sized for a single-parameter tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple one-parameter tool, but with no annotations and no output schema, the description must do more. It explains what and why, but omits return/outcome details and side-effect behavior, leaving the agent with only partial context for a mutating action.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully describes jobId as the unique tracking ID of the active job array, so the baseline is 3. The description adds some contextual language around 'active' and 'block item' but does not materially extend the parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States precise behavior: processes a single sequential block item from an active background batch queue entry, with a clear rationale (prevent API flooding). This is specific enough to distinguish it from sibling read/manage tools like get_background_jobs and update_job_status, even without naming them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than explicit: the description suggests manual stepping exists to prevent API flooding, and notes that started jobs also auto-advance one item per minute. However, it does not state when not to use this tool or name an alternative explicitly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden, but it does not disclose behaviors like whether this is read-only (it implies retrieval, so likely safe), how results are ordered, or if there are any side effects. The description is clear about the action (retrieves) but lacks depth on return format or filtering, though the tool has no parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the verb and resource, with no wasted words. It is appropriately sized for a simple tool with no parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters and no output schema, the description is nearly complete. It specifies what it retrieves (jobs) and their states, but could mention whether it returns a list or counts, though without an output schema, the description does enough to guide basic usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, and the description covers the full schema (100% coverage with no properties). The description clarifies the scope (server cluster) and job states, adding meaning beyond the empty schema, which justifies a score above the baseline for no params.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves media processing jobs, specifying the job states (active, pending, completed) and the resource (persistent media processing jobs on the server cluster). It distinguishes from siblings like get_plex_activity or get_library_analytics, though it does not explicitly name them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool—when you need to check on media processing jobs—but does not explicitly contrast with siblings like update_job_status or execute_next_job_step. No exclusions or alternative conditions are stated, but the context is clear enough for most agents.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that the tool connects over SSH and returns a Markdown table, which is useful. However, it does not mention potential side effects, authentication requirements, latency implications, or what happens if SSH fails. The description is honest but incomplete on behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the core purpose (real-time CPU load and memory allocation), specifies the scope (every configured cluster host), the method (over SSH), and the output format (Markdown table). Every element earns its place with zero waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no output schema, the description covers the main purpose and output format. However, it lacks context about failure modes, authentication prerequisites, or how this relates to sibling tools like get_cluster_infrastructure_health. An agent might not know when to prefer this over the infrastructure health tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema provides no parameter semantics to cover. The description compensates by explaining what data is fetched and how it is presented. With no parameters, the baseline is 4, and the description adds meaningful context about the tool's behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches real-time CPU load and memory allocation for every configured cluster host over SSH, and specifies the output format as a Markdown table. This is a specific verb+resource combination that distinguishes it from siblings like get_cluster_infrastructure_health, which likely covers broader health metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context (real-time hardware monitoring for cluster hosts) but does not explicitly state when to use this tool versus alternatives like get_cluster_infrastructure_health. There is no mention of when not to use it or what conditions would make a sibling tool more appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral disclosure burden. It does disclose that data is real-time, scoped to all configured Ubuntu hosts, and limited to CPU, RAM, and Docker container counts. It does not explicitly state whether the operation is read-only, describe potential side effects, error conditions, or output shape, so some behavioral detail is still missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single well-structured sentence conveys the action, the data collected, and the scope. Every word contributes meaning, and the most important information is front-loaded. No filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-style monitoring tool, the description is largely complete: it names the exact metrics and host scope. The main gap is the lack of explicit return-format or usage-context details, but the low complexity of this tool means an agent can reasonably infer how to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so per the rubric the baseline is 4. The description appropriately focuses on what data is collected rather than parameter details, since there is no input schema to clarify.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Collects') and a specific resource ('cluster infrastructure health') with concrete metrics: CPU utilization, RAM usage, and active Docker container counts. It is clear and likely distinguishable from get_cluster_hardware_analytics, though it does not explicitly name the sibling or draw the contrast.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage: call this when you need real-time resource metrics across the Ubuntu hosts. However, it provides no explicit guidance about when to prefer this tool over related siblings like get_cluster_hardware_analytics or check_indexer_health, and no exclusions or alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden. It indicates a read-only operation via 'Queries' and clarifies the data is historical aggregate statistics, but it does not disclose output structure, pagination, or authorization requirements. It is adequate for a simple query tool but leaves behavioral details unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler. Every clause contributes specific metrics or scope, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter analytics query with no output schema, the description gives the main return categories and scope, which is reasonably complete. It could specify the time window or output format, but the low complexity makes the current description sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters and 100% description coverage, and the tool takes no arguments. Per the 0-parameter baseline, this is a 4; there is no parameter semantics for the description to add.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Queries') and names the resource ('historical statistics') with concrete content examples: most watched movies, total user count, and overall watch metrics. It is clear and distinguishes itself from siblings like get_cluster_hardware_analytics by subject matter, though it does not explicitly contrast with any sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when historical library analytics are needed, but it provides no explicit when-to-use or when-not-to-use guidance and does not mention alternatives such as get_plex_activity or get_cluster_hardware_analytics. The context is understandable, but the guidance is indirect.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It states the tool 'fetches' data, implying a read operation, but does not explicitly say it is read-only, mention any side effects, rate limits, authentication requirements, or what happens if Tautulli is unavailable. It also doesn't clarify the output structure or that it returns current sessions only. This leaves significant gaps for an agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the primary action and purpose without any redundant filler. Every phrase adds value, and it is appropriately concise for a simple parameterless tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and no output schema, the description is the sole source of context about the return value and limitations. It says it fetches 'analytics' but does not describe the shape of the response (e.g., list of active sessions, per-user details). For an agent to know what to do with the result, more detail on the return would be helpful. Still, the tool is simple enough that the current description is minimally viable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the schema is empty. Per the rubric, 0 parameters sets a baseline of 4. The description adds no parameter information (since there are none), and no compensation is needed because the schema already fully covers the parameter surface.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Fetches'), names a clear resource ('real-time playback streaming analytics from Plex via Tautulli'), and states the purpose ('to monitor user context and transcoding strain'). This distinguishes it from siblings like get_library_analytics, which focus on broader analytics, and check_movie_status, which checks individual titles.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning the monitoring purpose, but it does not explicitly state when to use this tool over alternatives or provide exclusions. No mention of siblings or conditions like 'use this for live streams, use get_library_analytics for historical data'. The purpose gives some context but falls short of clear guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral disclosure burden; it does indicate the tool changes download state (isolate, pause, blocklist) rather than being read-only. However, it omits the destructive PURGE_STALLED side effect and the re-search flag, and gives no indication of reversibility or permissions; the schema's action descriptions partially compensate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence names the resource, the defect condition, and the possible actions with no filler. Every phrase earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter tool with a rich schema, the definition is mostly adequate, but there is no output schema and no annotation-level safety information. The description does not specify what AUDIT returns in practice or the full effects of PURGE_STALLED beyond the schema, so an agent has to rely on enum descriptions for side effects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3; the action enum and minSpeedKbps descriptions are already explicit. The description adds only the 'below threshold' concept, which loosely maps to minSpeedKbps but adds no syntax or format detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: scans qBittorrent download queues and targets stalled items below a speed threshold. It is clear about the domain and intent, though it does not explicitly distinguish itself from siblings and its 'pause or blocklist' wording does not fully match the AUDIT/PURGE_STALLED action enum.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The qBittorrent queue context and below-threshold condition imply when to use it, but there is no explicit when-to-use or when-not-to-use guidance, nor any named alternative. An agent must infer that this is for stalled-download management rather than being told.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'safely' and 'enforcing storage policies,' but does not clarify whether this tool mutates state by creating a persisted schedule, whether it is read-only, what its failure modes are, or whether it actually executes any upgrades.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, tightly written sentence with no filler. It front-loads the primary action and includes constraints like 'controlled' and 'enforcing storage policies' without wasting words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema and no annotations, yet the description does not explain what the tool returns, whether a schedule is persisted, or how this planning step relates to execution siblings. An agent would still lack critical information needed to safely invoke and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are already documented. The description adds loose context with 'specified media classes' and 'batch,' which roughly map to mediaType and maxBatchSize, but it does not meaningfully extend parameter semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Evaluates and safely schedules a controlled batch upgrade for specified media classes.' It clearly distinguishes itself from execution-focused siblings by emphasizing planning and scheduling rather than executing, and from status tools by naming the upgrade action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrasing implies this should be used when a batch upgrade needs to be planned and validated against storage policies before execution. However, it does not explicitly state when to use this tool versus alternatives like execute_next_job_step or update_job_status, leaving the selection logic mostly to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by revealing the external TMDb source, the filtering of talk shows/self-appearances/uncredited roles, and the conditional Plex ownership marking. It does not cover edge cases like unknown actor names or what happens when Plex is not configured, but the core behavior is honestly and usefully described.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences accomplish a lot: the first states the operation, source, and filters, and the second adds the Plex-dependent output and the intended use case. There is no repetition, filler, or unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has six parameters, 100% schema coverage, no annotations, and no output schema, the description provides enough context for normal use: what the tool returns conceptually, what it filters, and when Plex data is included. It could add more edge-case transparency, but nothing essential is missing for selecting and invoking the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains all six parameters, including enums, defaults, ranges, and the subsetting behavior of 'show'. The description adds only a general link to actorName and the owned/missing idea, not much additional meaning. Baseline 3 is appropriate because the description does not need to compensate for schema gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('resolves') and a clear resource ('actor's name to their official TMDb filmography'), then adds concrete scope by naming what is filtered out. The mention of marking Plex ownership and answering which movies the user is missing distinguishes it clearly from sibling tools like search_plex_library or check_movie_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this to answer which of an actor's movies the user is missing,' which gives a direct use case. It also conditions the Plex ownership behavior on Plex being configured. However, it does not name alternative tools or state when not to use it, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are absent, so the description carries the whole burden. It discloses that it waits for completion, verifies a new backup file, reports file metadata, leaves backups inside app folders, and copies nothing. It does not mention failure modes or authorization requirements, but the core behavior is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The action is front-loaded, the waiting behavior is clarified, and the non-copying boundary is stated at the end. Every sentence contributes useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-input, no-output-schema tool, this description is complete: it states target apps, action, synchonization behavior, verification step, return details, and side-effect boundary. No important invocation information appears to be missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema already covers everything. The description adds useful context by defining the scope ('each configured Servarr app'), and no parameter clarification is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('asks... to create'), the resource ('built-in database backup' for each Servarr app), and the observable outcome (waiting, confirming, reporting file name/size/time). This clearly distinguishes it from siblings like manage_stalled_downloads or get_plex_activity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit alternative or 'use instead' guidance, but the context is unmistakable: use when you need each configured Servarr app to create a database backup and verify it. No sibling tool appears to compete for the same operation, so missing exclusions is a minor gap, not a critical one.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It discloses a key behavior: rendering a Markdown multi-choice grid for confirmation, which goes beyond a simple search. However, it does not mention potential side effects, user interaction flow, or whether it blocks pending confirmation. This is adequate but not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, efficient sentence that front-loads the primary action ('Searches TMDb') and follows with the output behavior. No wasted words; every phrase contributes meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 no output schema, the description is complete enough to understand its purpose and behavior. It explains the search and the confirmation grid. It does not detail what happens after confirmation, but this is a minor gap given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides 100% coverage for the only parameter (query), including a description and example. The tool description adds no further semantics about the parameter beyond restating the search action, so it meets the baseline without extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: searching TMDb for movies, and the specific output: a Markdown multi-choice grid for confirmation. It distinguishes this tool from siblings like check_movie_status or get_plex_activity by its search-and-select nature.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 to search for a movie and let the user confirm a selection, but it does not explicitly contrast it with alternatives or state when not to use it. No explicit exclusions or comparisons are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations present, the description carries the full burden. It discloses that the results table shown to the user exactly matches the return, the default limit is small, and that pagination may require follow-up calls—context beyond the schema. It doesn't mention authentication or rate limits, but those may be less critical; still, it adds valuable operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized with front-loaded purpose and usage, followed by practical tips. It uses clear examples and covers edge cases (default limit, pagination) without unnecessary fluff. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with 7 optional params and no output schema, the description is remarkably complete. It explains filtering, combination, limits, pagination, and the exact relation to the displayed results. Everything an agent needs to use it effectively is covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each parameter is already documented with descriptions (year, actor, genre, limit, title, offset, library). The description reinforces filter combination and library semantics (e.g., '4k') but doesn't add much beyond schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches the user's actual Plex library by multiple filters (genre, actor, title, year, library) and explicitly differentiates it from sibling tools like check_movie_status. It specifies what it answers ('what the user owns or can watch'), making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit when-to-use guidance ('Use this to answer what the user owns or can watch') and when-not-to-use ('use check_movie_status for Radarr/download status'), naming the alternative. It also provides detailed operational instructions on how to express user requests as filters and how to handle pagination with limit and offset.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It indicates the tool mutates job state, but does not disclose potential side effects (e.g., whether CANCEL is irreversibly destructive, or whether PAUSE/RESUME have any queuing effects). It also doesn't mention any permissions or whether actions are reversible. For a mutation tool, this is a moderate gap, but the action enum provides some clarity for the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that is front-loaded with the purpose. It avoids fluff and is easy to scan, which is ideal for an agent's prompt context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-parameter tool with a clear schema, the description is mostly sufficient. However, given no annotations and no output schema, it could benefit from stating the expected response (e.g., success/failure indicators) or any constraints (e.g., actions only on active/pending jobs). The description is adequate but leaves some behavioral context unclear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of parameters with descriptions for jobId and action, including an enum for action. The description adds minimal extra meaning beyond the schema—it just restates that these actions operate on operational state. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Updates the operational state of an active or pending background batch job.' It specifies a verb (updates), a resource (operational state of a job), and the scope (active or pending). It distinguishes from siblings like get_background_jobs (which likely reads) but does not explicitly differentiate from other update tools like execute_next_job_step or manage_stalled_downloads, though the specific action set (PAUSE/RESUME/CANCEL) is implied.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly indicates usage: to change the state of an active or pending job, not for completed jobs. It does not explicitly state when to use this tool versus alternatives like execute_next_job_step (which might advance a job) or manage_stalled_downloads (which might handle stalled jobs). No explicit exclusions or alternative routing is provided, so guidance is adequate but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.