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

With no annotations, the description carries the full burden and does well: it discloses the return granularity, the two output formats, and the 7-day local disk cache with force_refresh to bypass it. It stops short of stating auth requirements, rate limits, or error behavior for invalid match_id, which keeps it from a 5.

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

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

Front-loaded with the core purpose and return shape, then a compact Args block. It runs long, but given that the input schema carries zero parameter descriptions, nearly every line earns its place; the only mild redundancy is restating return fields in both the opening and the Returns section.

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 10-parameter tool with no annotations and no schema-level parameter docs, the description covers filters, paging, caching, and output format thoroughly, and the output schema handles return typing. Gaps remain around authentication/preconditions and failure modes, which matter for a tool that reaches out to Hudl/Balltime.

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 fully compensate, and it does: every one of the 10 parameters is documented with accepted value sets and examples (action_type enums, team 'a'/'b' or name, quality values, jersey vs name for player, match_id accepting Balltime/Hudl IDs or titles). It also explains the DataVolley skill and evaluation codes the filters align with.

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

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

States a specific verb and resource ('Retrieve detailed tagged volleyball actions and touch events from a match/video breakdown') and enumerates the returned fields (set, score, timestamp, jersey, action type, quality, zones). This is clearly distinguishable from siblings like get_match_player_stats or get_rotation_breakdown, which aggregate rather than return event timelines.

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 makes the use case implied (event-by-event timeline with optional filtering) but never says when to choose this over get_match_player_stats or get_rotation_breakdown, nor when not to use it. An agent has to infer the routing from the return content rather than being told explicitly.

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

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

With no annotations, the description carries the full burden and adds substantial context: it strips UI metadata, recalculates hitting percentage, returns a formatted box score or compact JSON, and explains that force_refresh bypasses a 7-day disk cache. It does not mention authentication, permissions, or error behavior, which keeps it from a higher score.

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 purpose is front-loaded and the Args/Returns structure is easy to scan. The long list of statistical fields is useful but somewhat verbose given that an output schema exists, so the description is not maximally concise.

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 all four parameters, output formats, cache behavior, and how to obtain the required match_id. Since an output schema exists, it need not fully define return values, and the remaining gap around auth or error handling is minor for a read-only stats 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, and it does: match_id is tied to a Hudl match identifier obtainable through list_volleyball_matches, team_id is an optional filter, output_format distinguishes markdown from compact JSON, and force_refresh is explained as bypassing the local 7-day disk cache.

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 opens with a specific verb and resource: 'Fetch individual athlete box scores and volleyball statistics for a match.' It clearly distinguishes this from sibling tools like get_rotation_breakdown and get_game_actions by focusing on per-player box scores, not rotation summaries or play-by-play actions.

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

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

It gives clear context for obtaining the required match_id via list_volleyball_matches and explains optional filtering by team_id. However, it stops short of explicitly stating when to prefer this tool over siblings such as get_rotation_breakdown or get_game_actions, leaving that inference to the agent.

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

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

With no annotations, the description carries the full burden, and it does disclose meaningful traits: a 7-day local disk cache, the fact that force_refresh bypasses that cache and triggers a live fetch, and the two output serializations. It omits error behavior, authentication requirements, and whether a missing team_id aggregates across both teams.

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 purpose is front-loaded and the Args/Returns structure is scannable. The parenthetical enumeration of six setter zone assignments is the weakest part, since it is long and its value is marginal to the decision of whether to call the tool.

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

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

An output schema exists, so the Returns section is redundant but harmless, and the description covers inputs, caching, and output shape. The remaining gap is behavior when team_id is omitted versus supplied, which matters for interpreting the breakdown.

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 carry the load, and it documents all four parameters: match_id with a route to obtaining it, team_id as an optional filter, output_format's two valid values with their shapes, and force_refresh's cache semantics. This fully compensates for the empty 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?

The opening sentence names a specific verb and resource: fetching tactical performance metrics broken down by volleyball rotation P1 through P6. The specific metrics listed (sideout efficiency, point scoring percentage while serving, FBSO conversion, setter distribution) make it easy to tell apart from get_match_player_stats and get_game_actions.

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 concrete routing guidance by telling the agent that match_id is obtainable via list_volleyball_matches, and it explains the team_id filter. However, it never says when to prefer this tool over get_match_player_stats or get_game_actions, and it states no exclusions or prerequisites beyond that ID hint.

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

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

With no annotations, the description carries the behavioral burden and does well: it implies a read-only retrieval from an authenticated account, discloses the 15-minute disk cache, and explains how force_refresh bypasses it. It does not explicitly state permission requirements or rate limits, but the key operational traits are covered.

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 front-loaded with purpose and then structured with Args and Returns. It is slightly verbose because the Returns section repeats output format details, but it remains readable and appropriately sized for a two-parameter discovery tool.

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

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

The description explains the purpose, parameter behavior, authentication context, caching, and return formats. Since an output schema exists, the return details are not strictly required, but their presence makes the definition complete 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?

Schema description coverage is 0%, so the description must compensate for both parameters, and it does: output_format is explained as markdown table versus compact JSON, and force_refresh is explained as bypassing the local 15-minute disk cache for a live fetch.

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 and resource: discover/list all Hudl teams associated with the authenticated account. It also names the practical purpose, finding the Team ID, so an agent can immediately distinguish this from match/stats/auth sibling 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?

The use case is clear: call this to discover teams and find a Team ID. It does not provide explicit exclusions or name alternatives, but no sibling tool appears to serve the same purpose, so the context is still strong.

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 behavioral burden and does reasonably well: it discloses the 15-minute disk cache and force_refresh bypass, and that team_id is auto-detected when omitted. It doesn't mention authentication or rate-limit behavior, but the cache disclosure is meaningful non-obvious 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?

Front-loaded with purpose and usage, then cleanly sectioned into Args and Returns. Slightly long and the Returns line partially duplicates the output schema's role, but no sentence is wasteful.

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 four params at 0% schema coverage and no annotations, the description covers discovery purpose, cache behavior, and all parameter meanings adequately. An output schema exists, so return-value detail is a minor redundancy rather than a gap.

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 and does: all four params are explained with meaning beyond the schema, including output_format's actual values ('markdown'/'compact') and force_refresh's cache relationship. This fully fills the documentation 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?

States a specific verb ('Fetch'), resource ('recent volleyball matches for a team'), and source ('from Hudl'). The 'discover the appropriate match_id for downstream analysis' line distinguishes it from siblings like get_match_player_stats and get_rotation_breakdown, which clearly operate downstream.

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?

Explicitly says 'Call this tool first when a user asks about match results or team performance,' giving clear trigger conditions. It implies but never names the alternative downstream tools, so it stops short of explicit when-not 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 and does so well: it discloses the visible browser window, the target URL, the completion condition (navigation to /home), the state file location (~/.hudl_mcp/auth_state.json), automatic browser close, session update, and the guarantee that no password is stored. That is exactly the behavioral context an agent needs.

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 core action and the automatic-save mechanism are front-loaded in the first paragraph, with useful elaboration following. Slightly verbose in places, and the Returns section duplicates information already implied by the output schema, but nothing is wasted.

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

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

For a single-parameter interactive auth tool with no annotations, the description covers preconditions, the user's role in the flow, the completion trigger, side effects (state file, session update, browser close), and failure reporting. An agent can call and reason about this tool correctly without further information.

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 — and it does, defining timeout_seconds as the maximum wait for login completion and restating the 300s/5-minute default. It adds meaning beyond the bare schema but does not say what happens on timeout expiry (error vs. partial state).

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 first line states a specific action and resource: open an interactive pop-up browser to log into Hudl and save session state. It is clearly distinguishable from siblings like refresh_hudl_cookie (which implies reusing an existing session rather than a fresh interactive login).

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 clearly describes the context of use: interactive login via password manager, Google/Apple SSO, or 2FA, and explains the automatic completion trigger. It does not explicitly state when to prefer this over refresh_hudl_cookie, so the agent must infer that this is the first-time/expired-session path.

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

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

With no annotations, the description carries the full burden and does well: it discloses the credential prerequisite (.env), that a fallback may trigger an interactive pop-up browser login (a real side effect worth warning about), and what is returned. It does not say where/how the cookie is persisted, whether it expires, or whether an existing session is invalidated — gaps for an auth-mutating 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?

Short, front-loaded, and split into a purpose line, a conditional behavior line, and a returns block. The 'Returns:' paragraph is largely redundant since an output schema already exists, costing a small amount of space.

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

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

For a zero-parameter auth tool with an output schema, the description covers the prerequisites, the two execution paths, the notable side effect, and the outcome. Remaining unknowns (cookie lifetime, storage location, effect on concurrent sessions) are secondary but would matter to an agent reasoning about repeated auth failures.

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?

Zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. The description correctly does not invent or allude to inputs, keeping the no-arg contract unambiguous.

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

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

States a specific verb and resource ('Refresh the Hudl session authentication cookie') and immediately frames the two operating modes, which implicitly distinguishes it from the interactive login_to_hudl sibling. An agent can tell what it does and how it relates to the other auth tool without opening either schema.

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 conditional 'If credentials are configured in .env ... Otherwise ... via login_to_hudl' gives clear context for which path will run and names the alternative tool. It stops short of an explicit instruction such as 'call this first; only use login_to_hudl if this reports no credentials', leaving the routing decision partly to inference.

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