Trimi Health plan, policy and verification facts

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

Annotations already declare read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real value beyond them by stating it takes no input and that a licensed provider, not the tool, decides individual eligibility, which prevents an agent from misusing it as an assessment endpoint.

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

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

Three short sentences, each doing distinct work: content, trigger, and limitation. The opening is a resource list rather than a verb-led statement of purpose, which is slightly less front-loaded than it could be, but there is no filler.

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

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

For a no-argument, read-only lookup with no output schema, the description covers what the tool returns and what it refuses to do. The only gap is the unresolved relationship with the state_availability sibling, which an agent might otherwise pick instead.

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 zero parameters the baseline is 4, and the description explicitly confirms 'Takes no input', which matches the empty schema with additionalProperties false. Nothing further is needed.

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 the concrete resources it returns: the eligibility statement, the 50-state provider network, and the states page. That is specific enough for an agent to know what content comes back, but it never distinguishes itself from the sibling state_availability, which appears to cover overlapping ground.

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

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

'Use when someone asks whether Trimi is available where they live or who can use it' gives a clear triggering condition, and 'does not assess any individual's eligibility' supplies an explicit when-not boundary. It stops short of routing between this tool and state_availability, leaving a genuine overlap unresolved.

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 access, so the safety profile is covered. The description adds real value beyond that by enumerating the four returned fields (effective monthly price, amount billed, commitment, renewal) — important since there is no output schema — plus the regulatory caveat about FDA approval.

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

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

Three short sentences, front-loaded with the output shape then the usage trigger. Minor waste: 'compounded' and the non-FDA-approved disclaimer appear twice, once in the description and once in the schema's parameter 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?

For a single-parameter read tool with no output schema, the description supplies what the schema cannot: exactly which four figures come back and what kind of question the tool answers. Nothing an agent needs in order to call 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 coverage is 100% and the enum already documents both products with the same non-FDA-approved caveat, so the description's restatement of the product options adds little. Baseline 3 applies when the schema does the heavy lifting.

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 ('All four billing terms for one Trimi product') and names the two products the tool covers, so the scope is clear at a glance. Sibling differentiation from list_plans is only implicit in the word 'one' — the description never names the alternative.

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

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

'Use when someone asks about a specific medication's plans' gives a genuine usage trigger, which is better than nothing. However, it never says when to use list_plans instead, or what happens if the caller should be looking at all plans rather than a single product.

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 openWorldHint=false, so safety is covered structurally. The description adds real value beyond that: it states the tool takes no input and clarifies that no actual sign-up occurs, which prevents the agent from treating it as a transactional action. It does not describe response format in detail, but it does enumerate the content delivered.

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

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

Three short sentences, front-loaded with the scope and content of the answer, then the usage cue, then the no-input constraint. Minor redundancy between the title-like opening and the usage line keeps it from being maximally tight, but nothing is wasteful.

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 compensates by listing what the answer contains (steps, payment timing, review time, shipping, start link), which is the key thing an agent needs to decide whether this tool answers a given user question. Adequate for a zero-parameter informational tool; only a minor gap on how the link should be presented.

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

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

There are zero parameters, which is the baseline-4 case. The description reinforces this by explicitly stating 'takes no input', so the agent will not attempt to pass arguments.

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 the specific content the tool returns: the four onboarding steps, payment timing, review time, shipping, and the start link. That is concrete enough for an agent to know this is the 'getting started / sign-up process' explainer. It does not explicitly contrast itself with siblings like policies or get_plan, so it stops short of a 5.

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

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

'Use when someone asks how to get started' gives a clear triggering condition, and 'there is no sign-up inside an AI assistant' pre-empts a likely misuse (trying to actually enroll). No explicit when-not / alternative-sibling routing is offered, so it is not a 5.

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, and non-destructive behavior, so the description only needs to add context. It does: it enumerates the return fields (effective monthly price, amount actually billed, term, commitment/renewal rule, inclusions) and adds a compliance caveat that compounded medications are not FDA-approved — useful for how an agent frames the answer.

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

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

Three tight sentences: what is returned, when to call it, and the input contract, followed by a brief disclaimer. The highest-value content (scope and return fields) is front-loaded with no filler.

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

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

With no output schema, the description carries the burden of describing returns and does so at the field level, which is enough to set expectations. It does not mention whether pricing varies by state (a live concern given the state_availability sibling) or result ordering, a minor gap.

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

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

There are zero parameters and the description states 'Takes no input,' which is the correct baseline for a no-arg tool. Nothing more is required or possible here.

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

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

States a specific verb (lists) and resource (plans) and scopes it: 'Every Trimi Health plan for compounded semaglutide and compounded tirzepatide.' The word 'Every' distinguishes it from the singular get_plan sibling without the agent needing to open either 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?

'Use when someone asks what Trimi offers or costs' gives a clear triggering condition, and the total-list framing implies get_plan is the alternative for a single plan. No explicit exclusions or sibling names are given, so it falls short of a 5.

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, closed-world, non-destructive, so the safety profile is covered. The description adds useful context the annotations don't: fixed set size (37), source-linked provenance, and no input required. It stops short of describing the shape of what comes back, which matters somewhat since there is no output schema.

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 sentence, front-loaded with the enumerating scope, followed by topic coverage and the routing rule. Every clause carries information an 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?

For a zero-param bulk-retrieval tool with read-only annotations, the description covers scope, size, and alternative. The only gap is the absence of any hint about the return payload's size/structure, which would help an agent decide whether to pull all 37 at once.

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?

Zero parameters, so baseline is 4. 'Takes no input' merely restates the empty schema rather than adding meaning, but nothing is missing.

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

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

States a specific verb+resource (list all of Trimi's reviewed answers) plus scope: 'every one of the 37', 'in one call'. It also names the topical sibling it differs from, so an agent can distinguish it from search_questions without inspecting either 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?

Explicit when-to-use ('when you need the whole reviewed set') and an explicit alternative ('use search_questions for one topic'). The exclusion is stated, not 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 readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered by structured data. The description adds real value beyond that by enumerating the facts returned (license #35264, regulator lookup route, Arora Health, LegitScript) and confirming 'takes no input', which is essentially the return contract given there is no output schema.

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?

Content is front-loaded and both sentences earn their place, though the first sentence is dense with parenthetical identifiers that slow parsing slightly. It is nonetheless short and waste-free.

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 what comes back, and it does by listing the four fact groups. An agent knows what it will get and that no arguments are required; only the exact response shape is left unspecified, which is minor for a static fact lookup.

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 zero parameters the baseline is 4, and the explicit 'Takes no input' removes any ambiguity about whether a company or pharmacy identifier should be supplied. No further parameter semantics are needed.

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

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

The description uses concrete verbs and resources: it returns company identity, the compounding pharmacy with a named regulator license number, the clinical network, and a LegitScript lookup. This is clearly distinct from siblings like get_plan, list_plans, and eligibility_and_states, so an agent can route 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 explicit triggers — 'whether Trimi is legitimate' or 'which pharmacy fills prescriptions' — which are actionable conditions. It does not name a sibling to defer to, but the subject matter is far enough from the plans/eligibility tools that confusion is unlikely.

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=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered structurally. The description adds only that it takes no input and that the content includes links to governing documents; it does not describe the return format or whether content is static/policy-versioned.

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 preamble, content scope front-loaded before the usage trigger. The first sentence is a dense list but each item maps to a real coverage area 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?

For a zero-parameter, read-only informational tool with a fully annotated safety profile and no output schema, the description covers content scope, use trigger, and input expectation. Nothing an agent needs in order to call it correctly is missing; the only soft gap is return shape, which the mention of linked governing documents partly addresses.

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?

Zero parameters, so the baseline is 4. 'Takes no input' explicitly confirms what the empty schema already implies, leaving no ambiguity about whether arguments are expected.

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 enumerates the exact content the tool returns (payment timing, price inclusions, renewal rules by plan length, refunds, compounding and safety disclosures) and names the resource via the title. It is a content-scoped information resource, distinguishable from siblings like get_plan or eligibility_and_states, though it never states the verb form (e.g., 'returns the policy documentation') 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?

It gives explicit trigger conditions: 'Use when someone asks about cancelling, refunds, renewal or risks.' That is clear positive guidance, but no exclusions or named alternatives — an agent asking about price itself might not know whether to use this or get_plan.

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 and non-destructive behavior, so the description's added value is the result shape: up to five matching Q&A pairs with sources and review dates, plus the corpus size of 37 answers. It doesn't say what an empty result looks like, but the behavioral picture is otherwise well covered.

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

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

Two tight sentences: the first front-loads scope, the second covers output and input guidance. Every clause carries information (corpus size, source/review metadata, example topics, privacy exclusion) with no filler.

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

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

For a one-parameter read tool with no output schema, the description supplies the return shape (five Q&A pairs with sources and review dates), the corpus boundary (37 reviewed answers), and an input safety constraint. An agent has everything needed to call it correctly and interpret 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 100% and the single query parameter is already documented, so the baseline would be 3. The description earns above baseline by supplying concrete example topics ("cancel annual plan", "which pharmacy") that show the expected granularity of the query, which the schema's generic wording does not convey.

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 (keyword search) and resource (Trimi's 37 reviewed, source-linked answers) with an explicit topical scope covering pricing, billing, eligibility, pharmacy, shipping, safety and switching. It does not explicitly name a sibling it is not (e.g., list_questions or policies), so differentiation is inferred from the topical keyword-search framing 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?

Gives concrete invocation guidance with example queries ("cancel annual plan", "which pharmacy") and an explicit exclusion ("do not include personal or health details"). It stops short of naming alternatives or when-not-to-use cases such as routing listing/browsing needs to list_questions 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 cover read-only, idempotent, non-destructive, closed-world, so the description adds value with content-level disclosure: results are quoted from Trimi's state page with the link, and the 'not FDA-approved' compounding caveat. It does not say what happens for an unknown or unsupported state input, which is the main remaining gap.

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

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

A single front-loaded sentence carries the availability answer, the ancillary billing/ordering content, the source attribution and the eligibility exclusion in order of importance, followed by two short disclaimer clauses. It is dense but each clause does work; the opening clause is slightly overpacked.

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 nonetheless tells the agent what comes back (state-page wording plus link) and what it explicitly does not decide (individual eligibility). Only the invalid/unsupported-state behavior and any fallback routing to eligibility_and_states are 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 coverage is 100% and the single state parameter already documents accepted forms (full name, two-letter abbreviation, slug) and the no-personal-details constraint. The description only says 'when someone names their state', adding little beyond the schema, so baseline 3 applies.

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

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

States a specific verb/resource/scope: whether residents of a named US state can get Trimi's evaluation for compounded semaglutide or tirzepatide, plus how ordering, billing and payment work there. It also returns the source's own wording and link, which tells the agent the output shape and distinguishes it from a generic lookup.

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

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

'Use when someone names their state' is an explicit trigger, and 'Does not assess any individual's eligibility; a licensed provider decides' draws a clear boundary against the eligibility_and_states sibling. It does not name that sibling directly or say what to call instead when the user asks about personal eligibility, so routing is left partly implicit.

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