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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds no behavioral context such as authentication needs, return format, or whether the ABN must be formatted in a particular way.

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 words. It is efficient, though its brevity contributes to the gaps in parameter and usage guidance.

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 two-parameter lookup tool with no output schema and zero schema description coverage, the description is incomplete. It leaves out ABN formatting, requiredness cues beyond the schema, and the role of api_key.

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 compensate but does not. It expands the acronym ABN, which adds slight meaning to the abn field, but it gives no format or validation details and never mentions the optional api_key parameter.

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 verb and resource: looking up an Australian Business Number. It is clear what the tool does, but it does not distinguish itself from the sibling tool abn_search.

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 tool versus alternatives such as abn_search. The only implied usage comes from the tool name and description, with no exclusions or prerequisites.

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, open-world and non-destructive, so the safety profile is covered. The description adds nothing beyond that: no note that the call hits a registry-backed external API, no mention of result limits, pagination, or that an API key is needed for auth.

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. It is terse rather than bloated, though the brevity comes at the cost of the missing information noted in other dimensions.

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 should say what a result contains (ABN, entity name, status, location), but it does not. Combined with zero schema coverage on both parameters and no auth note, an agent could call this correctly only by guessing.

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 compensate and it does not. The 'name' parameter is only implied by the phrase 'by name', and the 'api_key' parameter — an authentication credential — is not mentioned anywhere in the description or 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 and resource ('Search for Australian businesses by name'), which is clear on its own. It does not distinguish itself from the sibling abn_lookup, so an agent cannot tell from the description whether to search by name here or use the lookup 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?

No guidance on when to use this versus abn_lookup, no note that results are name-based fuzzy matches rather than exact ABN resolution, and no mention of prerequisites. The agent must infer everything from the tool name.

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 no annotations provided, the description carries full responsibility for behavioral disclosure. It does not indicate that the tool is read-only, any authentication requirements (though api_key is a parameter), rate limits, or what happens when parameters are omitted.

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?

While very concise (4 words), it is under-specified. It lacks structure to convey essential information about parameters, usage, or behavior. Conciseness without substance is not effective.

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?

Given 3 undocumented parameters, no output schema, and no annotations, the description is grossly incomplete. It fails to explain what the blacklist contains, how to use the parameters, or what the response format is.

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 adds no meaning to the three parameters (confidenceMinimum, limit, api_key). It does not explain how they affect the output or provide formatting details.

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 'Get the AbuseIPDB blacklist', which clearly identifies the action (get) and the resource (blacklist). It distinguishes from sibling tools like abuseipdb_check_ip and abuseipdb_report_ip, which operate on individual IPs.

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 no guidance on when to use this tool versus alternatives like abuseipdb_check_ip. It does not mention any prerequisites, such as needing an API key, which is a parameter but not described.

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 openWorldHint, so the safety profile is covered structurally. The description adds nothing further: no mention that this is a third-party abuse-report database, no rate-limit or API-key/quota notes, no indication of what confidence score or report count comes back.

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, no filler. It is efficient, but the brevity reflects under-specification rather than tightness.

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?

No output schema and no parameter documentation means the description is the only place to explain what a result looks like and how the lookback window or credentials work — and it covers none of that. For an external, key-required reputation lookup this is thin.

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 3 parameters, so the description must compensate and does not. The 'ip' parameter semantics are implied, but 'maxAgeInDays' (the report lookback window) and 'api_key' (an auth parameter) are completely undocumented anywhere — a real gap for an open-world external API 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?

The description names a specific verb ('Check') and resource ('an IP address') and states the question it answers: has this IP been reported for abuse. It does not differentiate from close siblings such as virustotal_scan_ip, ip_lookup, or abuseipdb_blacklist, which an agent must disambiguate on its own.

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 the sibling abuseipdb_report_ip (the write counterpart) or versus other IP-reputation tools (virustotal_scan_ip, ipinfo_lookup, ip_lookup). Usage is only implied by the verb 'check'.

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?

No annotations provided; description only indicates a write operation ('report') but lacks details on side effects, authentication needs, rate limits, or what happens after reporting.

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?

Single sentence is concise but overly brief for a tool with 4 parameters. Could include more detail without losing conciseness.

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 4 parameters, no output schema, and no annotations, the description is insufficient. It fails to explain required parameters like 'categories' format or optional parameters.

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 has 0% description coverage for parameters. Description does not explain 'categories', 'comment', or 'api_key' fields, leaving their meaning and format ambiguous.

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?

Description clearly states the action ('report') and resource ('abusive IP address' to AbuseIPDB), distinguishing it from sibling tools like abuseipdb_check_ip and abuseipdb_blacklist.

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 tool versus alternatives, such as checking an IP first or prerequisites like API key. Missing context for ideal usage.

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?

No annotations are provided, so the description carries the full burden. 'Compute the Ackermann function' says nothing about cost, recursion depth, or the practical explosion of values even at m=3-4, which is the single most important behavioral trait of this function. The schema's 'max 4' constraint is left unexplained rather than justified by compute cost.

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 waste. It is efficient, though its brevity reflects under-specification rather than disciplined conciseness.

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 pure-compute tool with no annotations and no output schema, the description should at minimum warn about the computational blowup and what the return value looks like. Neither is present, so an agent could plausibly call it with values that stall or return astronomically large integers without warning.

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%: m is documented as a non-negative integer with max 4, and n as a non-negative integer. The description adds no meaning 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?

Names a specific verb ('Compute') and a specific well-known mathematical function with its canonical notation A(m, n). No sibling is confusable (ack_handoff is an unrelated dispatch concept), but the description does nothing to distinguish scope or differentiate from other math compute tools like is_even or fibonacci_sequence beyond the name itself.

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 tool versus alternatives, no prerequisites, and no caution about the function's extreme growth rate. The agent must infer everything from the name 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=false, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavior: it posts a short reply into the original thread via the existing Boardroom post path and explicitly does not mutate todos or code — useful for an agent deciding whether this call has side effects.

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 purpose and the ACK-card framing, followed by when-to-use and scope exclusions. No filler or repeated 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?

No output schema exists, but the description explains the observable effect — a short reply posted in the original thread — and the scope boundaries. For a mutation tool whose annotations cover safety and idempotency, this is close to complete; only the response shape of a successful ACK is left implicit.

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 every parameter including the ACK fields is already documented in the schema. The description's mention of ownership, next action, ETA and blockers loosely echoes the param set but adds no format or constraint detail beyond what the schema supplies. 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 — replies to a Boardroom handoff with a structured ACK card — and names the exact payload its readers see (ownership, next action, ETA, blockers). An agent can distinguish it from generic post_message/comment_on siblings 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?

Gives concrete trigger conditions: message directly addressed to you, tagged handoff, or asking for receipt confirmation. It also delineates scope by stating it does not claim a todo or change code, though it stops short of naming the alternative tool (e.g. create_todo or claim_lane) to use 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?

No annotations are provided, so the description carries the full behavioral burden. 'List' implies a read-only, non-mutating operation and the description states the returned content, but it does not disclose pagination, rate limits, auth needs, or exact output behavior.

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 redundant or filler content. Every phrase contributes to identifying the resource and 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?

For a simple zero-parameter lookup, the description gives enough to know what it returns. But with no output schema and no annotations, 'availability and prices' remains high-level and does not fully explain the return format or what availability entails.

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 there is no parameter semantics for the description to clarify. Per the rubric, zero parameters establishes a baseline of 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 states a specific verb ('List'), a specific resource ('Animal Crossing: New Horizons bugs'), and the fields returned ('availability and prices'). It distinguishes itself from siblings such as acnh_fish and acnh_villagers by resource name.

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 resource: an agent should use this when it needs ACNH bug data. However, there is no explicit when-to-use guidance, no exclusions, and no mention of alternatives like acnh_fish or acnh_villagers.

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?

No annotations are provided, so the description carries the full burden. 'List all' implies a non-destructive read and 'availability and prices' hints at the returned fields, but nothing states whether results are paginated, filtered, or complete in one call. The gap is small for a zero-argument lookup, but the behavioral profile is only partially 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?

One sentence, front-loaded with the verb and resource, and it uses the remaining clause to name the useful return fields. No filler or redundancy.

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-parameter list tool with no output schema, the description gives the domain, the universe of items, and the two main attributes returned. An agent has enough to call it and interpret the result, though the exact record shape and result count remain undisclosed.

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 for the description to compensate for. Nothing in the description is needed or misleading regarding inputs.

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 (List), specific resource (Animal Crossing: New Horizons fish), and explicit scope (all) with the data returned (availability and prices). An agent can distinguish it from acnh_bugs and acnh_villagers purely from the resource noun, 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?

Usage is implied: it is the only fish tool among the acnh_* siblings, so there is no alternative to route away from and no explicit when-to-use statement. No exclusions or conditions are given, leaving only the inference that it is for looking up ACNH fish 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?

No annotations are provided, so the description carries the full burden. 'List all' communicates that this is a complete, read-only enumeration with no filtering or pagination, which is useful context. However, it says nothing about response size or item shape, leaving the mutation-free, totality claim as the only behavioral signal.

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 no filler. Every word earns its place for a tool this simple.

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 parameterless, read-only list tool with no output schema, the description is essentially sufficient — the agent knows it gets all villagers. It could be marginally stronger by noting the expected response type, but nothing essential to correct invocation 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 schema has zero parameters, so there is nothing for the description to document; the baseline for a 0-param tool is 4. The description correctly implies no inputs are required.

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 ('List') and resource ('Animal Crossing: New Horizons villagers'), so an agent can tell it returns the villager roster. It does not, however, distinguish itself from the sibling acnh_bugs and acnh_fish tools beyond the resource name.

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 name and the word 'all' — use this to get every villager with no filtering. There is no explicit when-to-use/when-not guidance or mention of alternatives, but for a parameterless list-all endpoint the intended use is fairly self-evident.

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?

No annotations are provided, so the description carries the full burden. It does disclose the key behavioral choice ('optionally skipping small words'), but for a pure text transform there is little risk to disclose, and it omits output formatting details (uppercase, punctuation, handling of non-letter tokens).

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 clause-dense sentence with the core action front-loaded and the optional behavior appended. 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 simple deterministic transform with no output schema and no annotations, the description covers input intent but says nothing about the returned form (e.g., 'NASA' vs 'N.A.S.A.', casing, list vs string). Adequate but with a clear 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?

Schema description coverage is 100%, so both parameters ('text' and 'include_small_words') are already documented, including the default of false. The description's mention of 'phrase' and 'small words' mirrors the schema without adding format or edge-case semantics.

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 a specific verb ('Generate') and resource ('acronym from a phrase'), so the agent knows exactly what the tool produces. There is no near-identical sibling (nearest neighbours like nato_convert or phonetic_spell do different transforms), so explicit differentiation is unnecessary.

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 alternatives (e.g., nato_convert, morse_convert, phonetic_spell) or any prerequisites. Usage is only implied by the purpose statement.

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=true. The description adds no behavioral context beyond the purpose statement, such as invalid-ID handling or return characteristics, so it provides little transparency beyond the structured 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?

The description is a single front-loaded sentence with no redundant or filler content. Every word contributes to identifying the operation.

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 simple read-only getter with full schema coverage and complete annotations, the description is nearly sufficient. It does not explain behavior when an ID is invalid, but the lack of an output schema and the annotation coverage make that 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?

Schema description coverage is 100%, and the single id parameter is documented as 'Advice slip ID'. The description's 'by ID' adds no format, type, or validation detail beyond the schema, so the 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 uses a specific verb (Get) and resource (advice slip) and adds the by-ID qualifier, which distinguishes it from siblings like advice_random and advice_search. It does not explicitly name those siblings, but the purpose 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?

The phrase 'by ID' implies the tool should be used when the caller already has an advice slip ID, but there is no explicit guidance on when to prefer advice_search or advice_random. Usage is inferable 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 readOnlyHint, destructiveHint=false, openWorldHint, and idempotentHint, so the safety profile is fully covered by structured data. The description adds nothing beyond that (no note that results vary per call, no indication of data source), which is acceptable but thin. Worth noting: idempotentHint=true sits oddly with a "random" tool whose output changes per invocation, though that is an annotation issue rather than a description contradiction.

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 the verb and resource front-loaded and zero filler. Nothing could be removed without losing meaning.

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 trivial no-parameter fetch, annotations carry the operational profile, so little is required. However, there is no output schema, so the description is the only place to indicate what the response looks like (a plain advice string), and it does not say.

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 of 4 applies; there is nothing for the description to document in this dimension.

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 a random piece of advice") that an agent can act on without opening the schema. It does not, however, explicitly differentiate itself from the sibling advice_search and advice_by_id tools, leaving the agent to infer that "random" is the distinguishing behavior.

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: "random" suggests use when you want a non-targeted pick, versus advice_search or advice_by_id for targeted retrieval. There is no explicit when-to-use or when-not-to-use statement, though for a zero-parameter novelty tool the inference is fairly safe.

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 and destructiveHint=false, so the safety profile is fully covered. The description adds only the keyword-matching nature of the query; it says nothing about result count, pagination, or whether matching is exact, substring, or fuzzy.

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 the verb and scoping qualifier front-loaded and no filler. It is efficient, though it leans so terse that it omits useful matching context rather than being exemplary.

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 search with full schema coverage and annotations, the essentials are present. Still missing is any indication of what the search returns or how many results, which matters even without an 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 description coverage is 100% and the sole parameter 'query' is documented as 'Search keyword'. The description's phrase 'by keyword' merely echoes the schema, adding no syntax, quoting, or matching-semantics detail. 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 and resource ('Search advice slips') plus the matching mode ('by keyword'), so the agent can tell it apart from random/by-id siblings like advice_random and advice_by_id. It doesn't explicitly name those alternatives, so the differentiation is inferred from the verb 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: use this when you have a keyword and want matching advice slips. There is no explicit when/when-not guidance or pointer to advice_random for unsolicited picks or advice_by_id for known identifiers.

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=true, idempotent=true, destructive=false, and openWorld=true, so the safety profile is fully covered by structured fields. The description adds no further behavior — notably it does not mention that a remote API is involved despite openWorldHint, nor any latency/failure behavior — but it also contradicts nothing.

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, front-loaded with the verb and resource, with no filler. Nothing could be removed without losing meaning.

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 trivial read-only, zero-parameter call with no output schema, the description covers everything needed to invoke it. The only gap is not hinting that the return value is a random affirmation string (and that repeated calls yield different results despite idempotentHint).

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; baseline 4 applies. The schema is empty with additionalProperties=false, matching the description's implication of a no-argument 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?

The description gives a specific verb plus resource ('Get a random positive affirmation'), which is unambiguous and distinguishable from quote/zen_quote/dadjoke siblings by resource alone. It does not explicitly name an alternative, but none of the siblings overlap on this resource.

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 case is only implied by the description text; there is no statement of when to prefer this over e.g. quote_random or zen_quote_random, nor any exclusion. For a zero-parameter novelty tool the implied usage is sufficient to act, which is the definition of a 3.

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?

No annotations provided, so the description carries full burden. It doesn't disclose that this is a statistical estimate (not a fact), what confidence/accuracy to expect, rate limits, or response structure. 'Predict' hints at estimation but no behavioral detail is given.

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?

Single, front-loaded sentence with zero waste. Appropriate length for a simple 2-param 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?

Adequate for a simple estimation tool, but with no annotations and no output schema, the description leaves the agent guessing about return format and the statistical nature of the prediction. Could note that results are estimates, not guarantees.

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 both parameters (name, country_id) are documented in the schema. The description adds no parameter-level detail beyond what's already there. 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+resource: predict age of a person from first name. Clear enough to distinguish from genderize_name/nationalize_name siblings, though it doesn't explicitly say it's name-based demographic estimation.

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 vs alternatives like genderize_predict or nationalize_predict, which are clearly analogous name-analysis tools in the sibling set. No exclusions or prerequisites 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 readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered. The description adds nothing about matching semantics that the annotations cannot: whether overlapping matches are reported, case sensitivity, how empty patterns or no-match cases behave, or what the response contains. With no output schema, these gaps matter.

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 with no filler, and the distinguishing qualifier (multiple patterns, simultaneously) is front-loaded. 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?

With no output schema, the description should say what a match looks like (positions, per-pattern grouping, counts), and it does not. Annotations carry the safety profile and the schema carries the inputs, so it is minimally viable but incomplete for a tool whose whole value is the shape of its result 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 description coverage is 100% for both required parameters, so the schema already explains 'text' and 'patterns'. The description adds no semantics beyond that — no note on ordering of results per pattern, case sensitivity, or array-vs-single-pattern behavior. 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 (find all occurrences of patterns in text) and pins down the distinguishing trait: multi-pattern, simultaneous matching, which separates it from single-pattern siblings like kmp_search or rabin_karp_search. It never names those siblings explicitly, so differentiation is inferential 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?

There is no when-to-use or when-not-to-use guidance. An agent gets no signal about preferring this over a single-pattern matcher, regex_test, or text_count_occurrences when it only has one pattern or wants counts rather than positions.

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, openWorld, and non-destructive behavior, so the safety profile is covered. The description adds the data source and that both an index and pollutant levels are returned, but says nothing about units, update cadence, coverage, or rate limits. Adequate given annotation coverage, but not rich.

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 well-formed sentence with the core purpose front-loaded and zero padding. It is sized appropriately for a two-parameter read tool, though it offers nothing beyond the minimum.

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 simple, annotation-covered, two-parameter read tool with a full schema and no output schema, the description covers the essentials: what is returned and from where. Missing are the units/dialect of the AQI scale and the differentiation from related air-quality siblings, which keeps it below a 5.

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 both parameters (latitude, longitude) are documented in the schema. The description adds no extra semantics such as accepted ranges, decimal precision, or whether coordinates must be land-based. 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 and resource ('Get current air quality index and pollutant levels') plus the upstream provider (Open-Meteo). It is clear what the tool does, but it does not distinguish itself from sibling air-quality tools such as openaq_air_quality or air_quality_forecast.

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 instead of openaq_air_quality (a different provider) or air_quality_forecast (future data). The agent must infer the split between 'current' and 'forecast', and between Open-Meteo and OpenAQ, on its own.

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, open-world, and non-destructive behavior, so the description does not need to restate those. It adds useful context that the output is hourly and sourced from Open-Meteo, but it does not disclose pollutants, units, coverage, or rate limits. The added value is modest but not contradictory.

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 with no filler or redundancy. Every word contributes to identifying the action, the data granularity, and the upstream source.

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 with three documented parameters and annotations covering safety. However, there is no output schema, and the description does not explain the returned forecast fields, pollutants, units, or spatial coverage. It is minimally sufficient to invoke the tool but not fully complete for interpreting 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 description coverage is 100%, and the schema already explains latitude, longitude, and days including the default and maximum. The description adds no parameter-specific meaning beyond the schema, so the baseline of 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 states a specific verb and resource: 'Get hourly air quality forecast.' It also names the source, Open-Meteo, which distinguishes it from OpenAQ-based siblings. However, it does not explicitly contrast with air_quality_current or weather_forecast, so sibling 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 description gives no explicit when-to-use guidance, prerequisites, or alternatives. An agent can infer it is for future air quality rather than current conditions, but the definition does not say when to choose it over air_quality_current, openaq_air_quality, or weather_forecast.

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 are absent, so the description must disclose behavioral traits. It only states that the tool interacts with the API and lists operations. It does not mention side effects of write actions, rate limits, authentication details, or the unified nature of the tool (action parameter decides behavior). Minimal behavioral disclosure beyond the 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?

The description is a single sentence, which is concise and front-loaded with the tool's purpose. While it could be slightly more structured, it avoids unnecessary verbosity and 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?

Given 11 parameters and no output schema or annotations, the description is too sparse. It does not mention parameter dependencies (e.g., base_id and table_name needed for most actions), pagination, or the overall flow of using this tool. Incomplete for a complex 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%, so the baseline is 3. The description lists action types but does not add significant meaning beyond the schema's parameter descriptions. It fails to explain how parameters relate to each action or provide context on usage patterns for the various parameters.

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 the tool interacts with the Airtable REST API and lists specific actions (list bases, list and search records, get a single record, create or update records). This provides a clear verb+resource mapping and distinguishes it from any potential Airtable-specific siblings (though none exist in this list).

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 tool vs alternatives. With no sibling Airtable tools, the description could still explain which action to choose and under what circumstances, but it doesn't. It also fails to mention prerequisites like needing an Airtable personal access token, though that is implied by the required parameter.

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?

No annotations provided, so description carries full burden. It only mentions pagination (cursor-based), but doesn't disclose read-only nature, auth expectations, rate limits, or handling of large datasets. For a browse operation, more behavioral context is needed.

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?

Single front-loaded sentence with verb, resource, and key feature (pagination). No redundant words, efficient and to the point.

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?

Despite 7 parameters and no output schema, the description is minimal. It doesn't explain cursor-based pagination fully, nor does it mention performance implications, error handling, or result format. More context would aid agent decision-making.

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% with parameter descriptions. The description adds no additional meaning beyond what's in the schema. Baseline 3 is appropriate as 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?

The description clearly states the verb 'Browse', the resource 'all records in an Algolia index', and notes pagination style 'paginated cursor-based'. This distinguishes it from siblings like algolia_search (search) and algolia_get_object (single object).

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 explicit when-to-use or when-not-to-use guidance. It implies use when you need all records, but doesn't compare to alternatives like algolia_search for filtered browsing. The context is clear but lacks 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?

The description indicates a read-only operation ('Retrieve'), which is transparent. However, with no annotations provided, it does not disclose other behavioral traits such as rate limits, authentication requirements beyond schema, or any side effects. The schema already covers credential parameters.

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, concise sentence (12 words) that front-loads the purpose and method. No unnecessary words or repetitions.

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 simple read operation with all parameters required and no output schema, the description is nearly complete. It covers the what and how. A minor improvement would be mentioning the return format (object), but this is not essential.

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% with all four parameters described. The description does not add meaning beyond the schema; it only reiterates the 'objectID' parameter. Baseline of 3 is appropriate as the schema carries the full burden.

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 the verb 'Retrieve' and the resource 'a single record from an Algolia index', and specifies the method 'by its objectID'. It distinguishes from sibling tools like algolia_search (multiple results) and algolia_browse_index (browse all 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 description implies usage when a specific objectID is known, but does not explicitly state when to use or avoid this tool, nor does it mention alternative tools like algolia_search for non-objectID lookups or algolia_browse_index for multiple records.

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 and destructiveHint=false, so the safety profile is fully covered. The description adds nothing beyond that structured data — no note on credential scope, rate limits, or whether results include full index metadata versus names only.

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 zero padding. It is efficient, though its brevity is partly the cause of the missing usage and behavioral context rather than a virtue of tight writing.

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?

No output schema exists, so the description could say what is returned (index names versus full index descriptors). For a simple two-parameter read with complete annotations, this is adequate but not 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?

Schema description coverage is 100%, with both app_id and api_key documented (including that an Admin key is required), so the schema carries the burden. The description does not mention either parameter, leaving it at the baseline for a fully documented 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 and resource ('List all Algolia indices') plus a scope ('in the application'), so the operation is unambiguous. It does not distinguish itself from siblings like algolia_browse_index or algolia_search, which an agent must infer from the names alone.

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 versus algolia_browse_index or algolia_search, nor any mention that an Admin API key is required or that this is typically the discovery step preceding a browse/search. The agent is left to infer usage entirely from the name.

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 no annotations provided, the description should disclose behavioral traits. It merely states the action without mentioning pagination, authentication requirements, rate limits, or what happens with no results. The description is too minimal to inform an agent of important behaviors.

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 concise sentence that is front-loaded with the key purpose. However, given the number of parameters and complexity, a bit more detail could be helpful without being verbose.

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 is incomplete for a tool with 8 parameters and no output schema. It does not explain behavior like pagination, filtering, or the nature of returned records. Compared to the complexity, more detail is needed.

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 the baseline is 3. The description does not add any additional meaning beyond the schema; it does not mention any parameters or their roles.

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 the verb 'Search' and the resource 'an Algolia index for records matching a query'. It distinguishes itself from sibling tools like algolia_browse_index and algolia_get_object by focusing on searching 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?

No guidance is provided on when to use this tool versus alternatives such as algolia_browse_index, algolia_get_object, or algolia_list_indices. The description lacks context for choosing this tool over others.

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, idlempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered by structured data. The description adds nothing beyond that: it doesn't mention that credentials (access_key, secret_key, partner_tag) must be supplied, whether results are paginated, or what the response contains. For a tool with credential parameters this silence is a meaningful 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?

The single sentence is front-loaded and free of padding, but at four parameters with no schema documentation it is drastically under-specified rather than truly concise. Brevity here is a symptom of underspecification, not economy.

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 four parameters, zero schema descriptions, no output schema, and no annotations covering authentication, the description should explain how to call the tool and where to get a browse node ID. It does neither, leaving the agent to guess at required credentials and identifier sourcing.

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 four parameters, so the description carries the full burden and fails. The required browseNodeId is never explained (what a browse node is, or how to obtain one), and the three credential parameters are entirely unmentioned. Compare to the calibration LOW case: undocumented params at 0% coverage score 1, and this tool has four of them.

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 verb ('Browse') and a resource ('Amazon product categories'), so the general purpose is inferable. But it doesn't explain what 'browse' yields versus sibling amazon_search or amazon_product, nor that the operation is scoped to a specific browseNodeId. An agent cannot tell from this sentence why it would pick this tool over amazon_search.

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 use this tool, no prerequisites, and no reference to the obvious alternative amazon_search for keyword lookups. The only usage signal is implicit in the phrase 'browse categories,' which the agent must interpret against the sibling list on its own.

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?

No annotations are provided, and the description does not mention any behavioral traits such as read-only nature, rate limits, or authentication 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?

The description is a single short sentence, but it lacks necessary detail; it is concise but under-specified.

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?

Given 5 parameters and no output schema, the description fails to explain what data is returned or how the optional parameters affect 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 has 0% description coverage for 5 parameters; the description only mentions 'ASIN', providing no meaning for access_key, secret_key, partner_tag, or region.

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 the action ('Get... product details') and the primary identifier ('by ASIN'), which distinguishes it from sibling tools like amazon_search.

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 tool versus other Amazon tools (e.g., amazon_search, amazon_browse) or how to handle authentication parameters.

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, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context beyond that: it does not explain credential requirements, rate limits, result limits, or how regions affect 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 single sentence is front-loaded and has no waste, but it is under-specified for a tool with seven parameters and authentication requirements. Brevity here reflects missing information rather than effective concision.

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 tool with 7 parameters, no output schema, and no schema descriptions, the description is far too thin. It omits authentication needs, regional behavior, item count semantics, search index usage, and expected output, leaving the agent without enough context to invoke the tool reliably.

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 7 parameters with 0% description coverage, including non-obvious fields such as access_key, secret_key, partner_tag, and searchIndex. The description does not explain any of these parameters or their expectations, so it fails to compensate for the schema 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 states a clear verb and resource: 'Search for products on Amazon.' This is enough to distinguish it from a get-product tool like amazon_product, but it does not explicitly name alternatives such as amazon_browse or amazon_variations, so 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?

There is no guidance on when to use this tool versus amazon_browse, amazon_product, or amazon_variations, nor any mention of prerequisites such as API credentials or regional constraints. The agent is left to infer usage from the name 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?

No annotations are provided, so the description must disclose behavior. It only states what the tool does, not how it behaves (e.g., what it returns, authentication requirements, rate limits). The description is too minimal to compensate for the lack of 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?

The description is a single sentence and is very short. While brevity can be good, it is under-specified and does not earn its place because it omits necessary details.

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?

Given the tool has 4 parameters (1 required, 0% schema coverage, no output schema, no annotations), the description is vastly insufficient. It does not explain the concept of variations, how to use auth parameters, or what the output format is.

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% (no parameter descriptions). The description does not explain any parameter, including the required 'asin' or optional auth fields. It adds no value beyond 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?

Clearly states the action (get), resource (Amazon product variations), and key input (ASIN). However, it does not differentiate from sibling tools like amazon_product or amazon_search, so the purpose is clear but not uniquely defined.

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 tool versus alternatives. Does not mention that this is for listing variations of a product, while amazon_product might be for single product details. No exclusions or context provided.

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 openWorld, so the safety profile is covered. The description adds only that the result is a 'current price' and scoped to a site; it says nothing about auth requirements, error behavior, or return shape beyond 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?

A single efficient sentence with the resource and qualifier front-loaded. No waste, though it could carry one more clause of routing/param context at little cost.

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 simple read-only getter with no output schema, the description is close but leaves the two parameters (especially api_key and where site_id comes from) undocumented. A brief note on obtaining site_id would complete 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 coverage is 0% and the description explains neither parameter. The required site_id has no format or source guidance (presumably from amber_sites), and the api_key parameter is completely unexplained despite being an auth-sensitive input.

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 ('Get') and resource ('current electricity price for an Amber site'). The word 'current' implicitly distinguishes it from amber_forecast, but it does not explicitly name that sibling or amber_sites.

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: 'current' suggests now-vs-forecast, and 'for an Amber site' implies you need a site already known. No explicit when/when-not or alternative routing (amber_forecast for future prices, amber_sites to discover sites).

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, and open-world behavior, so the safety profile is covered. The description adds no behavioral context beyond what the annotations give: no forecast horizon, granularity (e.g., 5-minute vs 30-minute intervals), units, or timezone, all of which materially affect how the result is consumed.

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 short sentence with no wasted words and front-loaded verb. It is under-specified rather than verbose, so length itself is not the problem.

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?

No output schema exists, so the description must explain what a forecast returns, and it does not: no horizon, no interval, no unit (c/kWh). With two undocumented params and no return-value context, the definition is not sufficient for correct invocation or interpretation.

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 compensate and largely fails. It hints that 'site_id' refers to an Amber site, but 'api_key' is never mentioned, nor is any format, such as whether site_id is a NEM site identifier or an Amber internal ID.

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 ('Get') and resource ('electricity price forecast') scoped to an Amber site. The word 'forecast' implicitly separates it from amber_current_price, 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?

No guidance on when to call this versus amber_current_price or amber_sites, and no prerequisites (e.g., whether the site must be configured in Amber first) are stated. The agent must infer usage from the name 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?

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered structurally. The description adds scope information by stating results are limited to "the authenticated user," implying credential-bound, user-scoped results, but says nothing about return shape, error behavior for bad keys, or whether the api_key parameter can be omitted in favor of ambient credentials.

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, front-loaded on the verb and resource. It is efficient, though it omits any structuring that would help an agent route to it in a multi-step Amber workflow.

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 simple read-only list tool with annotations and no output schema, some brevity is acceptable. However, the agent gets no idea what a "site" object contains (an id/address) or that those identifiers feed amber_current_price and amber_forecast, which is the key context this tool needs to supply.

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 api_key parameter has 0% schema description coverage and no description here explaining whether it is required, optional, or defaulted from the environment. "Authenticated user" hints that api_key selects the account, but it does not tell the agent how the value is supplied, which is a meaningful gap at 0% coverage.

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 and resource ("Get Amber Electric sites") and scopes it to the authenticated user, which is clear enough for an agent to select it over non-Amber or non-site tools. It does not differentiate from siblings such as amber_current_price or amber_forecast, which would help the agent understand whether this tool is a prerequisite for 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?

There is no when-to-use guidance, no mention that the returned sites are likely the input required by amber_current_price and amber_forecast, and no exclusions. The agent must infer the call ordering from the sibling names 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, idempotentHint, destructiveHint=false and openWorldHint, covering the safety profile. The description adds nothing further — no return shape, no pagination behavior, no note on how series names are matched — so it contributes no behavioral context beyond structured data.

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 scope stated up front and no filler. It is appropriately sized, though it could have used one more clause to route agents away from sibling tools at no real cost.

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 trivial one-parameter list tool with complete schema coverage and rich annotations, little is strictly required. Still, no output schema exists and the description says nothing about result format, so an agent cannot anticipate what 'lists' means in practice.

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 the 'series' parameter is already documented with examples in the schema. The description only weakly restates that filtering happens by series, which is the baseline expectation for full schema coverage.

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 verb and resource are explicit ('List Amiibo figures'), and the required 'series' scope is stated. However, it does not distinguish itself from siblings like amiibo_search or amiibo_types, and 'game series' is slightly ambiguous since the parameter is actually the Amiibo series name (e.g. Super Mario).

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 versus amiibo_search or amiibo_types, and no mention of whether results are filtered, paginated, or exhaustive. The agent must infer the routing decision from the name 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 cover the full safety profile (readOnly, idempotent, non-destructive, openWorld), so the description must add context beyond that — and it adds none. It says nothing about matching behavior, result limits, or what a no-match response looks like.

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; every word identifies the resource, the verb, and the search dimension.

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 and its one parameter is fully documented in schema, and annotations carry the safety profile. However, with no output schema, the description gives no hint of the return shape or result size, which is 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?

Schema coverage is 100% with a single required 'name' parameter that is already described as 'Character name to search'. The description restates that same meaning without adding format, casing, or fuzzy-match details, 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 and resource ('Search Nintendo Amiibo figures') plus the search key ('by character name'), so the operation is unambiguous. It does not distinguish itself from siblings amiibo_by_series or amiibo_types, which is what keeps it from 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 name-based search intent is implied by 'by character name', but there is no explicit guidance on when to use this versus amiibo_by_series or amiibo_types, nor any note on partial/fuzzy matching or empty results.

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 destructiveHint=false, so the safety profile is covered structurally. The description adds only the concrete example values of the returned types; it says nothing about ordering, whether the list is exhaustive versus a fixed enum, or how the data behaves if Amiibo adds a new type, which the openWorldHint makes relevant.

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 the resource first and clarifying examples at the end; nothing is wasted. It is nearly minimal, though a short clause on what the values are useful for would have earned its place without bloat.

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 enumeration with a clean input schema, strong read-only annotations, and no output schema, the description is sufficient to call the tool correctly. The only missing piece is how this list relates to the sibling amiibo tools, which would help an agent chain calls.

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 nothing for the description to disambiguate. The parenthetical examples are a small bonus but not parameter documentation.

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 verb and resource ('List all Amiibo product types') and names example values (figure, card, yarn), so an agent knows exactly what taxonomy is returned. It does not explicitly contrast itself with the sibling enumeration tools amiibo_search or amiibo_by_series, which keeps it just 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?

Usage is only implied: an agent can infer this is the tool to call when it needs the set of valid product-type values, but the description never says when to prefer it over amiibo_search or amiibo_by_series, nor whether the result is meant to feed a filter. No exclusions or prerequisites 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, idempotentHint, destructiveHint=false, and openWorldHint, so the safety profile is covered. The description adds only the vague note "Includes trig values," without explaining output shape, precision, or what trig values are returned.

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 core conversion purpose is front-loaded before the supplemental trig note.

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 simple two-parameter conversion tool, the description plus 100% schema coverage and annotations are sufficient to call it correctly. The only minor gap is the unexplained "Includes trig values" return note.

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%, with both parameters documented directly in the input schema. The description repeats the supported units but adds no meaning beyond the schema's parameter descriptions.

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 a specific verb and resource: convert angles, with the four supported units named. It clearly distinguishes this from sibling conversions such as convert_temperature or convert_length.

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 states the operation clearly enough to imply when to use it, but gives no explicit when-to-use guidance versus related tools, nor any exclusions or prerequisites.

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, openWorldHint, non-destructive and no params, so the safety profile is fully covered. The description adds nothing beyond restating 'random', and it does not clarify return shape (quote text, character, anime title) or whether results can repeat across calls.

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, front-loaded with the verb, with zero wasted words.

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?

No output schema exists, so the description should ideally hint at what fields come back (quote, character, anime). For a zero-param random endpoint the gap is minor but real.

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; the baseline of 4 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: 'Get a random anime quote.' The behavior is unambiguous. However, it does not distinguish itself from the sibling animechan_search, which an agent could plausibly confuse with it.

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 animechan_search (or any other quote tool such as quote_random). The randomness is implied by the name, but no alternatives or exclusions are named.

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, openWorld, and non-destructive, so the safety profile is covered. The description adds nothing beyond that: it doesn't say whether the title match is exact or fuzzy, how many quotes come back, or what happens on a miss for a tool whose whole value hinges on matching behavior.

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 efficiently structured, though the brevity comes at the cost of substance rather than being a model of tight completeness.

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?

No output schema exists, so the description carries the burden of explaining what comes back (quote text, character name, anime title, count), and it says nothing. For a simple lookup this is a noticeable gap that forces the agent to call blind.

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 one parameter at 100% schema coverage, the schema already documents 'anime' as the title to search, so the baseline of 3 applies. The description could have clarified matching semantics (partial title, case sensitivity, aliases) but simply restates the parameter.

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 and resource ('Search for anime quotes') and scopes it to a specific anime, which is clear. It doesn't differentiate it from the sibling animechan_random (fetch quotes from anywhere) or from jikan_search_anime, so the agent must infer which tool to use.

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 use this versus animechan_random or the jikan anime search siblings, and no guidance on what happens if the title is wrong or unknown. The only implied usage comes from the required parameter, which the schema already conveys.

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 no annotations provided, the description must fully disclose behavior. It omits important details such as side effects (none expected), authentication requirements (api_key needed but not highlighted), rate limits, error handling, or response format. This lack of transparency could lead to unexpected agent behavior.

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 extremely concise with two sentences. The first sentence directly states the core functionality, and the second adds context. No unnecessary words or repetition, making it efficient for agents to parse.

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?

Given the tool has 10 parameters and no output schema or annotations, the description is insufficient. It fails to explain how parameters interact, required fields beyond api_key, expected output, or error conditions. An agent would need additional context to use this tool reliably.

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 already describes 60% of parameters (e.g., model, prompt, messages, system, max_tokens). The description adds no extra semantic value beyond what the schema provides, so it meets the baseline for moderate coverage.

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 the action ('Send a message') and the target resource ('Anthropic Messages API (Claude models)'). It identifies the tool as a means to call Claude programmatically, which differentiates it from sibling LLM tools like OpenAI or Groq, though not explicitly naming alternatives.

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 a use case ('agents that need to call Claude programmatically or compare model outputs'), implying when to use it. However, it does not mention when not to use it or explicitly compare to sibling LLM tools, leaving room for ambiguous selection.

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, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond that: no mention of authentication requirements, rate limits, pagination, or whether results are cached/live. For a read-only listing tool this is thin but not contradictory.

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. The scope qualifier ('available via the Anthropic API') is placed where it matters.

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 and annotations cover the safety profile, but with no output schema the description should indicate what the listing returns (model ids, display names, context limits?) and whether it is paginated. Those gaps are minor for a model-list endpoint but leave the agent guessing about the response.

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 single required parameter. The only hint about credentials is the phrase 'via the Anthropic API', which vaguely implies the api_key is a provider credential, but the description does not state that it is required, how to obtain it, or whether it is passed per-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 verb ('List') and resource ('Claude models') scoped to the Anthropic API, which implicitly separates it from the many sibling list-models tools (openai_list_models, groq_list_models, mistral_list_models, cohere_list_models). It does not explicitly name an alternative, but the provider qualifier makes the identity 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?

There is no when-to-use guidance, no mention of what to do with the result (e.g., pick a model id for anthropic_create_message), and no exclusions. An agent must infer the purpose entirely from the name and one sentence.

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?

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: it is implied to be a read, but there is no statement about error behavior for unknown IDs, whether the ID is numeric or slug-like, or what data comes back. For a zero-annotation tool this is a meaningful 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 short sentence with the verb and resource front-loaded and no filler. It is efficient, though it borders on under-specification rather than being richly concise.

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 one fully documented parameter, no nested objects, and no output schema, the definition is minimally adequate for a simple lookup. It stops at the minimum, providing no return-shape or error context that an agent could use, but nothing essential 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?

There is exactly one parameter with 100% schema description coverage, so the schema already defines 'id' as a Civilization ID. The description's 'by ID' adds no format, range, or valid-value detail beyond that, 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 states a clear verb ('Get') and resource ('Age of Empires II civilization') scoped by ID, which is unambiguous on its own. However, it does not distinguish this single-entity lookup from the sibling aoe2_civilizations (plural), which an agent must infer is the list 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?

There is no guidance on when to use this tool versus aoe2_civilizations or aoe2_unit/aoe2_units. The 'by ID' phrasing hints at the lookup pattern, but no alternatives or conditions 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?

With no annotations, the description carries the full behavioral burden. 'List all' implies a complete, non-paginated read with no side effects, which is a useful implicit signal, but there is no disclosure of return format, whether data is cached, or how large the result set 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?

A single sentence with zero waste, front-loading the verb and resource 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?

For a zero-parameter list tool this is minimally sufficient, but with no annotations and no output schema the description could reasonably hint at what each civilization record contains (name, expansion, bonuses) to help an agent decide whether 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?

The tool takes zero parameters, so per the rubric the baseline is 4. The description correctly implies no filtering is available, consistent with the empty input 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 ('List') and resource ('Age of Empires II civilizations') with 'all' clarifying scope. However, it does not differentiate from the near-identically named sibling 'aoe2_civilization' (singular), leaving ambiguity about whether these are the same or different endpoints.

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 alternatives. The singular sibling 'aoe2_civilization' is confusingly adjacent, and the description does nothing to explain the distinction or mention the related aoe2_technologies/aoe2_units 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?

No annotations are provided, so the description carries the full disclosure burden. It implies a read-only enumeration via 'List', but says nothing about return size, pagination, or ordering for the full technology set — meaningful gaps for a 'list all' 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?

A single, front-loaded sentence that conveys the verb and resource 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 no-argument, no-output-schema list tool, the description is nearly sufficient — an agent knows what it gets. Only minor details (result size/ordering) are absent, which is acceptable at this 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?

The tool takes zero parameters, so there is nothing for the description to document; the baseline of 4 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 (List) and resource (Age of Empires II technologies) with scope (all). It is clearly distinct from the sibling aoe2_units / aoe2_unit / aoe2_civilizations in substance, but the description never names those siblings to make the routing explicit.

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, when-not-to-use, or alternative guidance is given. For a zero-parameter 'list everything' tool the usage is largely self-evident, but the description does nothing to establish that.

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?

No annotations are provided, so the description carries the full disclosure burden, and it says nothing about error behavior for unknown IDs, rate limits, or response shape. It at least makes clear this is a read-only lookup, which prevents worse than a 1.

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 appropriately sized for a trivially simple one-parameter lookup.

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 minimal single-param lookup with no output schema, the description is adequate but bare. It leaves unresolved how an agent obtains a valid unit ID and what the returned object contains, which a slightly longer sentence could have covered.

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 one parameter with 100% schema description coverage ('Unit ID'), so the schema already documents it. The description adds no format or range detail beyond that, making the baseline 3 the correct 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 verb ('Get') and resource ('Age of Empires II unit') qualified by lookup key ('by ID'), which is enough to separate it from aoe2_units and aoe2_technologies. It stops short of the 5 tier because it never explicitly names the list sibling to contrast with.

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 prefer this over aoe2_units, nor any mention of what IDs are valid or where to get one. The only implicit signal is 'by ID' in the purpose text.

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?

No annotations are provided, so the description carries the full burden. It says nothing about whether the result is a full enumeration or paginated, how large the payload is, or what a unit record contains — the only implied behavior is 'all', which is really restating the purpose.

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. Nothing redundant or padded, and the verb/resource ordering is optimal for scanning.

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, no annotations, and no output schema, the description is barely sufficient for a trivia-list tool. It omits any hint of the returned fields or result size, though the invocation risk is low given the zero-argument signature.

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 there is no parameter semantics to document; the baseline of 4 applies. Nothing in the schema requires additional explanation from the description.

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 (List) and a specific resource (Age of Empires II units), so the agent knows it enumerates game units. It does not, however, differentiate itself from the sibling aoe2_unit (singular), leaving the list-vs-single distinction 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?

No guidance on when to use this versus aoe2_unit, aoe2_civilizations, or aoe2_technologies. The description gives no context about prerequisites, filtering, or which sibling answers a related question.

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?

No annotations are provided, so the description carries the full behavioral burden. It only implies a read-only metadata lookup and does not disclose permissions, rate limits, error behavior, or response characteristics.

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 wasted words. It states the action, resource, and required input directly.

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 low-complexity, one-parameter read tool with full schema coverage and no output schema, the description gives enough to call it correctly: it says what it returns and what identifier is needed. It lacks alternative-tool guidance, but that is a minor completeness 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 100%, so the identifier parameter is fully documented by the schema. The description repeats that it is an Internet Archive item identifier but adds no syntax, format, or validation details beyond 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 ('Get'), resource ('metadata for an Internet Archive item'), and scoping parameter ('by identifier'). It does not explicitly name the sibling archive_search, so it falls short of full sibling differentiation, but the identifier-based scope is clear.

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 'by identifier' implies usage when an item identifier is available, but there is no explicit guidance on when to use this tool instead of archive_search or other alternatives. 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?

With no annotations, the description carries the full behavioral burden and delivers almost nothing: no mention of rate limits, authentication, result shape, or how paging interacts with the result set. 'Search ... for items' is semantically empty beyond the verb.

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 zero filler, but it is arguably under-specified rather than tight; there is nothing after the core claim to earn the brevity.

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 search endpoint with no annotations and no output schema, the description is minimally adequate: it identifies the source, and pagination is covered by the schema. It omits what a result item contains and how total results/paging limits behave, which an agent would benefit from.

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 all four parameters (query, page, limit, mediatype) are already documented in the schema. The description adds no format hints, no example queries, and no guidance on mediatype 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 (Search) and resource (Internet Archive / archive.org items), so the agent knows this queries archive.org rather than arbitrary text. It does not distinguish itself from nearby siblings like archive_metadata or wayback_check, which is the only gap.

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 never names the alternative tools (archive_metadata for metadata retrieval, wayback_check for URL snapshots) that share the Archive.org domain. The agent must infer the routing decision entirely on its own.

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, so safety is covered. The description adds one genuinely useful behavioral fact — perimeter is returned only 'where possible', i.e. output varies by shape — but says nothing about precision, units, or whether formulas/steps come back.

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 with zero filler, verb and scope front-loaded, and the shape list packed into a compact enumeration. Nothing to trim.

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 must carry return-value burden; it says area plus optional perimeter but leaves the response shape, numeric precision, and unit assumptions unspecified. Adequate for a deterministic math tool, but not 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?

Schema description coverage is 100% and each property already names the shape(s) it applies to (e.g. base1/base2 for trapezoid, angle_degrees for sector), so the schema carries the semantics. The description only adds that shape determines which parameters matter; 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 ('Calculate') and resource ('area ... of common shapes'), then enumerates the seven supported shapes, which lets an agent match a request to this tool rather than to convert_area or polygon_calculate. It never explicitly contrasts with those siblings, 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 enumerated shape list implies when to use it (a named shape with known dimensions), but there is no explicit when-not guidance and no pointer to alternatives such as triangle_solve (for missing sides/angles) or polygon_calculate (for irregular polygons). Usage must be inferred.

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, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context such as what 'detailed info' includes, error behavior for invalid IDs, or any rate/auth considerations, making it minimally informative 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?

A single, front-loaded sentence with no wasted words. It clearly states the tool's purpose without unnecessary elaboration.

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 simple one-parameter read tool, the annotations and schema cover the essentials. However, with no output schema and only the vague phrase 'detailed info', the description does not characterize what the response contains, leaving a gap in completeness.

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 one required parameter with 100% schema description coverage ('Artwork ID (from search results)'). The description does not add any meaning or constraints beyond the schema, 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 states a specific verb ('Get') and resource ('detailed info about a specific artwork') scoped to the Art Institute of Chicago. It implicitly distinguishes this from a search tool by specifying 'a specific artwork', though it does not explicitly name the sibling search 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 use of 'specific artwork' implies this tool is for retrieving an item after obtaining its ID, likely via search. However, the description does not explicitly name artic_search_artworks or state when to use that alternative, so the guidance 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 readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds almost nothing beyond that: no mention of result caps/pagination (only the schema's limit hints at it), no ordering, no note that remote API failures or empty result sets are possible.

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; every word carries information. Brevity is not the problem here — missing content is.

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 simple two-parameter read tool with full annotations and complete schema docs, the essentials are present. However, with no output schema, the description could have stated the shape of results (list of artwork summaries requiring artic_get_artwork for detail), which is the main thing an agent still has to guess.

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% — both query and limit are documented with examples and bounds. The description repeats the keyword concept but adds no syntax or semantics beyond the schema, 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 (search), resource (artworks), and scoping constraint (by keyword) along with the source institution. It is distinguishable from artic_get_artwork by the search-vs-fetch distinction, though it never names that 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 statement of when to use this versus artic_get_artwork, no prerequisites, and no exclusions. The 'by keyword' phrase implies lookup-style usage, but the agent must infer that it should search first and then fetch details 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=true, idempotentHint=true and openWorldHint=true, so the safety and external-reach profile is covered. The description adds only the accepted query modes, and says nothing about result ordering, relevance ranking, or the fact that returned entries are metadata-only (no full text).

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. The resource, the verb, and the accepted query modes appear 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?

For a two-parameter read-only search with 100% schema coverage and full annotations, the description plus structured data give an agent enough to call it correctly. It could be marginally richer by noting that results are preprints (not peer-reviewed publications) and the max of 20, but nothing essential 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%, with the query and max_results (default 5, max 20) parameters fully documented in the schema. The description's "by keyword, title, or author" adds a small hint that the query string can target different fields, but doesn't give query syntax or field-prefix details. Baseline 3 applies when the schema carries the load.

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 arXiv for scientific preprints") and names the accepted query modes. No sibling in the tool list covers arXiv, so differentiation is largely unnecessary; the only gap versus a 5 is that it doesn't distinguish this from generic scholarly search siblings such as openalex_search_works or crossref_search_works.

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 versus the many other scholarly search tools (openalex_search_works, dblp_search_publications, crossref_search_works), nor any note on when it is inappropriate. Usage is only implied by the verb "search".

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states only that it calculates an aspect ratio and does not describe the return format (e.g., decimal vs. simplified ratio), edge cases such as zero height, or any other behavioral traits beyond the obvious.

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 words. It is appropriately sized for a simple calculation tool and immediately conveys the essential purpose.

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 simple calculator with complete parameter documentation and no output schema, the description is minimally adequate to invoke the tool. However, it omits the return value format, which would be useful since no output schema exists, leaving a clear gap in completeness.

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 schema descriptions fully cover both parameters ('Width in pixels.' and 'Height in pixels.'), so the baseline is 3. The description merely restates that width and height are the inputs without adding any semantic detail beyond what the schema already provides.

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 verb ('Calculate') and resource ('aspect ratio') with the inputs ('given width and height'). It is clear what the tool does, but it does not explicitly differentiate itself from related siblings such as ratio_simplify or proportion_solve.

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 explicit guidance on when to use this tool versus alternatives. The usage is implied by the tool name and description, but no context or exclusions are provided. This matches the 'no guidance' level.

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, open-world, and non-destructive behavior. The description adds the useful constraint that the transcript must be completed, but it does not describe error behavior, authentication needs beyond the schema, or return format 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 words. It communicates the core operation efficiently.

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 low-complexity, two-parameter read operation with full schema coverage and rich annotations, the description is nearly complete. It could provide slightly more detail about the return shape, but it is sufficient for correct selection and invocation.

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 both parameters are documented in the schema. The description does not add syntax or format details beyond the schema, so the baseline of 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 states a specific verb and resource: retrieving a completed transcript split into paragraphs. This clearly distinguishes it from sibling tools like assemblyai_get_transcript and assemblyai_get_sentences by specifying the output granularity.

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 should be used when paragraph-level segmentation is needed from a completed transcript, but it does not explicitly state when to prefer it over alternatives such as assemblyai_get_sentences or assemblyai_get_transcript. Usage is inferable but not fully guided.

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, and destructiveHint=false, so the safety profile is covered. The description adds the useful constraint that the transcript must be completed, but does not explain behavior for incomplete transcripts, authentication needs, or rate limits.

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 wasted words. It states the action and result 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?

The description is adequate for a simple read tool whose annotations cover safety and whose parameters are fully documented. With no output schema, though, it could say more about the sentence return format (e.g., timestamps or confidence) to be fully 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?

Schema description coverage is 100%, so both api_key and transcript_id are already documented in the schema. The description reinforces that transcript_id must refer to a completed transcript, but adds no syntax or format details beyond 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?

The description uses a specific verb ('Get') and a clear resource ('a completed transcript split into individual sentences'), distinguishing it implicitly from assemblyai_get_transcript and assemblyai_get_paragraphs. It does not explicitly name those siblings, so it falls short of the top 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?

The word 'completed' implies the prerequisite that the transcript must already be finished, giving some usage context. However, it does not explicitly say when to choose this over assemblyai_get_transcript, assemblyai_get_paragraphs, or assemblyai_summarize.

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 and non-destructive, so the safety profile is covered. The description adds the useful fact that the call returns job status as well as results, implying it may be called before completion, but says nothing about status values, error states, or rate limiting.

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, no filler. Brevity comes at the cost of the routing and polling details an agent would need, but there is no structural 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?

No output schema exists, so the description should say what 'results' contains (transcript text, status enum, error message, language, duration) and that incomplete jobs return partial status. It delivers none of that, leaving an agent unable to predict the response shape for a no-output-schema 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 schema already explains that transcript_id comes from assemblyai_transcribe and that api_key is the AssemblyAI key. The description adds no parameter-level meaning beyond that, 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+resource ('Get the status and results of an AssemblyAI transcription job'), so the agent knows it retrieves a job by ID. It does not distinguish itself from close siblings like assemblyai_get_sentences, assemblyai_get_paragraphs, assemblyai_list_transcripts or assemblyai_summarize, which all read from the same transcript.

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 assemblyai_get_sentences/paragraphs (which return subsets) or assemblyai_list_transcripts. It also omits the natural polling pattern — call after assemblyai_transcribe, repeat until status leaves queued/processing — which is the primary usage context for a status-check 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, idempotentHint, non-destructive and openWorld, so the safety profile is covered. The description adds two useful hints beyond that: results are 'recent' (implying a recency bound or default window) and scoped to 'the account' (implying API-key account scoping). It does not mention pagination or result ordering, which is a gap for a list 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 front-loaded sentence with no wasted words. It is efficient, though the 'recent' qualifier is left unexplained rather than elaborated.

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 list tool with full schema coverage and annotations, this is nearly complete. The only missing piece is clarification of what 'recent' means (default window, pagination behavior via cursors), which the schema hints at but does not tie back to the description.

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 limit, status, api_key and both cursors are fully documented in the schema. The description adds no parameter-level detail, so the baseline 3 for high-coverage schemas 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 (List) and resource (AssemblyAI transcripts) scoped to the account, with the qualifier 'recent' indicating a bounded result set. It is reasonably distinguishable from assemblyai_get_transcript (singular fetch) by virtue of being a plural list, but does not explicitly name that sibling.

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 offers no when-to-use guidance, no prerequisites, and no mention of alternatives. An agent must infer that this is the discovery step preceding get_transcript/get_sentences, which is not stated anywhere in the text.

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 no annotations, the description carries the burden of behavioral disclosure. It clearly states prerequisites (transcript must be completed and summarization enabled), but does not specify error handling or response format.

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 17-word sentence that states the purpose first, then the prerequisite. No unnecessary words or repetition.

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 simple retrieval tool with 2 parameters and no output schema, the description covers the essential purpose and prerequisite. It could mention the return format, but the context is largely 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 100%, so the schema already documents the parameters. The description adds context about the transcript needing summarization but does not enhance parameter understanding beyond 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?

The description clearly states the tool gets an AI-generated summary for a completed AssemblyAI transcript, distinguishing it from sibling tools like assemblyai_get_transcript or assemblyai_transcribe. The verb 'Get' and resource 'summary' are specific.

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 includes a crucial prerequisite ('must have been submitted with summarization enabled'), guiding when the tool can be used. However, it does not explicitly mention alternatives or when not to use it.

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?

No annotations provided; description fails to disclose that transcription is asynchronous or that the tool returns a transcript ID for polling. Behavior is opaque beyond basic submission.

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?

Single sentence, front-loaded with action and resource, no unnecessary words.

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 13 parameters, no output schema, and no description of return type or workflow (e.g., polling required), the description is insufficient for an agent to use 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 covers 100% of parameters with descriptions; description adds no extra meaning beyond the schema. Baseline score 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?

Description clearly states it submits an audio/video file for transcription to AssemblyAI, differentiating from sibling tools that retrieve or list transcripts.

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 tool versus siblings like assemblyai_get_transcript or assemblyai_list_transcripts. Missing context on asynchronous behavior.

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?

No annotations provided, so the description must carry the full burden of behavioral disclosure. It does not explain that walls block movement, that diagonal movement is allowed by default, that the grid uses 0/1 values, or what the return format looks like. Without annotations and an output schema, this is severely lacking for a mutation-free but complex algorithm.

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 that states the purpose without any wasted words. It is appropriately sized for a simple tool 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?

Given the complexity of A* pathfinding and the lack of annotations or output schema, the description is insufficient. It omits critical details such as default diagonal movement, grid interpretation, and what the function returns, leaving the agent to infer behavior from the schema alone.

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 the schema already documents all parameters, including the grid, start, end, and diagonal flag. The description adds no additional parameter semantics beyond stating it operates on a 2D grid.

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 (find), resource (shortest path on a 2D grid), and algorithm (A*). This distinguishes it from sibling pathfinding tools like dijkstra_path, bfs_search, or dfs_search, which use different algorithms or heuristics.

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 tool versus alternatives like dijkstra_path or bfs_search. The description does not mention prerequisites, such as grid format or movement rules, nor does it specify scenarios where A* is preferred (e.g., with heuristics, weighted grids).

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 no annotations, the description carries the full burden, and it does add one genuinely useful behavioral fact: 'Self-inverse' tells the agent the same call both encodes and decodes, removing the need for a separate inverse operation. It says nothing about how non-alphabetic characters, case, or non-ASCII input are handled, so the disclosure is partial.

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 operation and mapping, and the trailing property note is dense rather than filler. 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 single-parameter, no-output-schema transform, the description is nearly sufficient: purpose, mapping, and the self-inverse property are all covered. The only real omission is edge-case behavior for digits, punctuation, and case, which an agent would otherwise have to discover by trial.

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 one parameter at 100% schema description coverage ('Text to encode/decode.'), so the schema already does the work; baseline is 3. The description's 'to text' confirms the input type but adds no format, length, or charset detail beyond 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 (apply) and resource (Atbash cipher), and spells out the mapping (A=Z, B=Y, ...) so the transformation is unambiguous without opening anything else. It does not differentiate itself from cipher/encoding siblings such as rot13_convert, vigenere_process, or morse_convert, which keeps it 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?

Usage is implied rather than stated: the agent can infer this is the tool for Atbash transformations, and 'Self-inverse' hints it serves both encoding and decoding. There is no explicit when-to-use or when-to-prefer-an-alternative guidance relative to the many other cipher tools in the sibling list.

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 no annotations provided, the description carries full burden. It says 'Get' implying a read-only operation, but does not disclose authentication requirements (though an 'api_key' parameter exists), rate limits, or what happens on errors. The lack of detail on behavioral traits is significant.

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 concise sentence with no extraneous information. It is front-loaded and efficient, earning 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?

Given 4 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain return values, parameter formats, or any special considerations needed for correct invocation.

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 4 parameters with 0% schema description coverage. The description adds no meaning to the parameters (e.g., what 'from_postcode' and 'to_postcode' expect, what 'service_code' options are). The agent must guess or rely on external knowledge.

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 the tool's purpose: 'Get Australia Post estimated delivery times.' The verb 'Get' and resource 'estimated delivery times' are specific. While it doesn't explicitly differentiate from siblings, the sibling names (e.g., 'auspost_get_postcode', 'auspost_track_parcel') imply distinct functions, so purpose is reasonably clear.

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