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

No annotations are provided, so the description carries the burden. 'Fetched live from Steam' discloses that data is real-time and not cached, and the aggregation framing implies a read-only operation. However, it says nothing about auth requirements, rate limits, latency, or error behavior for an invalid AppID.

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

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

Two tight sentences with zero filler. The scope of the returned data comes first, then the routing guidance, so the most decision-relevant information is 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?

An output schema exists, so return values need not be described, and the description still enumerates the covered data domains. Combined with explicit sibling routing, an agent has everything needed to select and invoke this tool correctly.

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

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

Schema description coverage is 100% and there is a single parameter, so the schema already explains the AppID-or-name format and the preference for AppIDs from steam_search_apps. The description adds no parameter guidance beyond what the schema states, which is the expected baseline.

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 ('one-call health check for a Steam game') and enumerates the exact payload: current players, review summary, price, release info, genres, news headlines. This clearly distinguishes it from the sibling detail tools without opening any 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?

Gives explicit when-to-use ('how is X doing' questions, start here) and names the alternatives (steam_get_app_reviews, steam_get_game_news) with the condition that selects them ('only when the user needs detail'). Routing is fully specified.

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 delivers meaningful behavior: data is fetched live (freshness), it returns summary stats plus representative quotes, and it explicitly warns that review text is untrusted user-generated content to summarize rather than obey. It does not cover rate limits, caching, or permission needs, but the injection-safety disclosure is genuinely useful context beyond structured fields.

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

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

Two compact sentences, front-loaded with purpose and filters before the safety caveat. Every clause earns its place with no 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?

For a 7-param read tool with an output schema (which relieves the description of explaining return values) and pagination documented in the schema, the description is nearly complete. The main omission is any note on result freshness limits or throttling behavior when mining at scale.

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 71%, so the schema documents most parameters. The description maps filter dimensions to the filter/review_type/language/keyword params but adds no syntax or format detail beyond the schema, and says nothing about cursor or detail semantics. Baseline 3 is appropriate.

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

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

States a specific verb+resource ('Mine Steam reviews for a game') with scope qualifiers (fetched live from Steam) and enumerates the filter dimensions. This is unmistakably distinct from the sibling tools (search, overview, store details, news, player trend, market pulse), none of which touch reviews.

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?

Filter dimensions (recency, sentiment, language, keyword) imply what the tool is for, but there is no when-to-use guidance against alternatives — e.g. no hint of when to reach for reviews versus steam_get_app_overview or steam_get_store_details for sentiment-like signals, and no prerequisites or exclusions stated.

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 and does useful work: it discloses that content is fetched live, that detail="full" returns complete bodies, and it adds an important safety directive that news bodies are publisher-authored data and must not be treated as instructions. It omits rate limits, pagination and error/empty behavior.

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

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

Three compact clauses, front-loaded with what the tool returns and how, followed by the output-mode distinction and the safety note. No filler, and each sentence adds decision-relevant 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?

Even though an output schema exists, the description helpfully clarifies the two return shapes, freshness and the prompt-injection posture. Only the count parameter and paging/large-result behavior are left unaddressed, which is a minor 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 67%, and the description augments it by spelling out the digest shape (title, date, excerpt) and reinforcing the detail="full" mode. The count parameter's semantics live entirely in the schema and get no mention here, so it does not fully compensate for the coverage 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 and resource (fetches recent news/patch notes for a game) and names the source (live from Steam). The resource is clearly distinct from every sibling, which covers search, overview, store details, reviews, player trends and market 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?

Makes the use case clear (recent news and patch notes) and implicitly routes the agent away from the other Steam tools by resource type. It never states when-not to use it or names an alternative explicitly, so it falls short of full when/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. It discloses that entries are curated/original editorial content and 'latest' implies recency ordering, which is useful. It does not cover pagination behavior beyond limit, result freshness, or whether the digest is static, leaving a gap for a no-annotation 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?

Two front-loaded sentences with no filler; the scope ('curated market digest') comes before the enumeration of content types. The trailing list of topics is slightly long but still earns its place by clarifying what the entries cover.

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-value explanation is unnecessary, and a single optional parameter keeps the calling contract simple. The description is sufficient for correct invocation, with only minor gaps around recency/scope boundaries.

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

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

There is only one optional parameter (limit) and the schema documents it at 100% coverage with default and bounds. The description adds nothing about limit, so the baseline of 3 for fully-covered schemas applies.

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

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

The description names a specific resource (a curated market digest of editorial entries on Steam trends, live-ops, and competitor analysis) and its provenance (steam-mcp project). It is clearly not a per-app lookup, distinguishing it from siblings that all take an app identifier. The verb is only implied rather than stated, which keeps it 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?

Mentioning that the content targets 'game developers' with trends/live-ops/competitor pieces implies when the tool is useful, but no alternative is named and no explicit when-to-use/when-not guidance is given. An agent must infer that this is for broad market context rather than app-specific data.

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 substantial work: it discloses that Steam provides no history and the data comes from a companion backend over time (implying sparse history for newly tracked apps), plus the side effect that querying an untracked game begins tracking it. It omits auth requirements and whether tracking can be stopped, keeping it short of a 5.

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

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

Three sentences, zero filler: purpose first, then the provenance caveat, then the side effect. Each sentence delivers information the agent cannot get from the schema or annotations.

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 return shape need not be explained (the description's output enumeration is mild redundancy). The critical unknowns – data provenance and the tracking side effect – are covered, leaving only minor gaps such as what a series looks like for a barely-tracked app.

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

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

Schema description coverage is 100% – the schema already explains the AppID/name format for 'app' and the lookback meaning of 'days'. The description adds no parameter-level syntax or defaults beyond that, so the baseline of 3 applies.

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

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

States a specific resource and verb-equivalent: 'Player-count history for a game,' and enumerates the exact outputs (snapshot series with min/max/average, week-over-week change, insight line). This is unmistakably distinct from siblings like steam_get_market_pulse or steam_get_app_reviews without opening any 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?

Usage is implied by the resource name, and one triggering condition is given ('requesting a trend for an untracked game starts tracking it'). However, it never states when to prefer this over a sibling such as steam_get_market_pulse for current player numbers, so the agent must infer the choice.

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 carry the full behavioral burden, and 'fetched live from Steam' usefully signals freshness and an external network call. It says nothing about failure behavior for unknown apps, rate limits, or latency, leaving meaningful gaps for a no-annotation 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?

Two sentences, front-loaded with the resource and its field list, then the usage cue. The field enumeration is dense but each item earns its place by telling the agent what metadata is retrievable.

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-value explanation is not required, and the field list plus the `cc` regional-pricing note cover the calling surface adequately. The only shortfall is behavioral detail (error handling, live-fetch cost/latency) that the absent annotations leave unaddressed.

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

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

Schema description coverage is 100%, so both parameters are already documented ('cc' as ISO country code for regional pricing, 'app' as AppID or exact name with a preference for steam_search_apps results). The description's 'price (per region via `cc`)' only reinforces what the schema already states, adding no new syntax or format detail; baseline 3 applies.

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

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

States a specific verb+resource ('Full store listing for a game, fetched live from Steam') and enumerates the payload fields, which makes the tool's scope clear. It does not explicitly distinguish itself from the sibling steam_get_app_overview, which could plausibly overlap on store metadata, 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?

'Use for pricing and store-metadata questions' gives a clear, concrete usage cue tied to the tool's distinguishing feature (regional pricing). It names no alternatives and no when-not conditions, e.g. directing review or news questions to steam_get_app_reviews / steam_get_game_news, so no exclusion guidance is present.

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 and mostly succeeds: it discloses that results come from a live store search (not cached), that up to `limit` candidates are returned as appid + name, and that they are ordered best-match-first. It does not mention auth requirements, rate limits, or what happens on zero matches, which keeps it short of a 5.

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

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

Three sentences, front-loaded with the action, then the return shape, then the routing rule. No filler; every clause carries information an agent needs for selection or invocation.

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 2-parameter search tool with an output schema already covering return structure, the description supplies the missing pieces: the live-search semantics, the result count and ordering, and the resolution flow relative to sibling tools. Nothing required for correct invocation is absent.

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 50% — `query` is documented in-schema, but `limit` has only structural bounds and no description. The description compensates by explaining that `limit` caps the number of returned candidates, and it clarifies the query is a game name rather than an AppID. That adds real meaning beyond the schema.

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

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

States a specific verb (find/search) and resource (Steam game by name) and names the mechanism (Steam's live store search). It also explicitly distinguishes itself from all siblings by noting every other steam_* tool accepts an AppID, so an agent can route correctly without inspecting schemas.

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?

Gives the exact triggering condition: 'Call this whenever you have a game name but no AppID.' It also states the alternative path (AppID preferred, exact name accepted) used by sibling tools, which is precisely the when/when-not guidance an agent needs to choose between this and the steam_get_* tools.

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