Which conferences a company sponsors, exhibits at or speaks at, and who is open to sponsors.
Scored across 9 tools
Several tools have overlapping retrieval responsibilities: fetch and get_conference both return a single conference's full record, differentiated only by id vs slug, and search/search_conferences both find conferences with different query modes. An agent could easily select the wrong tool without carefully tracking which identifier or filter style it has.
Tool names follow no consistent pattern: bare verbs like fetch and search sit alongside verb_noun names like get_conference and search_conferences, noun phrases like company_events and organizer_contact, and the informal whats_new. The mix of styles and near-synonymous verbs makes the naming unreliable.
Nine tools is a reasonable size for a conference-research server, and the set covers multiple distinct research intents. However, the presence of duplicate retrieval/search surface makes it feel slightly over-provisioned; not every tool clearly earns its place.
The domain is well covered: conference discovery by text and structured filters, full conference details, sponsorship opportunities, speaker calls, organizer contact, company event footprints, and change tracking are all present. Gaps are minor, such as no speaker-centric search or company profile tool, but agents can generally work around them.
Every conference a company appears at, as sponsor, exhibitor or as the employer of a speaker. Past and upcoming. This is the question no other public source answers: give it a company name or a domain and it returns the event footprint. Up to 25 by default, 100 at most, upcoming first. Coverage depends on how a company spells its own name across event sites, so treat the list as strong evidence, not a complete census.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Rows to return. Default 25, maximum 100. | |
| company | Yes | Company name or domain, e.g. Datadog or monday.com. Pass it exactly as the user wrote it; do not strip or add a domain. | |
| include_past | No | Include finished events. Default true. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare openWorldHint=false, but the description directly contradicts this by warning that coverage depends on company name spelling and that the result should be treated as 'strong evidence, not a complete census.' That is explicitly an open-world completeness caveat, so an agent relying on the annotation would draw the wrong conclusion about absent 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?
The description is compact, front-loaded with the core scope, and every sentence earns its place: scope, unique value, output limits/ordering, and data-quality caveat. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input type, result scope, default/maximum limits, ordering, and a meaningful coverage caveat. While there is no output schema and the exact returned fields are not itemized, the description gives enough context for an agent to invoke the tool correctly, apart from the open-world contradiction.
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 the schema already documents company, limit, and include_past with defaults and usage guidance. The tool description adds only the conceptual 'name or domain' framing, which is already present in the schema, so it does not materially raise the 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 precisely what the tool does: given a company name or domain, it returns conferences where that company appears as sponsor, exhibitor, or speaker's employer, covering past and upcoming events. This clearly distinguishes it from sibling tools like events_open_for_sponsorship and get_conference.
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 identifies the exact question this tool answers ('the question no other public source answers') and the correct input form. However, it does not explicitly name alternatives or state when not to use it, so routing relies on the agent's inference from sibling names rather than explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Upcoming conferences that publish a sponsor page or a sponsor prospectus, so a marketer can see who is taking sponsors now. Filter by city, country or topic. Up to 25 by default, 100 at most. Pass a slug to also get the companies that sponsor comparable events but not this one.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | City name. | |
| slug | No | One conference slug. Adds the sponsors its peers have and it does not. | |
| limit | No | Rows to return. Default 25, maximum 100. | |
| topic | No | Topic or industry. | |
| country | No | Two-letter country code. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds meaningful behavioral details beyond that: the default and maximum row limits (25/100) and the unusual slug behavior that returns sponsors from comparable events not sponsoring this one. This helps the agent understand what the tool actually returns and how it behaves at boundaries.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences with no filler. It front-loads the core purpose, then lists filters, limits, and the special slug behavior in natural order. Every sentence earns its place.
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 read-only, filterable list tool with 5 optional parameters and no required fields, the description gives enough information to invoke it correctly. It covers what is returned, how to filter, the limit behavior, and the optional enrichment via slug. The lack of an output schema is acceptable because this is a list-retrieval tool and the descriptions focus on selection semantics.
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 input schema already describes each parameter and the default/maximum limit. The description reinforces the same information ('Filter by city, country or topic', 'Up to 25 by default, 100 at most') without adding meaningfully new semantics. This meets the baseline for a fully covered schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource: upcoming conferences with a sponsor page or prospectus, and the intended use case for marketers seeking sponsorship opportunities. It is immediately distinguishable from sibling tools like search_conferences or get_conference by focusing specifically on conferences 'open for sponsorship'. The phrasing 'see who is taking sponsors now' adds a concrete, actionable purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when a marketer wants to find conferences currently accepting sponsors. It also explains the available filtering dimensions (city, country, topic) and the optional slug behavior. However, it does not explicitly say when NOT to use this tool or compare it to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch one conference by the id returned from search. Gives the full record: dates, location, speakers, sponsors and exhibitors.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | An id from search. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by listing the record fields (dates, location, speakers, sponsors, exhibitors), but does not disclose additional behavior like error handling or permission requirements. With annotations covering the safety profile, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler. The action and source of the id are front-loaded, and the return content is listed succinctly. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read-only tool, the description is complete: it explains what to pass, what you get back, and the annotations cover safety. It does not address error cases or ambiguity with get_conference, but these are minor gaps given the tool's simplicity.
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% for the single 'id' parameter, described as 'An id from search.' The description repeats this context but adds no new detail beyond the schema, 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?
The description states a specific verb (fetch), resource (conference), and source (id from search). It clearly distinguishes from search tools, though it does not explicitly differentiate from the sibling get_conference, which appears to serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: the id comes from search, implying usage after a search operation. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an agent to understand when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Conferences currently accepting speaker submissions, with the deadline and the submission link. Soonest deadline first, up to 25 by default and 100 at most. Only calls that close before the event starts are returned.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Rows to return. Default 25, maximum 100. | |
| topic | No | Topic or industry, e.g. security. | |
| within_days | No | Only calls closing within this many days. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true, so no safety contradiction exists. The description adds meaningful behavioral detail beyond annotations: results are sorted by soonest deadline, limited to 25 by default and 100 max, and filtered to calls that close before the event starts.
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 crisp sentences deliver the core purpose, return contents, ordering, limits, and an important filter condition. There is no redundancy or filler; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with three optional, well-documented parameters and no output schema, the description adequately explains what will be returned (conferences with deadlines and links), how results are ordered, and the applicable limits and filters. Nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the three parameters (limit, topic, within_days) are already fully documented. The description adds some context about defaults and limits but does not meaningfully enhance parameter understanding beyond the schema, so the 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?
The description clearly identifies the tool's purpose: finding conferences currently accepting speaker submissions, and specifies what is returned (deadline and submission link). It is also distinguishable from siblings like events_open_for_sponsorship by focusing on speaker calls rather than sponsorship.
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 strong context for when this tool is appropriate—when you need open calls for speakers with deadlines and links. However, it does not explicitly state when to prefer an alternative or mention exclusions relative to sibling tools, leaving some 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.
One conference edition with its speakers, sponsors, exhibitors and sessions. Take the slug from search_conferences. Lists are capped at 25 each while the counts are the true totals, so a result can read '312 sponsors, showing 25'. Many upcoming editions publish before their line-up does: empty lists are normal and do not mean the event has none.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Conference slug, e.g. websummit-2026. | |
| facet_limit | No | Rows per list. Default 25, maximum 50. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds valuable behavioral context: the list cap of 25 while counts are true totals, and the note about empty lists for upcoming editions. This enriches the agent's understanding of what to expect, going beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact (2 sentences) and front-loads the core purpose. Every sentence earns its place: the first defines the resource, the second provides critical usage and behavior notes. There is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (one required param, one optional), the absence of an output schema, and the fact that the description covers purpose, usage, and behavior nuances, the description is complete for an agent to select and invoke the tool correctly. It addresses potential pitfalls (empty lists, list caps) and provides a clear parameter source, leaving nothing essential uncovered.
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 the schema documents 'slug' and 'facet_limit' with examples and ranges. However, the description adds crucial semantic value by explaining the list cap behavior tied to these parameters (e.g., counts vs. lists) and the practical nuance about empty lists. This exceeds the baseline of 3 by providing interpretative guidance on the parameters' effects.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'one conference edition' with its associated entities (speakers, sponsors, exhibitors, sessions), which is specific and distinguishes it from sibling tools like search_conferences. It uses a specific verb 'get' and names the resource and scope, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides a usage instruction: 'Take the slug from search_conferences', which tells the agent exactly how to obtain the required parameter. It also sets expectations about empty lists being normal for upcoming editions, guiding the agent's interpretation of responses. This is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
How to reach the organiser of one conference. Returns the conference page on conferencegrid.com plus its sponsor page and prospectus where the organiser publishes them. Direct organiser addresses are never returned. Events less than 21 days away are declined, because that is too late for an organiser to act on an approach.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Conference slug, from search_conferences. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive, so the description adds valuable behavior beyond them: it never returns direct organiser addresses, and it declines events less than 21 days away. It also clarifies that the sponsor page and prospectus are returned only when the organiser publishes them. There is no contradiction with the annotations.
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 four short sentences and every one earns its place: purpose, return content, privacy constraint, and date cutoff. It is front-loaded with the tool's purpose and keeps the most operationally important constraints near the end without padding.
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 one-parameter read-only tool with no output schema, the description is complete: it states what is returned, when the request is declined, and what is never returned. An agent can safely invoke it using a slug from search_conferences and understands the key failure condition in advance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the single slug parameter as 'Conference slug, from search_conferences,' so schema coverage is 100%. The description reinforces that the tool handles one conference at a time but adds no new detail about the parameter's format or source beyond what the schema provides. The baseline of 3 is appropriate here.
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 leads with a clear purpose ('reach the organiser of one conference') and then states specifically what it returns: the conference page, sponsor page, and prospectus where published. It also draws a firm boundary by saying direct organiser addresses are never returned. It does not explicitly distinguish itself from get_conference, which may also return a conference page, but the organiser-reaching framing makes the scope reasonably clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use case is clear: use this tool when you need to approach the organiser of a single conference indirectly. It also gives an explicit when-not condition: events less than 21 days away are declined. It does not name sibling alternatives such as get_conference or events_open_for_sponsorship, but the context is enough for an agent to infer when this tool applies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search conferences by free text: a city, a topic, a company or a conference name. Returns up to 10 results as id, title and url. Pass an id to fetch for the full record.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | What to look for. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral detail: results are capped at 10, each result includes id, title, and url, and a follow-up fetch is needed for full records. No contradiction with annotations exists.
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 short sentences cover purpose, output behavior, and follow-up action without filler. The description is front-loaded with the operation and scope, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one required parameter and no output schema, the description covers query semantics, result limit, result fields, and the next step for full records. The main omission is guidance on empty results and explicit differentiation from the similarly named 'search_conferences' sibling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes 'query' only as 'What to look for,' which is generic. The tool description enriches this by enumerating valid query types: city, topic, company, or conference name. This gives the agent practical guidance on how to form a useful query.
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: 'Search conferences by free text', and details the output shape. It is clear, but it does not explicitly distinguish itself from the sibling tool 'search_conferences', which appears to overlap in purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly sets the context: use this tool for free-text conference searches by city, topic, company, or name. It also instructs the agent to pass an id to fetch full records, but it does not explicitly say when not to use this tool or how to choose between this and 'search_conferences'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find upcoming B2B conferences by city, country, topic or date window. Returns up to 25 by default, 100 at most, soonest first. Every record carries the date we last verified it. An empty result means no match in the window asked for, not that the market is empty.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | Latest start date, YYYY-MM-DD. | |
| city | No | City name, e.g. Berlin. | |
| from | No | Earliest start date, YYYY-MM-DD. Defaults to today. | |
| limit | No | Rows to return. Default 25, maximum 100. | |
| topic | No | Topic or industry, e.g. devops, fintech. | |
| country | No | Two-letter country code, e.g. DE. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnly/idempotent annotations, the description reveals meaningful behavior: default 25 and maximum 100 results, soonest-first ordering, a per-record verification date, and exact semantics of an empty result. This materially improves an agent's ability to interpret 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?
Three short sentences front-load the core purpose and then add limit, ordering, freshness, and empty-result semantics in order of importance. Every sentence earns its place with no repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only, optional-parameter search tool with no output schema, the description covers what an agent needs before calling: filters, result cap, ordering, freshness marker, and empty-result meaning. It is self-contained enough to select and 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 coverage is 100%, so every parameter is already documented with type, example, and default. The description restates limit behavior and loosely groups filters into 'city, country, topic or date window' but does not add 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?
The description opens with a specific action ('Find upcoming B2B conferences') and names the key search dimensions, so an agent knows exactly what resource is being searched. It does not explicitly contrast itself with sibling tools like get_conference, company_events, or the generic search, so full sibling differentiation is left to inference.
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 intended use is clear from 'Find upcoming B2B conferences by city, country, topic or date window,' and the last sentence tells the agent how to interpret an empty result. However, it gives no guidance about when to prefer search_conferences over related siblings or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Changes for one company or one conference since a date: sponsors, exhibitors and speakers that appeared, and editions that were edited. Up to 50 by default, 100 at most, newest first. Honest limit: this reports records that appeared, not records that were edited, so a sponsor moving from silver to gold does not show up here.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | Conference slug to watch. | |
| limit | No | Rows to return. Default 50, maximum 100. | |
| since | No | ISO date or timestamp. Defaults to 30 days ago. | |
| company | No | Company name or domain to watch. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Even with readOnlyHint and idempotentHint annotations, the description adds important behavioral detail: default limit of 50, maximum of 100, newest-first ordering, and the crucial appeared-vs-edited distinction. This prevents false expectations about what 'what's new' means. No contradiction with annotations exists.
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-load the core purpose, then state constraints (limit, ordering), then close with an honest caveat. Every sentence earns its place with no filler or repetition of schema fields.
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 no output schema, the description carries the burden of explaining what the agent will get, and it does so for the key dimensions: scope, record categories, ordering, limits, and semantic boundary. It does not specify the exact response shape or behavior when neither slug nor company is provided, but these are minor for a simple change-feed 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 coverage is 100%, so the schema already documents all four parameters. The description reinforces that slug and company correspond to 'one company or one conference' but adds no per-parameter semantics beyond what the schema provides. 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?
The description states a specific query resource—changes since a date for one company or conference—and enumerates exact record types: sponsors, exhibitors, speakers that appeared, and editions that were edited. This clearly differentiates it from sibling tools like company_events or search_conferences by scope and change-tracking angle. The 'Honest limit' caveat further sharpens what the tool does and does not report.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this for one company or conference over a date range, with concrete defaults and limits. It also explicitly warns that sponsor tier changes won't appear, helping agents avoid using it for edit-detection. It does not name sibling alternatives, so it stops short of explicit when-to-use-versus-other-tools guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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