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

Beyond readOnlyHint/openWorldHint, the description adds genuinely useful behavior: results are cached so repeat calls are instant, and depth 18+ is slower but more precise. It also discloses the Chess.com username precondition, a real failure mode. Nothing contradicts the annotations — this is a read-only external-fetch-and-analyze 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?

Front-loaded with the outcome and the payoff ('explain why a move was bad'), followed by a clean Args block. The return-value enumeration partly duplicates the output schema, but it is tight and no sentence is filler.

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

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

For a four-parameter analysis tool with an output schema, the definition covers inputs, defaults, caching, and cost/latency tradeoffs. Minor omissions remain — no mention of what happens on an invalid or unsupported game id, and no relationship to engine_status despite engine availability being a likely precondition.

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 carries the full burden and does so: game_id accepts an id or URL from either platform, platform enumerates exactly 'lichess'/'chesscom' and is guessed when omitted, username's conditional requirement and its effect on user_color/user_result are stated, and depth's default of 14 with the 18+ tradeoff is given.

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 scope: 'Run a full engine analysis of one game and classify every move', then enumerates the outputs (eval before/after, centipawn loss, labels, accuracy, critical moments). An agent can tell it apart from find_blunders by the 'every move' / 'five most critical moments' framing, though it never explicitly names the sibling it replaces.

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 context is concrete: game_id comes 'as returned by get_recent_games', username is required only for Chess.com games not fetched via that tool, and depth trades speed for precision. What is missing is explicit routing against siblings — nothing says when to prefer find_blunders or get_opening_stats over a full analysis.

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?

The readOnlyHint annotation already establishes this is a safe, non-mutating read, so the description only needs to add context. It contributes by disclosing that the payload covers engine identity, filesystem location, and cache statistics, but says nothing about whether the result reflects live state, whether the fallback can be switched, or any cost/latency of the check.

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, front-loaded with the primary fact (which engine is active) and back-loaded with the secondary detail (location, cache stats) and the usage hint. No filler.

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

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

With an output schema present, no parameters, and a read-only annotation, the description carries only what structured data cannot: that this is a diagnostics call and what categories of information it surfaces. That is sufficient for an agent to decide to call it.

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

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

The tool takes zero parameters, which is the baseline-4 case; the description correctly implies a no-argument global query rather than promising any filtering options. Nothing further is needed on this dimension.

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 ("Report") and a precise resource (the active chess engine), and enumerates the possible values (local Stockfish vs. Lichess cloud fallback) plus the extra fields returned (location, cache statistics). This is unmistakably a diagnostic/status tool, so it cannot be confused with the sibling analysis 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?

"Useful for troubleshooting" implies the usage context but gives no explicit when-to-use or when-not-to-use conditions, and names no alternative. It does not say whether to call this before or after a failed analysis, which is the most likely reason an agent would reach for 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?

Annotations already declare readOnlyHint=true and openWorldHint=true, matching a read-only fetch against Lichess/Chess.com, so the safety profile is covered. The description adds useful behavior beyond that — deterministic sort order and the fact that results are filtered rather than exhaustive. However, the phrase 'uncached Chess.com games' hints at caching without explaining it, and nothing is said about failure modes such as an unresolvable game id or an unavailable engine.

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

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

A single front-loaded sentence states the return shape, the sort order, and the cost tradeoff, followed by a one-line routing hint and a compact per-argument block. No sentence is redundant and the highest-value information comes 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?

An output schema exists, so the description needn't fully define return values, and it still summarises them accurately. For a five-parameter, network-dependent tool the coverage is strong; the remaining gap is error and edge-case behavior (bad id, platform-guess failure, empty result when no move exceeds the threshold).

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% with five parameters, so the description has to carry the full load and largely does: game_id accepts an id or URL, platform is guessed when omitted, username is only conditionally required, and threshold is anchored with a concrete scale (100 = mistakes and blunders). The one soft spot is the interaction between only_user and username when only_user=true but no username was supplied, which is left implicit.

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 gives a specific verb and resource ('Return only the moves that lost at least threshold centipawns') and states the exact payload — FEN, engine best move, best line, sorted worst-to-best. It also explicitly contrasts itself with a named sibling ('Cheaper to read than analyze_game when you only need the mistakes'), so an agent can separate it from that 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 routing rule against analyze_game is explicit, and the Args block states the conditional requirement that username is needed for uncached Chess.com games. What's missing is any exclusion or fallback guidance — e.g. what to do if the id can't be resolved to a platform, or whether to analyze the whole game first.

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

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered; the description adds that each row carries game ids and that variations are folded under families by default, which is genuine behavioral context. It says nothing about pagination, performance, or behavior on invalid usernames/platforms.

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 summary followed by a short rationale and a compact Args block — no wasted sentences. The Args list is somewhat verbose in phrasing but is justified given the zero schema coverage.

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 5-parameter read-only analytics tool with an output schema, the description covers purpose, the analytical intent, parameter values, and the downstream workflow. Only edge-case handling (invalid platform, fewer games than count) is unaddressed, which is minor given the output schema exists.

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 carries the full burden and does: it documents all five parameters, including allowed values for platform and color, the 1-300 range for count, and the default-true semantics of group_by_family. This is meaning the schema cannot supply on its own.

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 names a specific aggregation (win/draw/loss record) over a specific resource (openings) and scope (a player's recent games). It is clearly distinguishable from siblings like get_recent_games (raw list) and find_blunders (mistake drill-down), which the description itself references.

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 states the analytical use case ('spot openings the player struggles with') and explicitly routes follow-up work to find_blunders via the per-row game ids. It stops short of saying when to prefer get_recent_games instead, so there is no explicit exclusion rule.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds real context beyond that: one entry per game, the fields returned, and the fact that games are cached locally so subsequent tools can resolve them by id — a side effect worth knowing. It does not mention failure modes for private or nonexistent accounts on an open-world network call.

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

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

A single front-loaded purpose sentence, a compact return-format note, and an Args block that earns its space precisely because schema coverage is 0%. No filler or repeated phrasing.

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 output schema covers return values, so the description needn't re-document them, and it instead supplies the caching behavior and downstream linkage an agent needs. What's missing for an open-world fetch tool is any note on rate limits, authentication, or behavior when the username is invalid.

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 carries the burden and largely does: it states the accepted platform values ("lichess" default or "chesscom"), which the schema does not, and constrains count to 1-100 with a default of 10. Username is described only minimally as the player's handle on the chosen platform.

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 (list a player's most recent games) and names the two supported sources, Lichess and Chess.com. It also implicitly separates itself from siblings by pointing to analyze_game / find_blunders as downstream consumers of the returned game_id.

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 establishes the context of use: fetch recent games, then pass the game_id to analyze_game or find_blunders. There is no explicit statement of when NOT to use it (e.g., versus get_opening_stats for aggregate results), so it falls short of a full when/when-not/alternatives treatment.

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