7IT Solutions

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). The description adds meaningful behavior: it computes strictly from supplied figures, applies a documented $47 default with its source and date, and returns break-even horizons of both 12 and 6 months. It does not mention rounding or currency assumptions, 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?

Front-loaded with the four outputs, then the input constraint, then the default cost with attribution. Dense but every clause carries information; the BLS attribution is slightly verbose but justified for a cost model.

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?

There is no output schema, so the description must convey return semantics, and it does: hours/month, cost/year, automatable share, and break-even budget at two horizons. Combined with the rich nested input schema, an agent has everything needed to call and interpret this 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 50%, and the description's handling of parameters largely restates schema content (hourly_cost default 47, copying_share as copying-not-judgment). It adds the rationale behind the default but no new syntax or constraints for the nested task fields, so baseline 3 is appropriate.

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

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

States specific computed outputs: monthly hours on repetitive tasks, annual cost, automatable share, and break-even budget at 12 and 6 months. An agent can tell exactly what this tool produces, and it is clearly distinct from the field-kit/guide/speed-test siblings.

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 description ('uses only the figures provided'), which signals it is a pure computation over caller-supplied data. However, there is no explicit when-to-use/when-not guidance or named alternative, and nothing about what to do if the user lacks task estimates.

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, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context by describing what the payload contains (full kit, ordered checks, rationale, usage, guide provenance), which annotations cannot convey. It does not discuss lookup-miss behavior, but that is a minor gap.

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

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

Two sentences, zero filler, with the return payload front-loaded and the input instruction second. Every clause 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?

There is no output schema, and the description compensates by enumerating exactly what the caller receives. For a single-param, read-only lookup whose annotations carry the safety profile, nothing an agent needs to invoke it correctly 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% and the single 'kit' parameter's schema description already explains slug-or-title-words with an example. The description repeats this rather than extending it (no fuzzy-match or ambiguity-resolution guidance), so baseline 3 is appropriate.

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

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

States a specific verb and resource ('Returns one 7IT Field Kit in full') and enumerates the returned contents (every check, reason it matters, grouping order, usage, source guide). The 'one' quantifier cleanly distinguishes it from the sibling list_field_kits.

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?

Explicitly routes the agent: 'Pass the slug from list_field_kits or words from the title,' which names the upstream sibling and the accepted input forms. It stops short of stating when-not to use it or how it relates to search_7it_guides, so it is clear context rather than a full when/when-not rule set.

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

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so safety is covered. The description adds genuinely useful context by enumerating what each returned item contains (title, one-line purpose, number of checks, link), which is not derivable from 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 sentences, front-loaded with the verb and resource, with the filter capability closing it out. The parenthetical example list is long but pays for itself by broadening semantic matching against real user queries.

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?

There is no output schema, and the description compensates by describing the shape of each returned item, which is exactly what an agent needs to decide whether to call this tool before get_field_kit. Nothing critical is missing for a one-parameter, read-only list operation.

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

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

Schema coverage is 100% and the single optional `topic` parameter is fully documented in the schema, including examples ('shopify', 'webhook', 'AI'). The description's 'optionally filter by a topic word' repeats that without adding syntax or matching behavior, so the baseline 3 applies.

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

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

The description names a specific verb (Lists) and resource (7IT Field Kits), then defines what a field kit actually is with concrete examples (webhook reliability, store speed audits, LLM production readiness). That goes well beyond the title. It does not explicitly contrast itself with siblings like get_field_kit or search_7it_guides, so it stops short of a 5.

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

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

The description hints at usage by saying 'Optionally filter by a topic word,' which tells the agent how to narrow results. However, it never says when to use this discovery tool versus search_7it_guides, or that get_field_kit is the follow-up for a single kit. Usage is implied rather than stated.

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

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuinely new context by stating what the response contains (best matches, a short excerpt, and a citable link), which is valuable given there is no output schema. It omits ranking behavior or result limits, 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, front-loaded with the verb and resource, and the second sentence usefully covers the return shape. The middle topical enumeration is somewhat list-heavy but does convey scope, so it largely 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 search tool with full schema coverage and no output schema, the description supplies the topic scope and return format an agent needs. It leaves minor gaps around result ranking and how the result cap interacts with queries.

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%, with both query and limit documented including bounds, so the schema carries the parameter burden. The description adds only indirect topical context for the query and nothing about the limit parameter, so the baseline 3 applies.

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

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

States a specific verb ("Searches") and resource ("7IT Solutions' guides and articles") and enumerates the topical scope, which cleanly separates it from siblings like estimate_automation_roi, get_field_kit, and test_store_speed.

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

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

Usage is only implied by the topic list – an agent can infer this is the tool for answering content questions, but there is no explicit when-to-use, when-not-to-use, or named alternative.

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, openWorld). The description adds real behavioral context beyond them: a 20-60 second latency window, the public-URL-only restriction, and a detailed enumeration of what the report contains. It does not mention rate limits or failure modes.

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

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

Front-loaded with the core action and the tool's output, with the timing and URL constraint placed at the end where they belong. It is a long run-on enumeration of report contents, but each clause conveys distinct, useful information 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 no output schema, the description fully carries the burden of explaining return values — score, content timing, responsiveness, layout shift, real-user data, third-party apps, platform detection, and ranked fixes. Combined with the timing and input constraint, an agent has everything needed to call and interpret 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 100%, so both parameters are already documented in the schema. The description restates the competitor limit ('up to two') and comparison purpose but adds no syntax or format detail beyond what the schema provides, matching the baseline for fully-covered schemas.

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 (runs Google PageSpeed Insights mobile lab test) and resource (public store/website), plus the scope of what it reports. None of the sibling tools overlap, so the agent can identify it immediately.

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

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

Gives clear usage context and constraints: 'only public web addresses are accepted' and an expected runtime of 20-60 seconds, plus the optional competitor comparison mode. It doesn't name an alternative tool or state when not to use it, but no sibling competes for this task.

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