64 Types: personality test

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real context by noting the payment happens on Lemon Squeezy and that the reply explains post-payment behavior, but with no output schema it stays vague about what the link actually is (URL form, expiry, whether the caller must be authenticated).

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 returned artifact and followed by the payment context. The phrasing is slightly telegraphic ("the reply says what happens after payment") but nothing is wasted.

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

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

For a one-parameter, read-only tool this is close to sufficient, and the payment-flow remark covers the return value loosely. It still leaves the agent guessing about the link's format and lifetime, which matters before handing something to a user.

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 is a single enum parameter with 100% schema description coverage, and the enum itself lists the product options. The description only restates that it is a "paid product" and adds no per-value meaning, 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?

The description names the exact resource returned (a checkout link) and its scope (one paid product), which is precise enough to distinguish it from get_pricing in the sibling list. It is a noun phrase rather than a verb+resource construction, but the intent is unambiguous.

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

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

"To hand to the user" gives a implied usage context and "They pay on Lemon Squeezy" sketches the flow, so an agent can infer this is a user-facing purchase step. However, it never states when to pick this over get_pricing, nor any 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 readOnlyHint=true and openWorldHint=false, so the safe-read profile is covered. The description adds that the response includes both free-tier facts and paid report prices with checkout links, which is useful content context, but says nothing about format, caching, or whether prices can change.

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 short with no wasted clauses, but it is a sentence fragment that leads with 'What is free' rather than an action, and the parenthetical 'the test, result and every type profile' is slightly ambiguous about what is returned.

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

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

With no output schema, the description carries the burden of explaining returns and does list the main content (free features plus paid reports with prices and links). However, it doesn't describe response shape or whether free and paid items come back in one structure, so an agent knows what's included but not how.

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 the baseline is 4 and there is no parameter semantics to explain. The description correctly implies a no-argument, unconditional lookup rather than suggesting any filters 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 identifies the resource (pricing: what's free vs. paid reports) but is a noun-phrase fragment with no verb, so it never explicitly says 'retrieve pricing.' It does convey scope that separates it from siblings like get_checkout_link, but the purpose reads more like a content inventory than a tool action.

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 call this versus get_checkout_link or the other pricing-adjacent siblings, despite get_checkout_link being an obvious alternative. There are no prerequisites or exclusions stated, leaving the agent to infer ordering from the description alone.

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 and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral context: the tool returns 62 specific test statements with a 1-5 scale and should be followed by score_test. It does not describe the exact return structure, but the content is clear.

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 content, followed by the required next action. Every clause carries useful information and there is no waste.

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 no output schema, the description supplies enough: what the 62 statements are, the answer scale, and the required follow-up call to score_test. No essential agent decision point is left unexplained.

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

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

The tool has zero parameters, so the baseline is 4. The description correctly adds no parameter details because none are needed, and the empty schema is consistent with the tool’s purpose.

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 exact resource: the 62 public-domain IPIP statements for the 64 Types test, including the Big Five and HEXACO Honesty-Humility dimensions and the 1-5 answer scale. It also distinguishes this tool from score_test by stating the workflow: ask each question, then score.

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 sequence — ask the user each statement, then call score_test — which routes the agent to the correct next tool. It does not explicitly state when not to use this tool or list exclusions, 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?

readOnlyHint=true and openWorldHint=false already cover the safety profile, and the description adds that the profile is research-backed and enumerates what it contains. It does not disclose behavior for invalid or partial codes (e.g. is a base code error-prone, are variants returned as a group).

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 with no boilerplate; the two accepted code shapes come before the content list. Dense but every clause contributes.

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 does the needed work by enumerating return content (traits, strengths, watch-outs, career, love, growth notes, link). Adequate for a single-parameter read tool, though nothing is said about response shape or missing-code handling.

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 parameter's schema description ('INTJ, or INTJ-CM') already carries the format guidance. The description restates both formats without adding new syntax, validation, or normalization rules.

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 the specific resource (a personality type profile) and the two input shapes (4-letter base like INTJ or a 64 Types code like INTJ-CM). Clear verb+resource, though the 'get' verb is implied rather than stated and no sibling is named.

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 accepted code formats, but the description never says when to call this instead of list_types (to discover valid codes) or score_test (to obtain a code in the first place). No when-not conditions are given.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description does add something annotations cannot: the shape of the returned records (names, taglines, links), which matters since there is no output schema. It says nothing about size or ordering, and the 20-vs-64 count discrepancy undercuts confidence in the result.

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 sentence fragment with no filler, which is good, but the fragment lacks a verb and its numbers contradict the title, so its brevity comes at the cost of clarity rather than from tight editing.

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 parameters and no output schema, the description carries the full burden of explaining what an agent gets back and how it relates to get_type_profile. It leaves the count conflict (20 vs 64) unresolved and gives no guidance on follow-up, so it is not complete enough for reliable 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?

The tool takes zero parameters, which is the baseline-4 case; there are no parameter semantics to explain. The description correctly implies a no-argument enumeration.

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 resource (base types and variants) and the fields returned (names, taglines, links), so the agent can infer it enumerates type entries. However, it omits an explicit verb and, more importantly, its counts (16 base + 4 variants = 20) conflict with the title's '64 types', leaving the scope of the result genuinely unclear.

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 versus the closely related sibling get_type_profile, which is the obvious alternative for per-type detail. The agent must infer that this is the bulk-listing entry point and that one should follow up with the profile 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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the description doesn't need to re-establish safety. It adds real behavioral context beyond the annotations: comparison against open norms of ~20,000 people, borderline-letter reporting, and generation of a shareable result link.

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, front-loaded with the action, followed by a compact enumeration of what comes back. Every clause earns its place by previewing a distinct return component.

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 compensates by enumerating the return payload (type code, trait percentiles, borderline letters, summary, share link). Nothing needed to call it correctly is missing for a single-parameter read tool.

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

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

Schema coverage is 100% and the single nested `answers` object is fully documented (question id -> 1..5 accuracy), so the schema does the heavy lifting. The description adds no format or validation detail beyond that, which is the expected baseline.

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

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

Specific verb (score) plus specific resource (the user's answers) and the exact output artifact ('64 Types type (e.g. INTJ-CM)'). It is clearly distinguishable from get_test_questions (which supplies the inputs) and get_type_profile (which looks up a type).

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 rather than stated: scoring follows answering the questions supplied by get_test_questions. There is no explicit when-to-use/when-not, and the dependency on get_test_questions is only conveyed through the input schema, not the description.

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