Klevero

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 covered. The description adds value beyond them by disclosing what the payload actually is — a fixed official llms.txt summary — and enumerating the topics it contains, which compensates for the absence of an output schema. It stops short of saying whether the content is static or refreshed, or how large the response is.

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 verb and resource, with the enumerated contents carried in a compact parenthetical. Nothing is wasted and nothing essential is buried.

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, non-destructive retrieval with no output schema, the description covers the essentials: what is returned and what topics it spans. A note on whether the content is static versus live, or its language, would close the remaining 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, which is the baseline-4 case; there is nothing for the description to disambiguate. The description correctly implies a parameterless, single-shot retrieval.

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 ('döndürür') and a specific resource (the official llms.txt summary of the Klevero AI lesson-coach app), then enumerates its sections (what it is, target users, features, prices, privacy, FAQ). This makes the tool's output unmistakable. It does not explicitly contrast itself with siblings like klevero_konu_ara or klevero_not_getir, but the enumerated scope does the distinguishing implicitly.

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 'general overview' tool to call for orientation questions about Klevero. There is no explicit statement of when to use it, when to prefer klevero_konu_ara or klevero_not_getir, or any prerequisite/call-ordering guidance.

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 behavior beyond that: Turkish diacritic- and case-insensitive matching plus relevance ordering (names containing the term rank first), which shapes how the agent should interpret results. It does not address zero-result behavior or result paging beyond the limit parameter.

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?

Four tight sentences, front-loaded with purpose, then matching semantics, then return shape, then the hand-off to the sibling. No filler and nothing repeated from 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?

A simple read-only search over a bounded corpus with all three params documented and a declared output schema, so return-value detail is not the description's burden. Everything an agent needs to call this correctly and chain into klevero_not_getir is present.

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

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

Schema coverage is 100%, so the baseline would be 3; the description earns extra credit by explaining that matching is diacritic/case-insensitive and partial-in-name rather than exact, which directly informs how to phrase "sorgu". It says nothing about the seviye filter or sınır default that isn't already in 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?

States a specific verb ("arar") and resource ("herkese açık konu notları") and narrows the corpus to LGS/TYT/AYT/YDT and grades 5–12, so the agent knows exactly what is indexed. It also names the sibling klevero_not_getir as the follow-up step, distinguishing this search tool from the note-fetch tool without opening 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?

Clear routing: use this to find the topic, then hand the page address to klevero_not_getir for the note text — an explicit alternative with the condition that selects it. It stops short of stating when NOT to use it or how it differs from klevero_bilgi, so a small inference remains.

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 genuinely new context by disclosing that only the public part of the note is returned (summary and core concepts) and the rest stays in the app — a scope limit the annotations cannot express.

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 waste, with the return value and its limitation front-loaded before the input hint. Nothing is padded or repeated from 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?

With no output schema, the description carries the return-value burden and does so: Markdown format plus the exact subset of content returned. Minor gaps remain around error handling for invalid or private addresses, but an agent has enough to call it correctly.

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

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

Schema coverage is 100% and the single parameter already carries an example url. The description only restates the same url-or-path semantics, adding little beyond pointing at klevero_konu_ara as the producer of valid values, 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 (döndürür) and resource (bir Klevero konu notu sayfasının Markdown sürümü), and scopes it precisely to the public portion of the note. It also ties itself to the sibling klevero_konu_ara as the source of its input, so the agent can separate it from the other tools without opening any 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?

The description tells the agent where the input comes from — the url in a klevero_konu_ara result or a /notlar/… path — which implies the search-then-fetch workflow. It stops short of explicit when-not-to-use guidance or stating what happens for a private/unknown note.

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