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

Annotations are absent, so the description carries full responsibility. 'Evaluate' implies a read-only analysis operation, providing some transparency, but it does not disclose behavior such as whether it uses synced data, how optional filters like league_id/roster_id affect results, or whether any state changes occur. The analysis nature is inferable but not fully elaborated.

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 immediately states the action and subject. Every word earns its place, with 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?

Even though an output schema exists, the description is minimal for a 4-parameter tool. It lacks any guidance on how to use the parameters, what 'current waivers' means in practice, or how this tool fits into a larger workflow. The high-level purpose is clear, but important operational context is 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?

Schema description coverage is 0%, and the description does not mention any of the four parameters (week, limit, league_id, roster_id). There is no explanation of the required week, the default limit, or how the optional filter parameters scope the analysis. The description fails to compensate for the undocumented 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 'Evaluate' with a clear resource 'current waivers' and specifies three analysis aspects (add/drop pairs, FAAB ranges, expected competition). It distinguishes itself from sibling tools like recommend_draft_pick or optimize_lineup by focusing specifically on waiver analysis.

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?

No explicit when-to-use guidance or alternatives are mentioned. The phrase 'current waivers' implies context, but it doesn't state when to prefer this tool over other analysis/recommendation tools, nor does it mention prerequisites like having synced league data or a specific week.

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. It discloses a behavioral trait ('without hiding their components') meaning the output will include component values, but it does not mention side effects, permissions, or any safety profile. For a read-only comparison tool, 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.

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

One concise, front-loaded sentence with no filler. Every word contributes to meaning: 'Compare,' 'same-horizon,' 'league-scoring,' 'without hiding components.' Excellent structure.

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?

An output schema exists, so return values are covered, but the description fails to explain required parameters or usage context. With 4 parameters, no annotations, and zero schema description coverage, the description is incomplete for effective tool selection and invocation.

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 0%, and the description does not mention any of the 4 parameters (player_ids, horizon, league_id, roster_id). No meaning is added beyond the raw schema, so parameter semantics are completely unexplained.

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?

Description states a specific action ('Compare') with a clear resource ('same-horizon league-scoring values') and adds a distinguishing qualifier ('without hiding their components'). This differentiates it from sibling tools that might compare values over time or provide summaries.

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 phrase 'same-horizon' implies when to use this tool (comparing players at a specific time horizon), but it gives no explicit when-not guidance or mentions alternatives. This is implied usage, not explicit direction.

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 of behavioral disclosure. It explicitly states a behavioral trait ('without inventing acceptance odds'), which is valuable context about what the tool will not do. However, it does not mention side effects, data requirements, or limitations beyond that single constraint.

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, well-structured sentence with no waste. It front-loads the purpose and includes a negative constraint, making it concise and scannable.

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?

Despite having an output schema and no required parameters, the description is thin for a tool that likely depends on league context and horizon. It does not explain how to set up inputs, when data is ready, or what 'plausible' means. More guidance is needed for an agent to invoke 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 0% and the description provides no explanation of the 4 parameters (limit, horizon, league_id, roster_id). Horizon is particularly ambiguous and would need clarification. The description completely fails to compensate for the lack of schema descriptions.

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

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

Description clearly states a specific action ('Find plausible one-for-one roster-fit trades') and includes a key differentiator ('without inventing acceptance odds'), which distinguishes it from sibling tools like record_trade_offer that record trades rather than find 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 usage (to find trade opportunities) but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among the many siblings. The context is clear but exclusions are absent.

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 convey behavioral traits. It notes the data source ('prospectively recorded outcomes'), which adds context, but does not specify side effects (e.g., read-only), output format, or any potential rate limits. The 'Report' verb implies a read operation, but this 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, and free of fluff. It precisely states the tool's function without redundant details.

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 is simple (one optional param, output schema exists), so the description could suffice, but it lacks usage context and does not clarify what 'prospectively recorded outcomes' means or how to interpret the metrics. Overall adequate but missing guidance for an agent unfamiliar with the domain.

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 sole parameter 'league_id' is not mentioned in the description, and schema description coverage is 0%. The schema provides name, type, nullable, and default, but the description adds no meaning about how league_id affects the report (e.g., filtering scoping). The parameter name is self-explanatory but the lack of description force the agent to guess.

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 ('Report') and resource ('Brier/absolute-error metrics'), clearly stating the tool's output. It distinguishes this tool from siblings like sync or analysis tools, as calibration metrics are unique among 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?

No explicit guidance on when to use this tool vs. alternatives. It does not mention typical use cases, exclusions, or related tools. Usage is only implied by the description, leaving the agent to infer when a calibration report is needed.

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. The word 'immutable' usefully implies a read-only, historical view. However, it doesn't disclose parameter behavior, authentication needs, pagination, or error scenarios. For a simple getter, this is moderate but incomplete transparency.

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 sentence that is front-loaded and contains no filler. It states the action and result clearly, making it concise and well-structured for its length.

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?

With two parameters and an output schema, the description should explain parameter semantics and use context. It does neither, leaving the agent without enough information to decide when to invoke this tool or how to set parameters 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 0%, and the description does not mention 'limit' or 'league_id' at all. The agent must infer meaning purely from parameter names, which is insufficient. The description fails to compensate for the lack of schema documentation.

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 clear verb ('Return') and resource ('decision history'), and specifies the content ('recommendation inputs, alternatives, actions, and outcomes'). This distinguishes it from sibling tools that record or recommend decisions, though it doesn't explicitly contrast with similar retrieval tools like get_calibration_report.

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 guidance on when to use this tool versus alternatives. It doesn't mention that it's for viewing historical records, nor does it provide exclusions or contextual hints. The description is purely functional and lacks any usage direction.

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 of behavioral disclosure. It only lists returned data and does not state whether the operation is read-only, has side effects, or requires specific permissions. The absence of such details is a gap for a tool with optional 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 tool's primary purpose. Every word contributes meaning, with no redundancy or 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?

The presence of an output schema covers return values, but the description lacks clarity on input configuration—specifically, how draft_id and league_id relate and what happens when no parameters are provided. Given three optional parameters, this is a notable omission for a tool designed to fetch draft state.

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 0%, so the description must compensate for all parameters. It only mentions an 'optional roster' (mapping to roster_id), but fails to explain the roles of draft_id and league_id or how they relate. This leaves the selection of draft context ambiguous and provides little value beyond the schema's bare parameter names.

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 the specific verb 'Get' and clearly identifies the resource as draft state, enumerating specific components (settings, picks, next-pick context, roster's local queue). This distinguishes it from sibling tools like get_roster_state and get_season_context, which target different aspects.

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 for retrieving draft-related information, providing clear context of what the tool returns. However, it does not explicitly contrast with alternatives or state exclusions, so it stops short of full 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 full burden for behavioral disclosure. It says 'Get' implying a read-only operation, and 'local' suggests cached data, but it never explicitly confirms that this does not trigger a sync, nor does it explain what 'sync provenance' includes. Important behavioral traits (e.g., whether the league must be initialized first, whether this is safe) are absent.

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 one concise sentence with no filler. It quickly enumerates the data categories returned. It loses one point because 'sync provenance' is a slightly unclear term that could be expanded, but overall the length is appropriate.

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?

Although an output schema exists (which can document return structure), the description lacks necessary context about the tool's role in a broader workflow. It does not clarify what 'local' means relative to sync tools, when this should be called, or how it relates to the many sibling tools. This is a minimal description that assumes prior knowledge.

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 one optional parameter (league_id) with zero description coverage. The description does not mention league_id at all, so the agent has no indication of what it means, what values are valid, or what happens when it is null or omitted. This is a complete gap.

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 ('Get') and names a concrete resource: 'current local league format, rosters, managers, and sync provenance.' It clearly states what the tool returns, and those categories distinguish it from siblings like get_sync_status or get_draft_state. However, it does not explicitly contrast with alternative tools, so it stops short of a 5.

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 no guidance on when to use this tool versus alternatives such as sync_league, get_season_context, or get_sync_status. There is no statement of prerequisites, exclusions, or recommended scenarios. The agent is left without contextual direction.

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 adds value by stating the output is 'uncertainty-labeled' and sourced from 'retained history', and 'Return' implies read-only. However, it does not disclose potential side effects, permissions, or how the uncertainty labels are generated.

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 communicates the key concept without redundant words. It is appropriately concise for a simple read-only getter.

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?

Despite having an output schema, the description fails to explain how the two optional parameters identify a specific manager. Without parameter guidance, the agent cannot confidently construct a valid request, and the description lacks necessary invocation context.

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 0% and the description does not mention league_id or roster_id at all. The agent cannot infer how to populate these parameters or whether they are required contextually, making invocation ambiguous.

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 'Return' with a clear resource 'manager behavior', and adds distinctive modifiers 'descriptive, uncertainty-labeled' and source 'retained history'. This clearly distinguishes it from sibling tools like get_roster_state or get_player_context, which target different data.

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 provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. Among over 30 sibling tools, the agent receives no contextual hints for selecting this specific tool.

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 disclosing behavior. It states what data is returned, implying a read operation, but does not mention side effects, data freshness, error states, or any restrictions. The list of return types provides some transparency, but not enough for a fully informed decision.

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 directly conveys the core functionality. It contains no filler or redundant information, making it highly concise and well-structured.

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's simplicity and the presence of an output schema, the description covers the essential return components. However, the lack of usage guidance and parameter clarification means it is not fully complete, but it is adequate for a straightforward context retrieval 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 schema has 0% description coverage, and the description does not elaborate on the player_id parameter. While it says 'for a player', it does not specify the expected ID format, source, or any mapping nuances (e.g., how to obtain a valid player_id). The description fails to compensate for the bare 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 clearly states the tool returns player context comprising specific data types (projections, market inputs, injuries, news). It uses the verb 'Return' and identifies the resource (player context), which distinguishes it from sibling tools like get_league_overview or get_season_context.

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 for retrieving comprehensive player-level data, which is distinct from league-level or sync-focused sibling tools. However, it does not explicitly state when to use it over alternatives or provide exclusion criteria, so it lacks explicit 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 provided, the description carries the full burden of behavioral disclosure. 'Inspect' implies a read-only operation but does not explicitly state safety, side effects, or what happens with unresolved identities (e.g., does it resolve them automatically?). No information about auth, rate limits, or return behavior is provided, leaving the agent to infer critical operational details.

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

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

The description is a single concise sentence with no wasted words. It is front-loaded with the action verb and resources. However, it is arguably too terse, omitting critical context that would make it more useful, but the conciseness itself is appropriate for the tool's simplicity.

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 status-inspection tool with a single optional parameter and no annotations, the description is minimal. An output schema exists, so return values need not be detailed, but the lack of parameter explanation and lack of differentiation from get_sync_status leaves the description incomplete for an agent to understand when and how to use it 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?

The input schema shows one optional parameter (league_id) with no description, and the schema description coverage is 0%. The description fails to mention league_id at all, leaving the agent to guess its purpose and formatting. With zero schema coverage, the description must compensate but does not, making parameter semantics entirely unclear.

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 specifies the verb 'Inspect' and the resources 'provider synchronizations' and 'unresolved player identities', which clearly identifies the tool's focus. It distinguishes from sibling sync tools (e.g., sync_league, sync_fantasypros) by targeting status inspection rather than performing operations, though 'get_sync_status' is a close cousin and no explicit differentiation is made.

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 provides no guidance on when to use this tool compared to alternatives, such as get_sync_status or the various sync_* tools. There is no mention of prerequisites, typical use cases, or exclusions. The single sentence is purely descriptive of what it does, not when to invoke it.

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 bears the full burden of disclosing side effects, permissions, or computational behavior. It states only that it returns data, without mentioning whether it is a read-only operation, if any state is modified, or if there are rate limits. This is a minimal disclosure.

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 directly states the tool's purpose with no unnecessary words. It is appropriately concise and front-loaded.

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?

While an output schema exists (so return values may be defined), the description is still incomplete: it omits any parameter semantics, usage context, or behavioral notes, making it insufficient for correct invocation. The required 'horizon' parameter is unexplained.

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 0% description coverage across all three parameters (horizon, league_id, roster_id), and the description does not explain any of them. With low schema coverage, the description was expected to compensate but instead adds no parameter 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 clearly states the tool returns value-aware roster depth, positional fragility, and injury risk, using a specific verb and resource. It distinguishes the tool from siblings like get_draft_state or get_league_overview by focusing on roster-specific analysis.

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 provides no guidance on when to use this tool versus alternatives, no exclusions, and no context for selecting it over sibling tools. An agent would have to infer usage from the name alone.

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

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

As a 'Get' tool it implies a non-mutating read, and the word 'persisted' adds useful context that this accesses stored defaults rather than live data. However, with no annotations provided, the description could still disclose behavior for missing data or null season, though for a simple getter 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.

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

The description is a single, front-loaded sentence with no filler or redundancy. Every word adds meaning, making it highly concise and well-structured.

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?

An output schema exists, so return structure is likely covered. The description states what resource is accessed, but it omits usage guidance and parameter semantics, making it minimally complete for a tool with no annotations.

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 has one optional 'season' parameter with 0% description coverage, and the tool description never mentions it or explains how null is interpreted (e.g., current season vs no filter). The parameter name is self-explanatory, but the description adds no value 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 ('Get') and names concrete resources (Sleeper user, league, roster, draft defaults), which distinguishes it from sibling getters like get_league_overview or get_draft_state by the 'persisted defaults' qualifier. However, 'defaults' is somewhat vague and it does not explicitly contrast with live-data or sync tools.

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 guidance on when to use this tool versus alternatives. It does not mention whether it should be called before sync/initialization, whether it is a read-only fallback, or what scenarios would favor a sibling tool 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?

With no annotations, the description carries the full burden. The verb 'Inspect' suggests a read-only operation, but the description does not explicitly state 'does not modify data.' It adds value by mentioning 'retained projection failures,' but it does not disclose pagination behavior, what 'recent' means, or how league_id filtering works.

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 with no wasted words. It uses an action verb and clearly names the resources, making it easy to parse and mentally model the tool's function.

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 is relatively simple with only two optional parameters and an output schema, but the description omits parameter semantics and usage context. It provides only a high-level gist, leaving the agent uncertain about how to correctly invoke the tool (e.g., what limit and league_id do). This is incomplete for ensuring 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?

Schema coverage is 0%, and the description does not explain the two parameters (limit and league_id). It fails to clarify whether 'limit' applies to number of sync records, failures, or both, and what 'league_id' filters. This is a significant gap for a tool with no parameter descriptions in 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 clearly states the tool's purpose with a specific verb ('Inspect') and resource ('recent season/draft synchronizations and retained projection failures'). It distinguishes itself from sibling sync tools like sync_league and sync_draft by focusing on status inspection rather than performing a sync.

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 for checking sync status, but it does not provide explicit when-to-use guidance or mention alternative tools. It lacks exclusions like 'use this after a sync to verify success' or 'alternatively, use get_provider_status for provider-level info.'

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?

There are no annotations, so the description must disclose behavioral traits, but it only offers a general 'screen' action that implies read-only intent. It does not mention side effects, permissions, rate limits, return format, or any other behavioral details, leaving the agent without crucial operational context.

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 and wastes no words. It is efficient in structure, though the brevity sacrifices content depth, which is a separate issue from structural conciseness.

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 four parameters, two required, and no annotations, this description is inadequate. It does not describe the output, filtering behavior, or parameter semantics, despite having an output schema that could be referenced. The description is not complete enough for an agent to invoke the tool correctly without additional investigation.

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?

With 0% schema description coverage, the description alone is responsible for clarifying parameters. It hints at the 'since' parameter via 'since a timestamp' but fails to explain 'horizon', 'limit', or 'league_id', leaving the meaning and usage of these parameters entirely ambiguous.

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 a specific action ('Screen') and target ('projection, market, trend, or contextual changes since a timestamp'), conveying the tool's purpose well. However, it does not explicitly differentiate from sibling tools that also involve data retrieval or analysis, missing the chance to clarify its unique 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 provides no guidance on when to use this tool versus alternatives like get_season_context or get_player_context. It only states what the tool does, without any context on appropriate invocation scenarios, exclusions, or prerequisites.

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 full responsibility. It only mentions the pipeline but does not disclose side effects, idempotency, or error handling.

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?

Single sentence, no fluff, front-loaded with the verb and object. Efficient.

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?

Despite 8 parameters and no annotations, the description provides only a high-level statement. It is far from complete for a complex import operation.

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?

With 0% schema description coverage, the description should explain key parameters, but it only references 'provider export' generically. No parameter semantics for provider, payload, document_kind, source_key, etc.

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 identifies the action ('Import'), the resource ('provider export'), and the destination ('same raw-first pipeline'). This distinguishes it from sibling sync and query tools, though it does not explicitly name alternatives.

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?

No guidance on when to use this tool versus the many sync_* tools. The description doesn't state scenarios 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?

It discloses that selection is automatic, persistent, and returns choices without guessing. However, it does not mention potential side effects like overwriting context, required configuration, or failure modes. With no annotations, this is a moderate disclosure.

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 two sentences in the main paragraph plus a behavioral note, efficiently front-loaded with the core purpose. No redundant 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?

The tool has an output schema but no annotations. The description covers the main behavior but leaves parameter semantics and edge cases (e.g., season validation, include_players effect) unaddressed. Overall adequate but not thorough.

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?

None of the three parameters (season, league_id, include_players) are described in the tool description beyond an indirect reference to league_id for re-calling. Schema coverage is 0%, so the description fails to compensate for missing parameter 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 states a specific verb 'Discover' with a clear resource ('configured Sleeper user's league, roster, and draft') and scope ('for a season'). It differentiates from sibling tools like get_season_context by emphasizing initialization and persistence of context.

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 explains automatic selection behavior and instructs the agent to call again with league_id when multiple leagues exist. However, it does not explicitly mention alternative tools or when to use them.

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 for behavioral disclosure. It usefully notes that Sleeper's search rank provides only stable ordering until independent valuations exist, which prevents misinterpretation. However, it does not clarify whether league_id or draft_id is required for meaningful results, nor what happens when neither is supplied, leaving a transparency gap.

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

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

The description is compact and front-loaded, with the primary purpose in the first sentence. The subsequent note about search rank is relevant and adds value without fluff. Every sentence earns its place, and the structure is easy to parse.

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

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

For a simple lookup tool, the description covers the core purpose and one behavioral nuance, but the optional parameters create ambiguity: calling with no league_id or draft_id might return an overly broad list, and the relationship between the two filters is not explained. With no annotations and 0% schema coverage, the description could be more complete in guiding proper invocation.

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 0%, so the description must compensate. It explains that the tool filters by current rosters and draft picks, aligning with league_id and draft_id, but it does not explain the limit or positions parameters or how the filters interact. This is partial compensation: useful for basic understanding but not a full substitute for detailed parameter docs.

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 a specific verb and resource: 'List active Sleeper players absent from current rosters and this league's draft picks.' It also explicitly distinguishes this from ranking or recommendation tools, which separates it from siblings like recommend_draft_pick.

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 frames this as an availability query and states it is not a ranking or recommendation, giving the agent clear when-not-to-use guidance. It implies use when a raw list is needed but does not name specific alternative tools or spell out conditions for each optional filter.

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 full disclosure. It mentions 'audit metadata' but does not disclose side effects such as whether the mapping is destructive, whether existing mappings are overwritten, or any permission requirements. This is a significant gap for a mutation-like tool.

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

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

Single sentence, directly states the core action with no filler. It is front-loaded with the verb and resource.

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?

Tool has 4 parameters and an output schema, and the description is minimal. While return values are covered by the output schema, the description lacks context on why manual resolution is needed and what 'audit metadata' entails, making it partially complete for a tool with this complexity.

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 0%, so the description must compensate. It references provider ID and Sleeper player, mapping to provider_player_id and sleeper_player_id, but does not explain the 'provider' parameter values, the 'confidence' default/semantics, or how they interact. Minimal value added beyond schema property names.

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 the specific verb 'resolve' with a clear resource: 'ambiguous provider ID to a Sleeper player'. The word 'Manually' distinguishes it from sibling sync tools that presumably automate identity mapping.

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 via 'Manually resolve' but does not explicitly state when to use it versus alternatives like sync_* tools. No exclusions or alternative references 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?

No annotations are provided, so the description carries the full burden. It discloses the optimization objectives (median, floor, upside), but does not indicate whether the tool mutates the lineup, requires authenticated league context, or returns a proposed lineup. This lack of side-effect or permission disclosure is a significant gap.

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

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

The description is a single, front-loaded sentence with no fluff. It efficiently conveys the core purpose, though it omits details that could be added without sacrificing conciseness.

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 3 parameters and no annotations, the description is minimally complete. It does not state required parameters, eligibility conditions, or any behavior beyond the optimization objectives. The presence of an output schema helps, but the tool still lacks essential context for correct invocation.

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 0%, and the description provides no explanation of the three parameters (week, league_id, roster_id). The required parameter 'week' is not even mentioned, leaving the agent to guess its role. The description adds no value beyond the schema's bare type definitions.

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 optimizes a weekly lineup for median, floor, and upside objectives. It uses a specific verb 'optimize' and resource 'eligible weekly lineup', distinguishing it from draft, waiver, and trade tools among siblings.

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: the tool is for optimizing a weekly lineup. However, there is no explicit guidance on when to use it versus alternatives, nor any mention of prerequisites like needing a valid league_id or roster_id, or the eligibility criteria for the lineup.

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 burden of disclosing behavioral traits. It explains the action (rank and estimate) but omits any details about output format, side effects, computational cost, or data dependencies. The tool's behavior beyond the basic outcome remains opaque.

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 efficiently conveys the core purpose. It is front-loaded and contains no filler, though it could be expanded to include more context without losing conciseness.

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's complexity (rankings, survival estimation) and the presence of four parameters plus an output schema, the description is underspecified. It does not explain what inputs affect the ranking, how survival is calculated, or what the output schema contains. The description leaves significant gaps for an agent trying to use 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?

The description provides zero information about the parameters (limit, draft_id, league_id, roster_id). Schema coverage is 0%, and while the schema includes defaults, it does not explain the meaning or usage. The description fails to compensate for the lack of parameter documentation.

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 function: ranking available draft choices and estimating survival to the next owned pick. This distinguishes it from sibling tools like list_available_players (which lists players) and get_draft_state (which provides state), though it does not explicitly name alternatives.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions. The description merely implies use during a draft, but does not clarify scenarios where other tools would be 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 must disclose behavioral traits, but it only describes the recommendation action. It does not mention whether the operation is read-only, requires any permissions, or how results are delivered, leaving safety and side-effect profile undefined.

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, compact sentence with no repetitive or extraneous content. It is efficiently structured with the verb and object first.

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's moderate complexity (3 params, output schema present), the description is too thin. It omits the meaning of optional parameters, the nature of the output beyond a recommendation, and any context about season strategy decisions. The presence of an output schema reduces the need to describe return format, but the description still leaves significant 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?

The schema has three parameters (week, league_id, roster_id) with 0% coverage in the description. The description's references to 'record, points rank, and roster strength' vaguely imply the data used but do not explain how these map to the parameters or why week is required.

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 function—recommending a risk posture—and specifies the data sources ('record, points rank, and current weekly roster strength'). While it does not explicitly contrast with sibling tools like recommend_draft_pick, the season strategy focus provides some distinction.

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?

No guidance is provided on when to use this tool versus alternatives. The description lacks contextual clues such as prerequisites, decision points, or exclusions, leaving the agent to infer suitability from the tool name alone.

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 must disclose behavioral traits. It indicates a mutation ('attach action') but does not state that it modifies an existing record, whether the change is reversible, or any side effects. It also does not mention required permissions or potential errors. The transparency is minimal.

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

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

The description is a single, clear sentence with a front-loaded verb, making it easy to parse. It avoids irrelevant detail. However, it is so brief that it sacrifices semantic richness, making it less useful than a slightly longer but more informative description.

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 two parameters, one of which is a nested object, and no annotations, the description is insufficient. It does not explain what a 'recommendation' is, what constitutes an 'action taken', or what fields 'chosen_action' should contain. While an output schema exists, the description still fails to give the agent comprehensive context for correct invocation.

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 description coverage for its two parameters, and the description does not mention 'decision_id' or 'chosen_action' at all. The description's phrase 'action actually taken' vaguely relates to 'chosen_action', but it provides no explanation of what these parameters are or how to structure them, especially since 'chosen_action' is an open object. This is a major gap.

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 function: attaching the action actually taken to a previously persisted recommendation. This uses a specific verb ('attach') and resource ('recommendation'), distinguishing it from simpler read tools. However, it does not explicitly differentiate from the similar sibling 'record_decision_outcome', leaving slight ambiguity.

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 this is used after a recommendation has been persisted, but gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives like 'record_decision_outcome' or conditions such as the recommendation existing or being in a certain state. Sibling tools are listed but not referenced.

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 full transparency burden. It discloses a key behavior (does not modify the original forecast), which adds value. However, it does not mention idempotency, whether an existing outcome can be overwritten, or what happens if the decision_id is not found.

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, well-structured sentence that is front-loaded with the verb. Every word contributes meaning, with no redundant phrases 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?

The tool has a nested object parameter and no annotations, yet the description is sparse. It does not explain what should go inside the outcome object, whether multiple outcomes can be attached to the same recommendation, or any constraints. While an output schema exists, the input semantics remain underspecified.

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 0%, so the description must compensate. It provides minimal semantic hint for 'outcome' as 'observed outcome', but does not describe the expected structure of the outcome object or the meaning of decision_id beyond its name. This is insufficient for low schema coverage.

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 ('attach') and identifies a clear resource ('observed outcome to a prior recommendation'). It also adds a distinguishing qualifier ('without rewriting its forecast') that separates it from sibling tools like record_decision_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 description clearly implies when to use the tool: after a recommendation has been made and an observed outcome is available. It does not explicitly name alternatives or exclusions, but the context is sufficiently clear for an agent to select it appropriately.

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 states 'Record' and 'for future calibration' but does not disclose whether it overwrites existing records, appends to a log, requires an existing synced league, or has any side effects. The behavior of the recording operation is essentially undisclosed beyond the verb itself.

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, front-loaded with the action and resource, with no redundant phrasing. It earns every word and is highly efficient.

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?

Despite the presence of an output schema, the description is too sparse for a 7-parameter tool. It does not explain the relationship between proposing and receiving rosters, the structure of player ID arrays, or any prerequisites like league sync. The phrase 'trade labels' fails to convey the full context of a trade offer recording, leaving significant gaps in understanding.

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 0% description coverage, so the description must compensate. It adds meaning to the 'status' parameter by listing valid statuses (proposed/rejected/countered/accepted), which is not present in the schema. However, it does not explain give_player_ids, receive_player_ids, roster IDs, league_id, or note, leaving most parameters semantically underdefined.

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 the specific verb 'Record' and identifies the resource as 'trade labels' with explicit statuses (proposed/rejected/countered/accepted). This distinguishes it from sibling tools like record_decision_action, but the term 'labels' is slightly vague and could be more precise about recording trade offers.

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 does not provide guidance on when to use this tool versus alternatives. Sibling tools such as record_decision_action and record_decision_outcome are present but no exclusions or differentiators are mentioned. The only context is 'for future calibration,' which implies a purpose but no clear usage conditions.

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 full responsibility for disclosing behavioral traits. It does not state whether the operation is a read-only refresh or writes data, what side effects occur, or whether it requires specific authentication or privileges. 'Refresh' implies a state change but nothing is confirmed.

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, which is concise, but it lacks substance. Conciseness should not come at the expense of necessary information. The one line does not earn its place because it is too vague to be actionable.

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 6 params, no annotations, and no parameter descriptions, the description is severely incomplete. It fails to explain what data is refreshed, how the tool integrates with the sibling tools, or what the output schema returns. This is far below a minimum viable description for such a complex operation.

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?

All 6 parameters have zero schema description coverage, and the description does not mention any of them (week, season, scoring, draft_id, league_id, include_players). The description provides no meaning or context for how these inputs affect the refresh operation, leaving the agent completely unguided.

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 identifies a verb ('refresh') and resources ('Sleeper ledger, market signals, licensed evidence'), giving a general sense of the tool's action. However, 'appropriate' is vague and does not clarify what is actually refreshed or how this differs from sibling sync tools. It reads more like a catch-all label than a precise purpose.

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 guidance on when to use this tool versus alternatives like sync_league or sync_sleeper_market. The description does not mention any exclusions, prerequisites, or context that would help an agent decide to invoke it. Usage must be inferred from the name and the vague '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 burden of behavioral disclosure. The term 'conflict-safely' hints at concurrency protection and 'agent-managed local' clarifies the queue scope, but details about conflict outcomes, reversibility, or side effects are missing.

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

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

The description is a single, front-loaded sentence with no wasted words. It achieves high clarity in one line, making it easy to scan.

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's complexity (4 parameters, conflict-safe logic, optional IDs) and lack of annotations, the description is insufficient. Even though an output schema exists, the critical semantics of revision checking and identifier selection are absent, making the tool hard to invoke 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 0%, and the description adds no information about the parameters. The crucial expected_queue_revision parameter is not explained, and optional identifiers like draft_id and roster_id are completely ignored, leaving the agent unable to construct correct arguments.

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 'remove' and clearly identifies the resource: one player from an agent-managed local draft queue. It also distinguishes itself from sibling tools like set_draft_queue_entry by specifying removal rather than addition.

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 for removing a player from the local draft queue, but does not explicitly state when to use it versus alternatives such as set_draft_queue_entry or get_draft_state. It provides no exclusionary guidance or prerequisites.

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 burden of behavioral disclosure. It clearly explains the optimistic concurrency mechanism (stale writes are rejected) and the consequence of preventing silent overwrites of picks or other queue edits. This goes beyond a generic 'update' statement.

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 two sentences long with no wasted words. It front-loads the core behavior and immediately provides the essential prerequisite, making it easy to parse and act on.

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 covers the critical behavior and prerequisite for safe writes, and an output schema exists so return values need not be explained. However, it does not elaborate on optional parameters or clarify that player_id and queue_rank are required (though schema does). For the tool's complexity, it is reasonably complete but not exhaustive.

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 0%, so the description must compensate for parameter meaning. It adds significant context for expected_queue_revision and expected_state_token by explaining they are concurrency tokens. However, the remaining six parameters (tier, draft_id, rationale, roster_id, player_id, queue_rank) are not described beyond their schema titles, leaving 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 clearly states the tool performs a conflict-safe insert-or-update of one player in the local draft queue, using specific verbs and a resource. It distinguishes itself from the sibling remove_draft_queue_entry by explicitly mentioning insert/update rather than removal.

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 provides a clear when-to-use context (insert or update a queue entry) and a specific prerequisite: copy expected_queue_revision and expected_state_token from get_draft_state. It does not explicitly name alternatives or exclusions, but the purpose is unambiguous relative to sibling tools.

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 full burden but only mentions the output estimate. It does not disclose whether the simulation mutates data, how long it runs, what inputs affect it, or any other behavioral traits. The term 'explicitly experimental' hints at an exploratory nature but is too vague to be informative.

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 short sentence, which is concise, but the phrase 'explicitly experimental' is awkward and structurally unclear. It could have been worded more clearly without sacrificing brevity.

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?

Despite having an output schema, the description is incomplete for a simulation tool with no annotations. It does not explain the simulation process, the meaning of 'experimental', or any edge cases. The agent likely needs more context to use this tool correctly, especially given the tool's complexity.

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 0% and the description does not mention any parameters. The schema's parameter titles ('Week', 'League Id', 'Simulations') are self-explanatory to some degree, but the description adds no semantics about how they influence the simulation or what values are appropriate. This leaves the agent without critical parameter insight.

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 action ('Estimate') and resource ('playoff and championship probabilities'), but the phrase 'explicitly experimental' is confusing and obscures clarity. It does not clearly differentiate from sibling tools like get_season_context or recommend_season_strategy, which might also involve probabilities.

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 guidance on when to use this tool versus alternatives, no exclusions, and no context about prerequisites (e.g., season must be initialized). The description only implies a generic use case without actionable direction.

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 burden of behavioral disclosure. It adds meaningful traits: it is a low-latency path, detects picks made during the read, and is intended to be paired with get_draft_state. It does not mention permissions or side effects, but the core behavioral nuance is present.

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 two sentences, front-loaded with the primary purpose, and every sentence adds useful information. There is no filler or redundancy.

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 covers what the tool does and when to call it, and an output schema exists to describe return values. However, parameter usage is completely unaddressed, and with many sibling sync tools, some explicit exclusions or alternative comparisons would make the description more 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 description coverage is 0% and the description does not mention draft_id or league_id at all. With two optional parameters and no guidance on how they relate to each other or when to provide them, the description provides no parameter-level 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?

The description uses a specific verb ('Refresh') with a precise resource ('live draft details, picks, and traded-pick ownership') and scoping word ('only'). It clearly separates this tool from sibling sync tools by emphasizing the draft-specific, low-latency 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 gives explicit timing guidance: 'Call it immediately before a draft decision' and explains the integration with get_draft_state via sync provenance. It does not explicitly state when not to use it or name alternative sync tools, but the context is clear enough for selection.

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 only says 'Ingest', which implies a write operation, but does not explain whether existing data is overwritten, what permissions are needed, rate limits, idempotency, or return behavior. The word 'licensed' hints at data rights but no more.

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?

Single sentence, front-loaded verb and resource, no redundancy. The description is appropriately sized and every word adds value.

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 4-parameter schema with no parameter descriptions and no annotations, the one-sentence overview is insufficient. It lacks parameter semantics, prerequisites, and expected effects. Even though an output schema exists, its content is not shown and does not compensate for missing operational context.

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 0% and the description does not explain any of the four parameters (week, season, scoring, league_id). There is no mapping from the listed data types to the parameters, so the agent cannot infer proper argument values.

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 the specific verb 'Ingest' and names the resource 'licensed FantasyPros identities, ECR/ADP, projections, news, and injuries', clearly distinguishing it from sibling tools like sync_league or sync_draft by indicating the data source and content.

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?

No guidance is provided on when to call this tool versus alternatives such as sync_league or import_provider_snapshot. The description only states what it does, not under what conditions or as part of what workflow.

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. It discloses automatic week capture and caching recommendation for players, adding useful context. However, it does not mention on whether the sync mutates state, is idempotent, or has rate limits—critical for a sync operation.

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 three concise sentences, front-loaded with purpose. Every sentence adds value: purpose, weeks behavior, and include_players guidance. No redundant content.

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?

An output schema exists, so return values are covered. The description adequately explains main decision points (weeks handling and players). Minor gaps: no mention of 'league_id' semantics, no statement about side effects of syncing, and no prerequisites. Overall, fairly complete for a sync 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?

Schema description coverage is 0%, so the description must compensate. It adds meaning for 'weeks' (current, historical, core state) and 'include_players' (large catalog refresh, caching). 'league_id' is not explained, but its purpose is easily inferred from the name. Overall, good compensation for schema lack.

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 'Synchronize broad Sleeper league state for setup and season-long operation,' using a specific verb and resource. It differentiates from sibling tools like sync_draft and sync_league_history by emphasizing broad league state and supporting historical/backfill via weeks parameter.

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 provides explicit guidance on parameter usage: omitting weeks captures current NFL week, explicit weeks for historical/backfill, empty list for core state, and include_players only for refreshing the player catalog. It does not explicitly mention alternatives or when-not-to-use, but the parameter behavior is well described.

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 of behavioral disclosure. It mentions the traversal method ('following the renewal chain') but does not disclose whether the tool over-writes data, is idempotent, or requires any prerequisites. Partial context but key side effects are missing.

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

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

A single, dense sentence covers purpose, frequency, and method with no wasted words. However, the extreme brevity contributes to ambiguity about prerequisites and effects.

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 annotations, so the description must cover side effects and prerequisites. It omits idempotency, data-handling behavior, and required initial conditions. An output schema exists, so return values are covered, but the side-effect profile is under-specified.

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 0%, so the description must compensate, but it provides no information about league_id or max_seasons. The defaults give faint hints, but agents cannot reliably infer what 'league_id' represents or how 'max_seasons' controls the backfill depth.

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 ('Backfill') and identifies the resource ('Sleeper's previous-league renewal chain'), which distinguishes it from sibling tools like sync_league that likely handle current data. The wording is somewhat cryptic but the actionable intent is clear.

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 provides a cadence ('every week') but does not explicitly state when to use this tool versus alternatives such as sync_league. No exclusions or alternative tool names are given, so usage guidance is only implied.

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 of disclosing side effects and behavioral traits. 'Ingest' implies writing/updating data, but the description does not state whether this is a read-only operation, whether it makes external API calls, if it is idempotent, or what the impact on existing data is. This lacks critical behavioral context.

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

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

The description is one short sentence, front-loaded with the verb 'Ingest'. It avoids verbosity and gets to the point quickly. However, it could be more structured by stating the purpose or usage context, but for conciseness alone it is effective.

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?

Despite having an output schema, the description is incomplete. It does not explain the parameters, when to use the tool, or the behavioral implications. The tool appears to be a data ingestion operation with optional parameters, but the description provides little context for an agent to invoke it 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?

The input schema has three parameters (limit, league_id, lookback_hours) with 0% description coverage. The description does not mention or explain any parameters, leaving the agent to guess their meaning and usage. This is a significant gap as the description should compensate for the lack of parameter documentation.

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 action ('Ingest') and resource ('Sleeper global add/drop trends'), making the core purpose clear. It also includes the purpose ('as a market signal'), which adds context. However, it does not explicitly differentiate from other sync tools like sync_fantasypros, but the source and data type are distinct enough.

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?

No guidance is provided on when to use this tool versus alternatives. There are no exclusions, alternatives, or context clues about suitable scenarios. The short description only states what it does, not when to invoke it.

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