GTM Daily

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 a genuine behavioral guarantee not present in annotations: missing facts come back as null/unknown rather than being inferred, telling the agent it can trust gaps in the output. Nothing is said about ordering of results or whether an unpublished/invalid ID errors or returns a null row.

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 core scope (2-4 tools, side-by-side) front-loaded and the data-integrity guarantee second. Nothing could be removed without losing 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?

An output schema exists, so return values need no explanation, and annotations cover safety. Still missing for a comparison tool: what use_case does to the result, whether compared tools should share a category, and how invalid or unpublished IDs are surfaced.

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

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

Schema description coverage is 0%, so the description carries the burden. It partially compensates for tool_ids by restating the 2-4 count and the 'published' constraint, but the optional use_case parameter (max 60 chars) is never mentioned and its effect on the comparison is entirely opaque.

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?

Names a specific operation (side-by-side comparison) on a specific resource (published GTM tools) and bounds the input size (2 to 4), which implicitly distinguishes it from get_gtm_tool (single tool) and search_gtm_tools (discovery). It never names a sibling outright, and 'facts' leaves the dimensions compared unspecified.

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 '2 to 4 published tools' framing implies this is the multi-tool comparison path, but there is no explicit when-to-use statement and no mention of when to prefer search_gtm_tools to find IDs first or get_gtm_tool for a single record.

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?

Beyond the annotations, it discloses the conditional behavior: check whether connected, then start sign-in if not. It also explains why connecting matters by listing unlocked capabilities. It does not detail the sign-in flow mechanics, but annotations already cover the safety profile and an output schema 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?

The description is front-loaded with the core behavior and uses three concise sentences. The unlock list is relevant motivation 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 annotations covering safety and an output schema documenting returns, the description is largely complete for a no-parameter auth-status tool. A minor gap is that it does not clarify what 'start sign-in' looks like to the caller, but this is not essential for selection.

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

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

The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and the empty schema is consistent with that.

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 check-and-conditional-sign-in behavior for a GTM Daily account, which is clearly distinct from the public data/search siblings. An agent can tell this is the personal-account authentication/status tool without opening the 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?

It gives a clear usage trigger: 'Call this when the person asks for something personal.' It does not explicitly name when not to use it or list alternatives, but no sibling tool appears to serve the same authentication purpose.

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 this as a read-only, idempotent, non-destructive, closed-world operation. The description adds useful context that only approved creators are covered and that the result is a public portfolio containing bio, links, and published content, but it does not describe lookup failure behavior or other operational details.

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 a single, front-loaded sentence with no wasted wording. It efficiently conveys the resource, access scope, and returned components.

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 need not enumerate return fields, and annotations cover safety semantics. Still, for a required slug-based lookup, the description leaves the parameter meaning and the relationship to search_creators underexplained.

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 input schema has 0% description coverage for the single required slug parameter, and its only constraint is maxLength. The description implies that a creator can be identified, likely via slug, but does not explain what a slug is, its format, case sensitivity, or whether it refers to an approved creator identifier.

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 resource and scope: a public portfolio for an approved creator containing bio, links, and published content. It is clear what the tool returns, though it does not explicitly distinguish the read-by-slug behavior from the sibling search_creators tool.

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 phrase 'approved creator' implies this tool is for fetching an existing approved creator's profile rather than searching for creators. However, there is no explicit guidance on when to use this instead of search_creators or what happens for unapproved or unknown creators.

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 fully covered. The description adds one genuine behavioral detail — 'published' implies unpublished or unknown slugs return nothing — but says nothing about what happens on a miss or how much data 'full' entails.

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?

One sentence, no waste, with the resource and the accepted key forms front-loaded. Nothing in it is redundant with the title.

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 with an output schema and full annotation coverage, very little is required. The output schema carries the return shape and the annotations carry the semantics; only failure behavior for unpublished agencies is 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 coverage is 0%, so the description must carry the burden, and it does the important part: 'by slug or id' tells the agent the single string parameter accepts two identifier forms, which the bare schema (string, maxLength 200) does not reveal. It does not give format or example values.

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 scope: 'full public profile of a published agency or consultant', with the lookup key named ('by slug or id'). The word 'full' distinguishes it from the listing sibling search_gtm_agencies, though that sibling is never 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?

Usage is only implied: the agent must infer this is the detail-fetch step that follows a search_gtm_agencies result. There is no explicit when-to-use, no statement that it should be called with an id obtained from search, and no exclusion of alternatives.

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

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

The readOnly/idempotent/openWorld annotations already cover the safety profile, so the description only needs to add interpretive context, which the causality caveat does well. It does not disclose what happens when the optional from/to are omitted — a notable behavioral gap for a windowed aggregate whose parameters are both optional.

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: the first defines the measure and its dimensions, the second supplies use and caveat. No filler, no repetition of the name.

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 need not be explained, and the interpretive caveat handles misuse. The remaining hole is the unspecified time-window parameters (format, defaults, optionality) in a tool whose entire behavior is defined by that window.

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

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

Schema coverage is 0%: 'from' and 'to' are bare strings capped at 40 chars with no descriptions and no required flag. The description only says 'in a window', adding no date format, default range, or inclusivity semantics, so an agent cannot reliably construct the call.

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 (public GTM Daily content), a specific measure (how much was published), and a scope (in a window, by topic and format). The reference to 'next to job demand' implicitly distinguishes it from the job-market sibling, though no sibling is named outright.

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

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

'Useful next to job demand to spot topics with little coverage' gives a concrete use case and pairing; 'it does not prove demand or causality' is an explicit negative constraint on interpretation. What's missing is any when-not guidance (e.g., when to prefer the job market or trends tools instead).

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 genuine behavioral context beyond that: results include provenance and stated limitations, and private/non-public items are returned as not-found rather than erroring — a meaningful disclosure for an evidence 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?

A single tight sentence with the cap and the provenance guarantee front-loaded and the not-found behavior as a trailing caveat. Nothing is 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?

With an output schema present, return-value explanation is unnecessary, and the batch/citation framing is adequate. However, the undocumented include_linked_public_evidence flag and the lack of any routing guidance against 30 sibling tools leave real gaps for an agent deciding how to call this.

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

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

Schema description coverage is 0%, so the description must carry parameter meaning and does not. It restates the maxItems=15 cap already in the schema, but never explains the include_linked_public_evidence toggle or what the seven entity_type enum values mean, leaving the second parameter entirely opaque.

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 concrete operation and resource: batched retrieval of public records for up to 15 entity references, returned with provenance and limitations. It is clear what the tool produces, though it never distinguishes itself from siblings like get_gtm_related_records or get_public_record_updates that plausibly overlap.

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 phrase 'so you can cite them' implies the citation/evidence-gathering use case, and the not-found note hints at a public-records-only scope. But there is no explicit when-to-use versus alternatives, and no mention of any of the many sibling retrieval 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?

Beyond the read-only and idempotent annotations, the description discloses a major behavior: super admins receive exact counts with denominators, while everyone else receives only a ranked summary with relative levels and no counts or sample sizes. It also instructs the agent never to state unreturned numbers and to redirect exact-figure requests to Neel at GTM Daily.

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

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

The description is front-loaded and appropriately sized: the first sentence states the data returned, the second explains role-dependent output, and the third gives the critical handling rule for exact numbers. There is no wasted text.

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

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

The description covers the key behavioral caveats and the output schema exists, so return values need not be explained. However, with eight parameters and zero schema descriptions, the definition still leaves meaningful invocation gaps around parameter formats, defaults, and limits.

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

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

With 0% schema description coverage, the description partially compensates by naming the main analytical dimensions: window, tool, role, region, seniority, and example jobs. It still omits parameter-level details such as date formats, defaults, array limits, and the exact mapping of terms like 'tool' to schema fields such as skill_ids.

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 that this returns job demand in a window by tool, role, region, and seniority, with linked open jobs as examples. It does not explicitly distinguish this from close siblings like get_gtm_tool_market_data or search_jobs, so it is clear but lacks sibling differentiation.

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 the tool is for job-demand windows and gives important operational guidance about exact versus relative data and how to answer exact-figure requests. However, it does not explicitly say when to use this instead of alternatives such as search_jobs or get_gtm_tool_market_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?

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds one genuine behavioral signal — that this returns an 'opened' launch and includes votes and public comments — but says nothing about lookup failure behavior or access requirements.

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?

It is a single short fragment with zero padding, which is efficient, but it is under-specified rather than front-loaded: the reader gets a field list before learning what the tool does with the identifier.

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?

Complexity is low (one required parameter, read-only, output schema present so return values need no explanation), and annotations carry the safety profile. Still, the definition omits how to identify the launch and the meaning of the 'opened' qualifier, so it is only minimally sufficient.

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

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

Schema description coverage is 0% and the single required parameter launch_slug is undocumented; the description never mentions it, its format, or where the agent obtains one. With a low-coverage schema the description is expected to compensate for the gap, and it does not.

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 fragment 'A launch that has opened: pitch, what is new, maker listing, votes and public comments' conveys the resource and the record's contents, but it lacks a verb and never states that it retrieves a single launch by identifier. It only implicitly distinguishes itself from the sibling search_gtm_launches (single record vs. search), leaving the agent to infer the distinction.

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?

There is no when-to-use guidance at all: no mention of search_gtm_launches as the alternative when the slug is unknown, and no prerequisites such as holding a valid launch_slug. The word 'opened' hints at a state constraint but never explains it or says what happens for unopened/upcoming launches.

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 and side-effect expectations are covered. The description contributes the useful behavioral filter that only *active* categories are returned and that counts reflect *published* listings only, but says nothing about ordering, pagination, or completeness of the category set.

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 no filler or redundancy. It is efficient, though its brevity is partly the cause of the missing parameter and usage guidance noted elsewhere.

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 described, and annotations cover the safety profile. However, for a tool whose only differentiator is a tool/agency split, omitting that split from the description leaves a real gap for an agent choosing how to call it.

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

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

Schema description coverage is 0%, and the description never mentions the sole parameter entity_type or that it narrows results to tool vs agency categories. The enum values are self-describing, but the effect of the parameter (which category namespace is returned) is left entirely to inference.

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+resource ('Active directory categories') and adds a return-value detail ('number of published listings in each'), which clearly conveys a category-browsing tool. It does not name or differentiate itself from plausible siblings such as get_gtm_taxonomy or list_gtm_data_domains, so an agent could still confuse the two category-shaped tools.

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

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

There is no when-to-use statement, no exclusion, and no pointer to an alternative. The agent must infer from the word 'directory' that this is a discovery/browsing call rather than part of a search or taxonomy flow.

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 annotations already covering read-only safety, the description adds useful behavioral context: only published public data, no candidate-discovery opt-in, no private profiles, and no contact details. It does not contradict the annotations and meaningfully reduces privacy/scope uncertainty.

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 and front-loads the core purpose before the privacy caveats. It is efficient, though the hiring framing could be tighter relative to the actual returned data.

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 details need not be repeated, and annotations cover safety. However, for a three-parameter search tool with low schema coverage, the description leaves important gaps around query semantics and sibling-tool selection.

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 only 33%, so the description should compensate, but it only vaguely references tools/skills and does not explain the query parameter at all. The limit parameter is documented in schema only, leaving key filtering semantics under-specified.

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 resource and filter: public creator portfolios and published work mentioning given tools/skills. It is clear what the tool returns, but it does not explicitly distinguish itself from similar siblings such as search_creators or get_creator_profile.

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 hiring-oriented name and the tools/skills filter, but the description never says when to use this tool instead of search_creators or get_creator_profile. It does clarify exclusions around private/candidate-only data, but not selection guidance among alternatives.

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), so the description correctly spends its words on the trait annotations cannot express: the response shape branches by caller privilege, with admins getting denominators, sample sizes, coverage and methodology while others get relative levels only. That privilege-dependent output difference plus the 'zero is reported as zero' rule is real behavioral context an agent needs before calling.

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?

Roughly three sentences with little padding, and the privilege branching is placed early. However, the opening is the vaguest clause in the text, and the instruction to tell users data is available 'from Neel at GTM Daily' is a policy insertion that reads awkwardly alongside the behavioral description.

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?

Output schema exists, so return values need no explanation, and the caller-privilege behavior is well covered. But for a tool with 9 parameters and zero schema descriptions, an agent still has no idea what the filter arrays accept or how limit interacts with the ranked summary, which is a substantial 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 description coverage is 0% across 9 parameters, so the description must carry the load and it does not. Only the date window ('to'/'from') and the metric concept are touched; roles, regions, seniority, skill_ids, open_only and limit are never explained, and the 12-value metric enum is left entirely to 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?

It states a verb-plus-resource ('Trend counts over a date window') and adds that non-admin users receive a 'ranked summary of job metrics'. But 'trend counts' stays abstract and never says which data domain it reports on, and nothing distinguishes it from siblings like get_gtm_job_market_data or get_public_platform_stats in the listing.

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?

There is no statement of when to call this tool versus the many siblings, nor any prerequisite besides the implied admin status. The guidance present ('never invent counts', 'say the full data is available from Neel') governs how to present results, not when to select the tool.

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

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

The annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the description does not need to repeat safety details. It adds useful context by calling the links 'typed' and 'data-grounded', but it does not describe ordering, pagination, missing-record behavior, or result shape beyond what annotations and the output schema provide.

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 definition is a single front-loaded sentence that earns most of its length by enumerating the supported relationship types. It avoids repetition of annotation or schema fields, though the colon-and-semicolon list is dense and could be slightly easier 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 read-only related-records endpoint with an output schema, the description covers the key entity-to-relationship mapping and is sufficient to call the tool correctly. The main remaining gap is the meaning/format of the id parameter, which is mitigated by the required field name and the output schema.

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 only 33%, so the description must compensate for undocumented parameters. It does add meaningful semantics for entity_type by mapping each enum value to its relationship types, but it says nothing about the required id parameter's format or meaning beyond the obvious record identifier.

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 as typed links between public records and enumerates the concrete relationship types for each entity. It is distinguishable from sibling entity-fetch tools like get_gtm_tool or get_job_details, though the opening phrasing is more conceptual than an explicit verb such as 'returns related records'.

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 relationship list implies when the tool is useful: when an agent needs connections around a tool, job, creator, or launch. However, it does not explicitly say when to choose this over fetching the entity directly or using sibling search/profile tools, and it gives no exclusions or alternatives.

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 the tool as read-only, non-destructive, idempotent, and closed-world, covering the safety profile. The description adds that the vocabularies are normalized and include aliases, but does not disclose response format, caching, or other behavioral details beyond what annotations provide.

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 a single, efficient sentence that front-loads the resource being described. It wastes no words, though it could be slightly more structured by including a clear verb or explicit 'use this to' phrasing.

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

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

The tool is simple (2 optional parameters) and has an output schema, so the description needn't explain return values. However, with 0% parameter description coverage, the description should compensate more for the missing query and category semantics; it only partially covers category values.

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

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

Schema description coverage is 0%, so the description must clarify parameters. It lists seven of the eight category enum values (omitting pricing_models) but says nothing about the query parameter or the category filter itself, leaving significant gaps.

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 as normalized vocabularies with aliases across several domains, giving a specific sense of what the tool returns. However, it lacks a direct verb and does not differentiate itself from sibling tools like list_gtm_data_domains or get_gtm_marketplace_categories.

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 phrase 'so filters and tags line up across jobs, tools, agencies and resources', suggesting it's for aligning filter values. No explicit when-to-use or when-not-to-use guidance is provided, and alternatives are not mentioned.

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 read-only, idempotent, non-destructive, closed-world behavior, and the description still adds real substance: counts are rounded for non-super-admins, counts below 3 collapse into a band, and company names and raw job counts are withheld with an explicit 'do not guess them' instruction. What is missing is failure behavior for an unknown or unpublished slug.

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 clauses, front-loaded with what is returned and scoped immediately after by the access-tier and privacy caveats. Every sentence carries information an agent would otherwise get wrong, including the anti-hallucination warning.

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 need not be restated, and the description covers the non-obvious parts of the response: the hiring signal semantics and the deliberate omissions. It stops short of saying what happens for a missing or unpublished tool, which matters for a lookup-by-key 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?

The single parameter has 0% schema description coverage, but the description compensates by stating the key accepts either a slug or an id. That resolves the main ambiguity; it does not mention slug format or case sensitivity.

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 precise verb and resource — the full public profile of a published GTM tool — and adds the distinguishing payload (hiring signal). 'Published' and 'by slug or id' separate it cleanly from search_gtm_tools, which returns result sets rather than one full profile.

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 reader infers 'call this when you already hold a slug or id and want the complete profile' and otherwise use search_gtm_tools or compare_gtm_tools. No explicit when-to-use, when-not, or named alternative appears.

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

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

The annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds meaningful semantic context by clarifying that the data measures directory listings and activity rather than market share or adoption, which is behaviorally important for interpreting 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 two tightly written sentences with no repetition or filler. The signal list is front-loaded and the caveat about interpretation 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?

Because an output schema exists, the description need not explain return values, and the annotations cover the safety profile. Still, for correct invocation the description leaves the date-window parameters under-specified and does not route the agent among siblings, making it only minimally complete.

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 input schema has zero description coverage for the from and to parameters, and the description only says results are in a window. It does not explain accepted date formats, inclusive/exclusive boundaries, default window, or which parameter represents the start versus end.

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 identifies the resource and enumerates the signal types: tools by category and pricing model, declared integrations, launches, and published reviews. It lacks an explicit action verb and does not directly distinguish itself from sibling tools, so it is clear but not fully 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?

The description provides a scope exclusion by stating these signals measure listings and activity on GTM Daily, not market share or adoption. However, it never says when to use this tool instead of siblings such as search_gtm_tools, get_gtm_public_trends, or list_gtm_tool_reviews, so usage is only implied.

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 safety is covered. The description adds meaningful behavior beyond that: only *open* jobs are retrievable, and the payload returns an excerpt rather than the full posting plus an outbound link to the original page.

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?

One front-loaded sentence naming the action, the identifier input, and the returned content. Nothing is padded or repeated from the schema.

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 needn't enumerate return fields, and it still gives the gist (excerpt + link). It is nearly complete; only the not-found / closed-job behavior is 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 0%, so the description must carry the load — and it does clarify that the single parameter accepts either a slug or an id, which the schema's bare 'job_id_or_slug: string' does not spell out. The 200-character limit and format specifics remain undocumented.

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 (retrieve details) and resource (one job), scoped by slug or id, and distinguishes itself implicitly from the list-style sibling search_jobs. It stops short of naming that sibling explicitly, so the differentiation is inferable rather than stated.

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 — you'd call this after finding a job via search_jobs or when you already hold an id/slug — but the description never says when to prefer this over search_jobs or what to do if the job is closed. No exclusions or prerequisites are 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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds only that the result concerns reading/subscribing locations — no mention of staleness, external links, or side effects (e.g. whether subscription is performed or merely pointed to).

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 short sentence with no filler and no burying of key information. It is not padded, though it is arguably under-specified rather than maximally efficient.

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

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

For a zero-parameter, read-only tool with an output schema and full annotation coverage, little description is required. Still, the reader cannot tell whether calling it yields URLs, an about-page summary, or subscription instructions, leaving a small but real 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?

The tool takes zero parameters and the schema is effectively empty, so there is nothing for the description to disambiguate. Baseline for a no-param tool 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 sentence identifies the resource (GTM Daily newsletter) and hints at the payload (where to read and subscribe), but there is no verb stating what the tool returns or does — an agent has to infer 'returns links/info' from 'Where to read and subscribe'. It is distinguishable from siblings by topic, but the operation itself is vague.

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?

No indication of when to call this versus sibling tools such as search_gtm_knowledge or get_resource, and no stated prerequisites or exclusions. The topic alone implicitly scopes it, which is the only guidance 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?

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the description isn't needed for safety. It does add genuine context beyond them: a 'right now' snapshot framing and the caveat that counts are exact, not estimated, which matters for how an agent should report the numbers.

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, front-loaded with the core purpose, with the accuracy caveat second. Every clause carries information; nothing is padded.

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 explained, and there are no parameters to document. However, for an aggregate-stats tool whose value depends on what is being counted, the description never enumerates the counted dimensions, which an agent would need to judge relevance against the many sibling data-domain tools.

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

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

The tool takes zero parameters, so there is nothing for the description to clarify; baseline 4 applies. No parameter confusion is possible.

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 (aggregate counts of published content on GTM Daily), which is clearly distinguishable from the entity-level siblings like get_gtm_tool or search_gtm_launches. It stops short of naming what categories of content are counted, leaving the scope of 'what is published' slightly open.

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 this is the overview/summary tool versus the record-level siblings, but the description never says when to reach for it instead of list_gtm_data_domains or get_gtm_public_trends, and names no alternatives.

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 beyond them by disclosing that withdrawn records are returned as tombstones with no content — a return-shape behavior an agent would otherwise trip over. It does not mention ordering or pagination behavior, 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?

Two sentences, no waste, and the core scope statement comes first with the tombstone caveat second. 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?

An output schema exists, so return values need not be spelled out, and the tombstone note covers the main edge case. Still missing is the format/interpretation of the required 'since' parameter and any hint about result ordering when using limit — meaningful gaps for a 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 description coverage is only 33% — just the limit parameter is documented in the schema. The description says 'since a time' but never gives the expected format for the required 'since' string (ISO timestamp? epoch? relative?), and the domain enum values carry no explanation. This is a real gap the description should have filled.

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 concrete resource and scope: 'public records created, changed or withdrawn since a time', which makes the delta/change-feed nature of the tool obvious. It is clear what is returned, but it does not distinguish itself from siblings such as search_resources or get_gtm_related_records, so an agent must infer it is the incremental-sync variant.

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?

'Since a time' strongly implies polling for changes after a checkpoint, which is implicit usage guidance. However, there is no explicit statement of when to prefer this over search_* or get_* sibling tools, and no noted prerequisites or exclusions.

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 behavior, so the safety profile is covered. The description adds a genuinely non-obvious behavioral trait beyond that: full text is returned only for ungated content, warning the agent that a successful call may yield partial content.

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, no filler, and the lookup key explanation precedes the gating caveat. Every clause carries information the agent needs.

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, return values needn't be explained, and the gating caveat covers the main content-shape surprise. Minor gaps: no mention of not-found behavior or whether gated resources return metadata at all, which matters for a closed-world single-item fetch.

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

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

Schema description coverage is 0%, so the description carries the full burden, and it does well: it identifies both required parameters and explains that creator_slug and slug are the two segments of the resource's GTM Daily URL. It stops short of stating format constraints (case, allowed characters) beyond the schema's maxLength.

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 one published resource') and pins down the identity mechanism: two slugs that form the GTM Daily URL. This differentiates it from the discovery-side sibling search_resources, though the description never names that sibling explicitly, so differentiation is implied rather than stated.

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 URL-parts framing implies this is a direct-lookup tool used when you already have a resource's URL, which is useful routing context. However, it never says when not to use it or points to search_resources for discovery, leaving the agent to infer the split.

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, destructiveHint=false and closed-world behavior, so safety is fully covered. The description adds that results include caveats and the tools that read each domain, but with an output schema present it does not need to enumerate return shape; no auth, rate, or freshness behavior is disclosed.

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 contents and closing with the call-to-action. Every clause adds distinct information and nothing is repeated from 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?

For a zero-parameter discovery tool with full annotation coverage and an output schema, the description supplies the two things structured fields cannot: what the catalog contains and when to invoke it first. It is nearly complete; only a hint about what to do after reading the catalog (which sibling to call next) 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the schema cannot be enriched. Baseline for a no-parameter tool is 4.

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 — the catalog of public GTM data domains — and enumerates what it covers (filters, id/URL patterns, timestamps, caveats, reading tools), which separates it from sibling retrieval/search tools. It is a noun phrase rather than a verb-led statement of action, so the 'what it does' is implied as a listing/discovery call rather than stated outright.

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?

'Start here when unsure what to ask for' gives an explicit entry-point condition that no sibling offers. It does not name when to skip it or which sibling to go to once the domain is known, but the positive routing guidance is 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, closed-world behavior, so the bar is lower. The description earns some credit for disclosing that only published reviews are returned and that private proof is redacted, which is real policy context beyond the annotations. It stops short of saying what happens on a nonexistent entity_id or how pagination terminates.

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 the core scope front-loaded and zero filler. It is efficiently written, though the brevity is partly a symptom of omitted parameter guidance rather than disciplined restraint.

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 and rich annotations carry the return-value and safety burden, so the description needn't explain response shape. It is still thin for a paginated, sortable, parameterized list endpoint — nothing tells the agent which id space entity_id belongs to or how sort affects results.

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

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

Schema coverage is 0% across three parameters; the description never explains that entity_id is the listing UUID, that page is 1-100, or what "high"/"low" sort actually keys on (presumably rating). With no schema descriptions to lean on, this is the tool's biggest 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?

The description identifies the resource precisely — published reviews of a listing — and the name supplies the verb (list). "Listing" is slightly ambiguous versus the sibling set's "tool" terminology, but no sibling offers reviews, so an agent can place it uniquely.

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?

No when-to-use guidance, no mention of prerequisites (e.g., that entity_id must be a tool/listing UUID), and no note on how to page or when to pick a sort order. The agent is left to infer everything about invocation context from the schema.

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 this as a safe, read-only, idempotent search. The description adds useful scope: results are 'approved public' profiles and 'No private contact details are returned'. It does not describe pagination behavior, ranking, or rate limits, but the privacy note is meaningful 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?

Two short sentences, front-loaded with the core action and resource. The privacy constraint is placed immediately after and 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?

The output schema exists, so return shape need not be explained, and annotations cover safety. However, for a search tool with many search/get siblings, the description is missing routing guidance and does not fully explain how query and topic interact. It is adequate but incomplete for correct tool selection.

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%: limit and cursor are documented in the schema, while query and topic have no per-parameter descriptions. The description partially compensates by saying search works 'by name, headline or topic', which clarifies what query and topic match, but it does not explain their exact relationship or syntax.

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: 'Search approved public creator profiles'. It also narrows the searchable fields to name, headline or topic. It does not distinguish itself from the closely related sibling get_creator_profile or from other search_* tools.

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

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

The description implies it is for searching creators, but gives no explicit when-to-use guidance. It never mentions when to use this instead of get_creator_profile, search_jobs, or the many other search_* 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 declare readOnly/idempotent/non-destructive/closed-world, so safety is covered. The description adds two useful behavioral facts: results are limited to published listings, and sponsored placements never influence ordering — a meaningful disclosure about result composition. It says nothing about pagination behavior or result volume, which would have raised the score.

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

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

Two short sentences, front-loaded with the purpose, with no filler. The second sentence earns its place by disclosing ranking integrity, though it occupies the slot where filter guidance would have been more useful.

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 described. But for a 9-parameter faceted search with 44% schema coverage, the description leaves the agent guessing about sort semantics, filter value vocabularies, and how this search relates to the single-record get_gtm_agency 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?

Schema description coverage is only 44% across 9 parameters, so the description is expected to compensate — and it adds nothing. Unexplained semantics remain: what 'picks', 'saved', 'reviewed' mean for sort, what values region/service/delivery_model accept, and what 'published' implies for filtering.

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: 'Search published GTM Engineering agencies and consultants.' That is clearly distinct from get_gtm_agency (single record) and search_gtm_tools (tools, not agencies). It doesn't explicitly name a sibling to contrast with, so it stops 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?

There is no guidance on when to use this vs. get_gtm_agency, search_gtm_tools, or compare_gtm_tools, and no advice on which of the 9 optional filters to combine. The only contextual sentence concerns sponsored placements, which is a ranking property, not a usage 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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description does not need to restate that. It adds meaningful behavior beyond the annotations: every result is a cited public record, and visibility is applied before text is searched or excerpted, which is important context for an agent using public search.

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 compact sentences with no wasted wording. It front-loads the core action and domain scope, then adds the most important behavioral caveat about visibility and citation.

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 does not need to explain return values, and annotations cover safety semantics. The description gives enough scope and behavioral context to call the tool correctly, though explicit guidance on broad versus domain-specific search would make it more complete given the large sibling set.

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%: limit and cursor are described in the schema, while query and domains lack schema descriptions. The description lists the valid domain values, which reinforces the domains parameter, but it does not explain query behavior, matching scope, or syntax beyond the general statement that text is searched.

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: 'One search across public GTM Daily domains,' and enumerates the covered domains (resources, jobs, tools, agencies, launches, insights). This makes the tool's scope clear, though it only implicitly distinguishes itself from the many domain-specific search siblings rather than naming them.

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 phrase 'One search across public GTM Daily domains' implies this is the broad, cross-domain search option, which is useful context. However, it does not explicitly say when to use this versus siblings like search_gtm_tools, search_jobs, or search_resources, nor does it state any exclusions.

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, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds real behavioral value by constraining the result set to opened launches and asserting vote counts are real, but it says nothing about pagination (the cursor/limit behavior) or the cost/size of queries.

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 with no filler, and the scope constraint leads. It is efficient but slightly backwards in structure — it opens with the result set rather than stating that this is a search over launches, which would orient the agent faster.

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 needn't be explained, and annotations cover safety. The remaining gap is functional: with 5 optional parameters and 40% schema coverage, the description should explain how date/sort/window interact with the opened-launches scope, and it does not.

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 only 40%: limit and cursor are documented in the schema, but date, sort (trending/newest/top/picks) and window (today/week/all) carry no meaning anywhere. The description compensates for none of these — an agent cannot tell what 'picks' or 'window=all' means relative to the opened/scheduled scope it describes.

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 scopes the resource precisely: launches that have opened (live or closed) with real vote counts, explicitly excluding scheduled launches. It never states the action verb ('search'/'list') or that it accepts filters like date, sort and window, so an agent must infer from the name that this is a filtered list tool rather than, say, a single-launch lookup like get_gtm_launch.

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 exclusion 'Scheduled launches are not listed' implies a when-not condition, which is useful. However, no alternative sibling is named (e.g., get_gtm_launch for a single launch's details, or search_gtm_knowledge for other content), so the routing decision is left to inference.

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 behavior, so the description's burden is lighter. It adds one genuinely useful behavioral fact — that sponsored placements are excluded from the ordering — which is not visible in annotations or schema. It says nothing about result ordering semantics for the sort enum, relevance behavior, or how the filters combine.

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 with zero waste and the ranking-integrity caveat front-loaded right after the core statement. The brevity is efficient, though it edges toward under-specification for an 8-parameter search tool.

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

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

An output schema exists, so return values need not be explained, but a multi-parameter search endpoint needs at least a note on how query and filters interact and what ordering the sort values produce. None of that is present, leaving the definition incomplete for its complexity.

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 only 38% across 8 parameters, and the description adds no parameter guidance at all. Sort, query, use_case, integration, and pricing_model are undocumented in both places, so the thin description fails to 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: 'Search published GTM tools'. It is implicit but not explicit how this differs from get_gtm_tool (single fetch) or compare_gtm_tools (comparison), so the 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 description gives no when-to-use guidance and names no alternatives among a large sibling set that includes get_gtm_tool, compare_gtm_tools, and search_gtm_knowledge. An agent must infer from the tool name alone whether to search first or fetch a specific tool by id.

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 non-destructive behavior, so the safety profile is covered. The description adds genuinely useful scope: what is excluded (closed, expired, draft, unreviewed). It says nothing about pagination mechanics or result ordering beyond what the cursor schema field already conveys.

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 positive scope is front-loaded and the exclusion clause follows immediately.

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 and annotations cover safety, so return values and side effects need not be explained. However, a search tool with eight optional filters and 38% schema coverage leaves the agent guessing at what query, seniority, and role_category accept, which the description could have addressed.

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 only 38%, and several parameters (query, seniority, role_category) are undocumented in both schema and description. The description supplies no parameter meaning at all, so it fails to 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 clear verb+resource ('Search ... GTM Engineering jobs') with a domain qualifier. It distinguishes itself from get_job_details by being a search rather than a detail fetch, though it does not name any 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?

No guidance on when to use this versus get_job_details or get_gtm_job_market_data, both of which are plausibly overlapping candidates. The only usage-adjacent content is a data-visibility rule, not a selection 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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds a genuine behavioral fact not in any structured field: gated items return metadata only, which materially shapes how an agent should interpret results. It stops short of disclosing pagination/cursor behavior or relevance ordering.

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 corpus definition is front-loaded and the gated-item caveat follows immediately, so both sentences earn their 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?

An output schema exists, so return values need not be described. However, with 5 parameters and none required, the description never says what an empty call does (browse-all vs error) or how cursor pagination works, which are the main ambiguities an agent faces here.

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 60%; the limit and cursor params are documented in-schema, but query and format carry no description. The description's content-type list only loosely maps to the format enum (it names 'guides' and 'blog posts' which are not enum values, and omits 'video' and 'collection'), and it says nothing about how query terms are matched.

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 — 'Search published GTM Daily resources' — plus an enumeration of content types (guides, playbooks, courses, blog posts) that tells an agent exactly what corpus is covered. It implicitly separates from the singular get_resource sibling, but does not explicitly distinguish itself from search_gtm_knowledge or search_gtm_launches, which are the closest fuzzy neighbors.

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: 'Search published...' vs the sibling get_resource suggests search-then-fetch, but the description never states when to pick this over search_gtm_knowledge, search_gtm_tools, or the singular get_resource. No exclusions, prerequisites, or query-required guidance are given.

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