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

With no annotations, the description carries the full burden and does add real behavioral context: the signature comes from the library's actual source and is paired with a documentation URL, which tells the agent how trustworthy the output is. It is silent on failure modes (unknown symbol), and the library-version interaction is only lightly covered.

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

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

The core purpose is front-loaded in the first sentence, followed by input-format detail and a compact Args block. Slightly redundant in re-listing the symbol parameter, 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?

For a single-symbol lookup with an output schema present, the description supplies what the agent needs: name formats, library scoping, version override, and the provenance of the returned signature. Only error behavior is unaddressed.

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, and it does: symbol is described as a class/function/method/module name, library is enumerated as "merlin" (default) or "perceval", and version is explained as a docs version override used for the documentation link. That covers all three parameters with meaning beyond their bare titles.

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 precise verb+resource: retrieving the exact signature and docstring of one API symbol, with the key qualifier that the signature is parsed from real source and paired with a doc URL. This implicitly separates it from search_api (searching) and get_source (reading a file), though no sibling is 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?

The description explains accepted input forms but gives no guidance on when to choose this tool over search_api, get_source, or get_doc_page. No prerequisites or exclusions are offered, leaving tool selection to inference 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?

With no annotations, the description carries the full burden and does add real behavioral context: it returns published reStructuredText source (so code blocks/directives survive), and it discloses that long pages are windowed with the footer indicating the next offset. It does not mention auth/permissions or rate limits, but pagination and return-format behavior are covered.

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

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

The behavioral facts and input contract are front-loaded, and the Args block earns its place because schema coverage is zero. The block slightly duplicates the schema structure, but there is no filler text.

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, yet the description usefully explains the return shape and pagination anyway, and it covers both library scoping and versioning. Combined with the schema, an agent has enough to invoke it correctly; only auth/version-format details are absent.

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 documents all five parameters inline (page as name or URL, library options merlin/perceval, version override, offset, limit). The version entry ('docs version override') is somewhat thin and no value ranges/defaults are given, but every parameter is at least semantically grounded.

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+resource ('Read one documentation page in full') and scopes it against the sibling workflow by stating it accepts a page name produced by search_docs. An agent can distinguish this from search_docs and, by resource wording, from the API-doc and source tools without opening the schema.

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

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

It clearly tells the agent the two valid inputs (a search_docs page name like 'user_guide/layer' or a documentation URL), which implies the intended workflow after searching. It stops short of explicit exclusions ('use get_api_doc instead for API reference'), so it is clear context without routing rules.

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. It usefully discloses that cell outputs are omitted by default and that notebooks track the current release, which is real behavioral context. It says nothing about permissions, rate limits, or failure modes (e.g. unknown example name), leaving gaps for a tool of this kind.

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?

Purpose is front-loaded, the usage rationale follows in one sentence, and the parameter list is compact with no redundant restatement. Slightly verbose in the usage sentence but nothing that fails to earn 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?

An output schema exists so return values need not be explained, and the description still adds the markdown/runnable-cell shape and the output-omission default. Parameter coverage is complete despite 0% schema coverage, so an agent can invoke this correctly without opening the 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 0%, so the description must compensate, and it does: all six parameters are explained, including the `name` example format ('notebooks/FirstQuantumLayers'), the `library` values ('merlin' default or 'perceval'), version override, and offset/limit semantics. Only minor syntax details (e.g. valid version strings) are absent.

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 an example notebook') plus the rendering format ('as markdown with runnable code cells'), which separates it from the doc/api reading siblings. It also names list_examples as the source of valid `name` values, but it does not explicitly contrast itself with get_doc_page, which is the nearest ambiguous 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?

'This is the fastest way to get correct, working code: the notebooks are maintained against the current release' gives a clear reason to prefer this tool over prose docs. There is no explicit when-not or named alternative, so it stops short of a 5.

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

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

No annotations are provided, so the description carries the burden. It implies a read-only upstream fetch and discloses ordering ('newest first') and the two supported libraries, and the output schema covers return values. It omits any auth, rate-limit, or caching behavior, so it adds some but not rich context.

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 action, followed by concrete use cases and a compact Args block. The Args section partly duplicates the schema, but given 0% schema coverage it 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?

For a simple two-parameter read tool with an output schema, the description covers purpose, use cases, and both parameters. Only edge details like limit bounds or recency guarantees are missing.

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

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

Schema coverage is 0%, so the description must compensate, and it does: library is documented as 'merlin' (default) or 'perceval', and limit as the number of releases, newest first. It does not state bounds or a maximum for limit, a minor 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 specific verb and resource: 'Read the most recent upstream release notes,' with the scope ('most recent upstream') making it distinct from doc/API/source lookup siblings. It does not explicitly name a sibling to distinguish itself, but the operation 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?

It gives clear usage contexts – 'what changed', 'is this API still current', and migration questions – plus the rationale (fast-moving libraries, breaking changes described in release notes). It stops short of naming alternatives or stating 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?

There are no annotations, so the description carries the full burden. It discloses useful behavior (symbol vs module narrowing, offset/limit paging), but omits read-only framing, truncation/output-size behavior (limit defaults to 40000), error cases, and whether it hits a network or cached source. Adds real context but leaves behavioral gaps.

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-loads the purpose in the first line, then a precise behavioral sentence, then a clean Args block. Every element earns its place; only the retained Args indentation styling is slightly less tight than prose.

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 explained. Combined with the documented parameters and targeting behavior, the definition is nearly complete, though a note on truncation limits/read-only guarantees would close the remaining gap.

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

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

Schema description coverage is 0%, so the description must compensate, and it does: it documents all five parameters (target, library, ref, offset, limit) with meaning and concrete examples (e.g. "merlin.core.circuit" or "QuantumLayer") that the bare schema lacks.

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 ("Read the library's real source code") and immediately clarifies the two targeting modes: a dotted symbol narrows to a class/function, a module name returns the whole module. This clearly distinguishes it from doc-oriented siblings like search_docs, get_doc_page, and get_api_doc.

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 a clear triggering condition: "Use this when the documented behaviour is ambiguous and you need to see what the code does." It does not explicitly name the alternative tools or state when NOT to use it, so it falls short of a full 5, but the context is unambiguous.

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. It does disclose what the listing contains ('each with a one-line summary and tags') and notes the MerLin gallery scope, but says nothing about pagination, result limits, or that this is a read-only enumeration. Adequate 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?

Front-loaded with the core purpose in the first sentence, followed by useful scope detail and a compact Args block. Slightly verbose in the MerLin gallery clause, but every sentence contributes.

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

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

An output schema exists, so return values need not be explained, yet the description still gives the shape (one-line summary + tags). Both optional parameters are covered. Complete enough for a two-param listing tool, with only minor gaps around result limits.

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 does so well for both params: library values ('merlin' default, or 'perceval') and topic's matching scope ('title, summary or tag') plus sample values. It omits that topic is nullable/optional, but the key semantics are supplied.

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 opens with a specific verb+resource ('List the runnable example notebooks shipped with the library') and then differentiates from the sibling get_example by explaining that names from this listing are the input to that tool. An agent can distinguish it from search_docs/get_api_doc 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?

It clearly routes the agent: 'Pass a name from here to get_example', establishing the list-then-fetch workflow. It also explains the topic filter's intended use with concrete examples. It does not, however, state when to prefer this over search_docs/search_api, which is the natural adjacent alternative.

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 supplied, so the description carries the full burden, and it does disclose meaningful behavior: the search covers the entire documented symbol inventory and 'query' is a partial/substring match rather than exact. It omits any statement about result ordering, error behavior on unknown library/version values, or whether results are paginated beyond 'limit'.

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-loads the purpose in the first sentence, then the differentiated scope, then the workflow; the Args block is cleanly formatted. The enumerated symbol-type list is somewhat long but warranted since it defines coverage. No wasted sentences.

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 five parameters, no annotations, and an output schema already present, the description supplies what the structured fields do not: scope, matching semantics, all parameter meanings, and the follow-up tool. It leaves a small gap around result pagination/ordering and failure modes for invalid library or version values.

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 documents all five parameters plus the default for library ('merlin') and the valid kind values (class, function, method, module, attribute, property, data). 'version: docs version override' and 'limit: maximum number of symbols to return' are terse, leaving minor gaps, but the required 'query' parameter is illustrated with concrete examples.

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+resource ('Find documented API symbols by name') and states the search domain precisely: the project's own symbol inventory, covering every documented class, function, method, module, attribute and property. This scope statement alone differentiates it from search_docs (page text) and get_api_doc (signatures), which are named or implied.

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 a clear two-step workflow: 'Use it to discover exact dotted names, then call get_api_doc for signatures,' which explicitly routes the agent to the correct follow-up sibling. It does not state when NOT to use it (e.g. when the agent already knows the exact symbol and should call get_api_doc directly), so it stops short of a 5.

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

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

No annotations are provided, so the description carries the full burden. It discloses that results are ranked pages carrying a page name for the get_doc_page handoff, which is useful, but says nothing about ranking semantics, result volume beyond the limit arg, or any access/rate constraints.

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-loads the purpose, then usage, then a tidy args block. Slightly verbose with the multi-line example questions, but every line carries information the schema does not.

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 modeling is not required, and the description still adds the page-name handoff detail. Given a 4-parameter tool with zero schema description coverage, the prose covers the params adequately; only ranking/limit behavior nuance is absent.

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 is the only source of parameter meaning, and it documents all four: query as free text with an example, library with its value set ('merlin' default or 'perceval'), limit as max pages, and version as an override defaulting to the upstream-published version. Minor gap: no value-set detail for version.

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 (documentation full text) plus the return shape (best-matching pages). It is clearly distinguished from the sibling search_api, which targets API docs rather than conceptual documentation.

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 says to 'use this first for conceptual questions' and gives sample query phrasings, then routes the agent onward: 'Each result gives a page name to pass to get_doc_page.' Both the when-to-use and the next step are stated.

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