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, yet it discloses almost nothing beyond the output hint 'Returns question refs'. Nothing is said about auth requirements, rate limits, caching, whether the 'refresh' flag triggers a network refetch, or whether the call is read-only versus mutating; the 'Returns question refs' line is also redundant since an output schema exists.

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

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

Three short sentences, front-loaded with purpose, then identifier examples, then the sibling routing. Every sentence earns its place; only the slightly awkward 'List one OAHelper set page' phrasing costs a 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?

For a two-parameter lookup tool with an output schema (so return values need no explanation), the description covers purpose, identifier format, and alternative tools adequately. The single real gap is the undocumented 'refresh' semantics, which keeps it from 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 description coverage is 0%, so the description must compensate, and it does well for slug_or_url by giving two accepted formats (bare slug and full URL). However, the 'refresh' parameter is completely unexplained in both schema and description, leaving half the parameters opaque and capping this at a partial-credit 3.

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 one OAHelper set page') and pins down the identifier format with two concrete examples ('kickdrum-mcq24sep', full URL). It also explicitly routes sibling confusion by stating that company-by-name lookups belong to oahelper_search or oahelper_sync, so an agent can differentiate it from its siblings without opening schemas.

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?

Names the alternatives (oahelper_search, oahelper_sync) and the condition that selects them ('For a company by name'), which is exactly the disambiguation an agent needs. It doesn't state the inverse condition as explicitly (use this when you already have a slug or URL) or any exclusions, so it falls short of a full 5.

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

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

With no annotations, the description carries the full behavioral burden and does well: it discloses a side effect (saving full write-ups to library/<company>/interviews/), the pagination rate (12 per page, most relevant first), and that the return is only a short list. It omits overwrite behavior, auth/permission needs, and rate limits, which keeps it below a 5.

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

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

Two tight sentences with the core resource front-loaded and the side effect plus the required follow-up action stated next. Every clause carries information; only minor polish is missing.

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 tool with an output schema present, the description covers the essentials an agent needs: what is returned (a short list), where the full text lives, and the page size. Remaining gaps (whether re-running overwrites saved files, how `pages` interacts with results) are secondary.

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% for both parameters, so the description must compensate. '12 per page' gives the agent a way to infer what `pages` means (pages × 12 results, default 2), and `company` is implicitly the lookup key, but neither is stated explicitly.

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 resource ('Interview experiences for a company') and its source (OAHelper), which is clear enough for an agent to distinguish it from oahelper_question or oahelper_solution. It does not explicitly contrast itself with oahelper_search, so sibling differentiation is only partial.

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: fetch interview write-ups for a company, then 'read the saved files for the full text,' which is a useful follow-up instruction. There is no guidance on when to prefer this over oahelper_search or how to size the `pages` parameter, so no explicit when/when-not reasoning is 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?

With no annotations, the description carries the full behavioral burden, and it does disclose two real traits: the operation is a local/no-network read, and its output shape switches based on whether company is supplied. It does not mention staleness of the offline cache, sync prerequisites, or error behavior when a company is absent locally.

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

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

Three short sentences, zero filler, with the core 'what is saved offline / no network call' framing front-loaded before the conditional behavior. Every sentence adds information.

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?

An output schema exists, so return-value detail is not the description's job, and for a single-optional-parameter read tool this covers the essentials. Missing only offline-cache freshness/sync prerequisites, which would help an agent avoid stale results.

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

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

Schema coverage is 0% and the sole parameter has no description, so the description must compensate — and it does, fully defining the parameter's two modes (omitted = list all companies, supplied = that company's index). It only lacks format examples (e.g., exact company identifier form).

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 resource (the offline-saved library) and a specific dual behavior: full company list without a company, and that company's index (sets, interviews, counts) with one. It implicitly separates itself from network-based siblings via 'No network call', though it never names oahelper_sync or oahelper_company by 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?

'No network call' implies the offline use case, which is genuine context for choosing this over a network-backed sibling. However, it never states when to prefer this over oahelper_company, oahelper_search, or oahelper_sync, so the selection logic is left for the agent to infer.

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 and does reasonably well: it discloses the returned content set and, importantly, the side effect 'Saves it to the offline library,' which is not obvious from the name. It still omits whether the operation is read-only in effect, any auth requirements, 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?

Front-loaded with the core purpose followed by a focused parameter note; every line carries information with no filler. Minor looseness in the parenthetical about MCQ sets, but overall tight and well-ordered.

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?

An output schema exists, so return-value detail is unnecessary, and the description covers the main behavior and the offline-save side effect. The remaining gap is the unexplained 'refresh' flag and lack of any safety/auth context, but it is largely complete for a single-item fetch 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 description coverage is 0%, so the description must compensate. It documents ref_or_url well with concrete format examples, and 'optionally community solutions and images' loosely maps to include_community/include_images, but the 'refresh' parameter is never explained and the two flags are not tied explicitly to their names.

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 ('Read one OAHelper question') and enumerates the returned content (statement, MCQ answers with explanations, official solution, optional community/images), which clearly sets it apart from a search tool. It does not, however, name or differentiate itself against siblings like oahelper_search or oahelper_solution, 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?

Usage is only implied: an agent infers it should call this when it has a question ref or URL and wants the full question. There is no explicit when-to-use, when-not-to-use, or pointer to an alternative such as oahelper_search for discovery.

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 the full behavioral burden. It discloses the return shape (each set with company_ref, date and question counts) and implies a non-mutating lookup via "Find" and "Lists", but says nothing about authentication, rate limits, pagination, or whether results are capped — meaningful gaps for a search tool with zero annotation coverage.

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 filler. The purpose and the routing hint to oahelper_sync are front-loaded, and the return-contents sentence earns its place by telling the agent what to expect.

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?

An output schema exists, so return values needn't be fully documented, yet the description still summarizes them usefully. Purpose, input examples, and the alternative tool are all covered; only the absence of auth/limit context keeps it from being 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?

The single parameter has 0% schema description coverage, so the description must compensate. It does so reasonably by naming the expected value type (company name) and giving two concrete examples, which is enough to invoke the tool correctly even though it doesn't state matching semantics (exact vs partial, case sensitivity).

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 a company's OA question sets on OAHelper by name") and includes concrete input examples ("Amazon", "Kickdrum"). It also explicitly distinguishes itself from the sibling oahelper_sync by contrasting retrieval with download, so an agent can route without opening a schema.

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

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

The description gives a clear when-to-use-this-instead condition: use oahelper_sync to download sets into the offline library rather than this tool. It does not clarify the boundary with oahelper_company or oahelper_question, leaving some sibling ambiguity, but the primary alternative is named explicitly.

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 and does disclose the key non-obvious trait: each new fetch consumes one of a limited daily quota, while previously saved solutions are free. It does not mention authentication/account requirements or whether a fetch is idempotent/cacheable beyond the 'saved solutions are free' hint.

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

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

Two tight sentences with no waste; the quota constraint and the use-only-when-asked rule are front-loaded where the agent will see them before deciding to call.

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?

An output schema exists, so return values need no explanation, and the description covers purpose, languages, and quota behavior well. The remaining gap is the undocumented required parameter ref_or_url, whose accepted format an agent must 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 coverage is 0%, so the description must compensate. It usefully enumerates the accepted languages (cpp, python, java), filling an enum gap the schema lacks, but says nothing about ref_or_url — the required parameter — such as whether it accepts an ID, slug, or full URL.

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 (Fetch) plus a precise resource (OAHelper's official solution for one coding question), which is far more than a restatement of the name. It does not explicitly contrast itself with the closest sibling, oahelper_question, so the boundary between the two is left for the agent to infer.

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 an explicit when-to-use rule ('only call this when the user asks for the official solution') backed by a cost rationale, and notes that saved solutions are free. It stops short of naming a specific alternative tool to use instead, so routing 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 burden and it discloses the key side effect explicitly: online=true performs one network request against the site to check Pro status, while the default makes no network call. That is the most consequential behavioral trait for a status tool. It does not mention authentication requirements or rate/latency considerations, so it falls short of a 5.

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

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

Two compact sentences, no filler, with the core purpose front-loaded before the conditional network behavior. Every clause carries information an agent can act on.

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?

An output schema exists, so return values need not be described, and the low-complexity single-parameter surface is well covered. The remaining gap is the absence of any statement about auth/session prerequisites for a tool whose whole purpose is reporting session status.

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% — the schema exposes only a bare 'online' boolean with default false and no explanation. The description compensates by stating exactly what the flag does (triggers one network request to check Pro status) and what the default behavior is (no network call), which is meaning 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 names a concrete resource and outcome — 'Session and usage status' — so an agent immediately knows this reports current session/usage state rather than searching or syncing. It does not explicitly differentiate itself from siblings, but none of the siblings (search, company, sync, question, solution, interviews, offline) overlap with a status check, so mis-selection risk is low.

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 statement of when to call this tool versus alternatives, nor any prerequisite (e.g., must be authenticated/logged in for session status to be meaningful). The only usage-like content is the conditional behavior of the 'online' flag, which is invocation detail rather than selection guidance.

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

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

With no annotations the description carries the full burden, and it does well: it discloses ordering ('newest sets first'), a per-call request budget tied to max_items, cost semantics ('already-saved items cost nothing'), and quota rationale for the exclusion. It stops short of stating auth requirements or failure behavior, so 4 rather than 5.

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

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

Front-loaded with the action, then budget behavior, then the sibling alternative, then where to read output. Each sentence adds information, though the multi-line layout is slightly denser than needed.

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?

Output schema exists, so return format needn't be explained, and the description usefully points to library/<company>/index.md. However, for a 4-param tool with 0% schema coverage, leaving include_images and include_interviews unexplained is a real gap in an otherwise thorough definition.

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 there are 4 params, so the description must compensate. It only explains max_items (live requests per call); include_images and include_interviews are never mentioned, and the 'cost nothing' note only loosely implies idempotent behavior. Two of four parameters remain fully undocumented.

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 ('Download') plus a specific resource ('one company's OAHelper content into the offline library') and enumerates the content types (set lists, question statements, MCQ answers, interview experiences). It also carves out what it does NOT do, routing the agent to the oahelper_solution 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?

Explicitly states the repeat-call pattern ('call it again to continue') and explains the exclusion condition for official solutions ('NOT fetched here because each one uses the account's daily solution quota; use oahelper_solution'). Both when-to-use and when-not-to-use are covered.

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