Outmano

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

Annotations already declare readOnly, idempotent, and non-destructive, so the description's job is context: it correctly frames output as AI-generated (hence potentially stale) and scoped to a single competitor, and clarifies that generation is a separate in-app action. It stops short of describing the empty/unavailable-card case.

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 verb and resource; the section list is dense but each item tells the agent what content to expect from the return. The generation sentence is a worthwhile second beat rather than 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 handling return shape and annotations handling safety, the description covers scope, content, and the generation pathway. The only meaningful omission is behavior when the competitor has no battlecard or isn't tracked.

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

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

Schema coverage is 100% and the only parameter's format ('acme.com') is fully documented there, so the schema carries the load. The description adds only the mild implication that the domain must belong to a tracked competitor.

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 ('Get the AI-generated sales battlecard for one tracked competitor') and enumerates exactly what the card contains, so an agent knows this is the sales-enablement view rather than the SEO, feature-gap, or matrix views its siblings return. No sibling is named explicitly, which keeps it just short of 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?

'for one tracked competitor' establishes the precondition, and the closing sentence routes card creation/refresh to the app's Battlecard tab, telling the agent this tool only reads. It doesn't state what to do if the competitor isn't tracked or no card exists yet.

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, idempotentHint, non-destructive and closed-world, so safety is covered. The description adds meaningful context beyond that: it is a 'snapshot' of 'latest' data, both extras default to off, and the 'moves' are explicitly 'scored against you' with a stated relevance frame ('your brand, keywords you both rank for, real gaps'). Missing only freshness/refresh cadence and any cost or plan limitations.

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, well front-loaded: the core snapshot and its metric list come first, the optional enrichments second. Dense but every clause carries information; the second sentence is long with nested parentheticals, which slightly reduces scannability.

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 annotations covering the safety profile and an output schema covering return structure, the description only needs to convey scope, subjects, and optional enrichments — all present, including the useful qualifier that scope is limited to competitors already being tracked. Nothing an agent needs to call it correctly 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 description coverage is 100%, so a 3 is the baseline. The description earns a point above that by explaining the intent of each flag at a conceptual level — keywords are 'top organic' by traffic, and moves are 'scored against you' around brand/both-rank/gap keywords — which helps an agent decide whether to enable them rather than just knowing their type.

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 a well-scoped resource ('latest SEO snapshot for your product and each competitor'), then enumerates the exact metrics returned (domain rating, organic keywords, traffic, backlinks, referring domains, top-3/top-10 counts). This is unambiguous and non-overlapping with siblings like pricing changes or reviews, but it never names or differentiates itself from those siblings explicitly.

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 only implied: an agent can infer 'use this for SEO comparison' from the content, and the two optional flags are explained in terms of what they add. There is no explicit when-to-use vs. when-not, no mention of prerequisites (e.g. competitors must already be tracked, though 'each competitor you track' hints at it), and no routing to the battlecard or feature-gap siblings.

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 cover safety (readOnly, idempotent, non-destructive, closed-world), so the description is free to add semantics — and it does: results are ranked by rival count, and each gap carries every rival's own label and description. It doesn't discuss result size, pagination, or what happens when the competitor set is empty.

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-loads the definition before the enumerated use cases, and no sentence is filler. The second sentence is long and packs two ideas with an em dash, which slightly dilutes scannability.

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 shape needn't be spelled out, and the description still sketches the payload (per-rival labels and descriptions). It omits any prerequisite that competitors and your own site must already be tracked, and never mentions the category filter.

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 the single optional `category` param is fully documented with its enum-like value list, so the description adds nothing about filtering. The mention of majority_of_rivals is likely an output field rather than an input, so it doesn't compensate for input semantics.

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

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

States a specific verb and resource with precise scope: features competitors market that YOUR site doesn't mention, ranked by rival count. The gap-analysis framing implicitly separates it from outmano_get_feature_matrix, but no sibling is named explicitly, so an agent must infer the boundary.

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 two concrete, actionable scenarios — building missing features (with majority_of_rivals: true flagging table stakes) and fixing under-marketed existing features. There is clear context for when to reach for it, but no explicit exclusion or named alternative such as the feature matrix for full side-by-side comparison.

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 establish readOnly/idempotent/closed-world safety, so the description is free to spend its words on what annotations can't say — and it does: coverage is derived from each product's public site, and a missing feature means 'not marketed,' not 'not built.' That provenance and interpretive caveat materially change how an agent reads the results.

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 what the tool returns, then the caveat, then the parameter tip. Every sentence carries information and none is filler; slightly dense with clauses in sentence one but 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?

An output schema exists, so return structure needn't be described; the description still conveys grouping and column semantics. Combined with annotations covering safety, what remains omitted — pagination/volume behavior on a full catalog matrix, and the fixed enum list for category, which lives only in the schema — is minor.

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

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

Schema coverage is 100%, so the baseline is 3. The description goes beyond the schema's terse 'only return features where coverage differs across the set' by spelling out the semantic outcome — rows where everyone or no one has it are hidden — which clarifies what 'differs' means operationally.

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 (get the feature matrix for your competitive set) and enumerates the row/column content: canonical features grouped by category, competitor coverage, and your own coverage. It does not name a sibling to contrast with — notably outmano_get_feature_gaps, which an agent could easily confuse with this — so it is clear but not sibling-differentiated.

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 guidance is present but only at the parameter level: 'Use differences_only to hide rows where everyone (or no one) has it' tells the agent when to flip the flag. There is no statement of when to call this tool versus outmano_get_feature_gaps or the battlecard tool, and no prerequisites are given.

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 establish read-only, idempotent, non-destructive behavior, so the description does not need to repeat safety details. It adds meaningful behavioral context beyond annotations: ignored items are omitted, results are newest first and paginated, and each item includes angle, urgency, confidence, evidence, status, and a ~30-minute first step.

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 resource and scope, and every clause adds useful information. There is no filler or repetition of annotation or schema 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?

An output schema exists, so the description is not required to explain return values in full, though it helpfully summarizes item fields. Combined with annotations and full parameter schema coverage, the definition gives an agent everything needed to call the tool correctly.

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

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

Schema coverage is 100%, so the baseline would be 3. The description adds semantic value by explaining that limit=1 retrieves just the current plan and by reinforcing the paginated, newest-first ordering, which goes beyond the schema's generic 'Max results per page' wording.

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 your weekly AI action plans', and immediately explains what those plans are: suggested action items generated from competitors' latest moves. This clearly distinguishes it from all sibling tools, which retrieve competitor data (battlecards, SEO, pricing changes, reviews, etc.) rather than your own action plans.

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 useful usage guidance such as 'use limit 1 for just the current plan' and notes that ignored items are omitted. It does not explicitly frame when to choose this tool over siblings or when not to use it, but the resource distinction makes the intended context clear.

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 readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds value beyond that: newest-first ordering, pagination behavior, and the dashboard-feed equivalence that tells the agent what result set to expect.

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 short sentences, no filler, with the scope and ordering front-loaded and the dashboard-equivalence as a supporting clause. Every phrase carries 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?

With annotations, a full output schema, and 100% parameter coverage, the description supplies what structured fields can't: aggregate scope, sort order, and how the feed relates to the dashboard. Only the relationship to domain-specific sibling tools is left implicit.

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 each parameter (angle, significance, limit, offset) is documented in the schema with defaults and enum-like values. The description only alludes to pagination generically and adds no meaning about filtering dimensions beyond what the schema already states, so 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 (list) and resource (detected activity events) with scope ('across everything you track') and ordering ('newest first, paginated'). The aggregate framing implicitly separates it from per-domain siblings like outmano_list_competitor_pricing_changes or outmano_list_competitor_reviews, though no sibling is named explicitly.

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?

'This is the same feed as the in-app dashboard' gives useful context for what the results represent. However, there is no explicit when-to-use vs when-to-use-a-sibling guidance (e.g. 'for a single domain, use outmano_list_competitor_reviews instead') and no stated 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?

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely behavioral context beyond that: results are ordered newest-first and the listing is paginated, which tells the agent how to consume results. It stops short of saying what happens for an untracked or unknown domain (error vs. empty list), which is the main remaining behavioral ambiguity.

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 short sentences, zero filler. The resource and ordering are front-loaded and the optional filter is mentioned last, matching its optional status.

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 explained, and annotations cover the safety profile; with those accounted for, the description covers purpose, ordering, and filtering adequately. The gap is that it doesn't disambiguate the blog-posts resource from the news-mentions sibling or describe failure behavior for a non-tracked 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?

Schema coverage is 100%, so each parameter (limit, offset, competitor) is already fully documented, including defaults, max limits, and the 'use next_offset from the previous page' hint. The description's 'newest first, paginated' and 'filter to one competitor by domain' restate the schema's semantics rather than adding new detail, so the 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?

Specific verb+resource ('List recent blog posts published by the competitors you track') with scope, ordering, and pagination stated up front. The resource differs cleanly from sibling tools like outmano_list_competitor_news_mentions, outmano_list_competitor_reviews, and outmano_list_competitor_mentions.

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 to one competitor by domain' plus 'competitors you track' implies when this is the right tool, but it never states when NOT to use it. The most likely confusion is against outmano_list_competitor_news_mentions (both return competitor content), and the description offers no routing between the two.

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real value by disclosing ordering ('newest first'), pagination, and that each mention is enriched with sentiment and intent labels. It still says nothing about rate limits, freshness/lookback window, or how many competitors 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?

Three tight sentences: what is listed and where it comes from, then ordering/pagination and payload enrichment, then filtering. No filler and 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?

With an output schema present, the description need not explain return values, and it covers purpose, ordering, pagination and filter surface for a 6-optional-parameter tool. The gap is the omitted 'web' channel in the source list, which leaves the channel filter's full domain slightly 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?

Schema description coverage is 100%, so every parameter including limit, offset and the enum-like value lists is documented in the schema itself. The description only restates the filter dimensions ('competitor domain, channel, sentiment or intent') and adds no syntax or behavioral nuance 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?

Specific verb+resource with sources named ('List recent public mentions of the competitors you track and of your own product (Hacker News and Reddit)'), which separates it from siblings like list_competitor_news_mentions or list_competitor_reviews. However, it says mentions come from Hacker News and Reddit only, while the schema's channel filter also accepts 'web' — a mild scope inconsistency.

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 clear operative context: newest first, paginated, and filterable by competitor domain, channel, sentiment or intent. It does not explicitly say when to prefer this over sibling tools such as list_competitor_news_mentions or list_competitor_reviews, so the routing is inferred from the named sources rather than 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?

Annotations already declare read-only, idempotent, closed-world, so the safety bar is low; the description adds the useful behavioral facts not in annotations — newest-first ordering and pagination. It omits retention window ('recent' is unquantified), which is the one real 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?

A single dense sentence with the core purpose front-loaded, followed by ordering, pagination, and filter options. No filler, nothing redundant.

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-required-param list tool with a full output schema and complete parameter docs, the description covers what the agent needs. The missing piece is disambiguation from outmano_list_competitor_mentions and a definition of 'recent'.

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

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

Schema coverage is 100%, so limit/offset/category/competitor are already documented thoroughly. The description only echoes the filtering intent and adds that competitor filtering is by domain — marginal value over the schema, so 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?

Specific verb and resource: lists recent press mentions of tracked competitors, with the category taxonomy (funding, acquisitions, layoffs, general) and ordering/pagination stated. It does not, however, distinguish itself from the very similarly named sibling outmano_list_competitor_mentions, which is the one ambiguity an agent would hit.

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

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

The description implies when to use it (press coverage tracking) and what filters exist, but gives no explicit when-not guidance and never mentions the near-duplicate sibling outmano_list_competitor_mentions. Usage is inferable but the agent is left to guess between two similar 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?

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely useful behavior beyond them: results are ordered newest first, results are paginated, and each item carries an AI summary with before/after pricing detail — all relevant to how an agent should consume the output.

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

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

A single front-loaded sentence with the verb and resource first, then ordering, pagination, and payload shape. Every clause carries information an agent would otherwise have to discover, and there is no filler.

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

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

With annotations covering safety, a 100%-documented schema, and an output schema that carries return-value detail, the description is nearly sufficient. The only real gap is the undefined window behind 'recently' — how far back the list reaches and whether older changes are retrievable — which matters for an intelligence-monitoring 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 100%, so limit, offset, and the significance enum are fully documented structurally; the baseline is 3. The description reinforces ordering and pagination semantics but adds nothing about the significance filter or how it interacts with the detected changes.

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 ('List recently detected pricing changes') and scopes it to 'competitors you track,' which naturally separates it from siblings like outmano_list_competitor_roadmap_changes or outmano_list_competitor_blog_posts. It never names an alternative explicitly, so a 5 isn't warranted, but the resource is specific enough to route correctly.

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 only implied: the phrase 'recently detected' suggests a monitoring/browsing workflow, but there is no statement of when to choose this over the roadmap-changes or mentions tools, nor any exclusion criteria. Nothing misleading, but the agent must infer the decision 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, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds useful behavior beyond that: newest-first ordering, pagination, and that a per-competitor rating summary (average, count) is returned alongside the list. It stops short of stating prerequisites such as needing competitors tracked or connected review sources.

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 with zero filler: it front-loads what is listed, then ordering, pagination, the aggregate payload, and the filter dimensions. Nothing repeats the title 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?

With an output schema present and full parameter documentation, the description covers the remaining essentials: what is returned (reviews plus rating summary), ordering, and pagination via offset. Minor gaps remain around whether a competitor must already be tracked before reviews appear, but overall it is sufficient 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 100%, so each parameter (limit, offset, source, competitor, negative_only) is already documented in the schema, including the G2 plan caveat and the 2-star threshold. The description only restates the filter dimension names and adds no syntax or format detail beyond the schema, so the 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?

The description gives a specific verb and resource ('List recent public reviews of the competitors you track') plus scope details like ordering and the rating aggregate. It does not explicitly distinguish itself from close siblings such as outmano_list_competitor_mentions or outmano_list_competitor_news_mentions, so an agent must infer the boundary between reviews and mentions.

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 through the description of available filters ('Filter by competitor domain, source, or negative-only'), telling the agent what can be narrowed. There is no explicit when-to-use guidance, no exclusion conditions, and no named alternative sibling tools to redirect to.

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 readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds ordering ('newest first') and pagination, plus that each item carries an AI summary and details, but says nothing about auth requirements, rate limits, or retention window of 'recently'.

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

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

A single well-formed sentence that front-loads the resource and scope, then appends ordering, pagination, and payload content. 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?

With a full output schema, rich annotations, and 100% parameter coverage, little narrative is required. The description covers what is returned and in what order; only the meaning of 'recently' and the available filters are left unstated.

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 limit, offset, change_type, and significance are fully documented in the schema, and the baseline for that is 3. The description adds no parameter-level meaning, notably omitting that change_type and significance filters exist at all.

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: lists recently detected roadmap changes for tracked competitors, enumerating the change kinds (added, shipped, renamed, removed). This clearly separates it from sibling resources like pricing changes, blog posts, or news mentions, though it never names a sibling explicitly.

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 only implied by the scope phrase 'for the competitors you track' plus 'recently detected'; there is no explicit when-to-use guidance, no statement of when a different tool (e.g. feature matrix or feature gaps) is the better call, and no exclusions.

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