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 the checks performed (validity status, revision date, future amendments relative to today), which is meaningful behavioral context, but it does not state whether the operation is read-only, whether authentication is required, or how errors are handled.

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 that quickly establishes the tool's purpose and scope. The phrase 'Критический инструмент' is minor fluff, but overall it is efficient and well-structured.

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 helpfully explains what the check returns (status, revision date, future amendments). However, it does not clarify how the four optional input parameters should be combined (e.g., act+article vs. url vs. raw_html), leaving a meaningful gap 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?

Schema description coverage is 100%, so all four parameters (act, url, article, raw_html) are already documented in the schema. The description adds no parameter-level meaning or input-combination guidance, 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 ('проверяет') and resource ('актуальность нормы'), then enumerates exactly what is checked: article validity status, current revision date, and future amendments. It is clearly distinct from siblings like search_legislation and get_norm_text, though it does not name them 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?

There is no explicit guidance on when to use this tool versus alternatives such as search_legislation or track_bill, nor any when-not conditions. The opening phrase implies its purpose but does not tell the agent how to choose it over siblings.

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 exist, so the description carries the full burden: it discloses the useful behavioral trait that output is clean Markdown with ads, banners, and navigation stripped out. However, it doesn't say whether the tool fetches live over the network or how it behaves when the fetch fails and raw_html is supplied, so important operational context is missing.

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

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

It is a single tight sentence with zero waste, and the key deliverable (clean structured Markdown text) is front-loaded before the parenthetical about what gets removed.

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?

It has four optional parameters and no output schema, so the description needs to explain the return shape on its own; it does so by specifying Markdown and what is cleaned out. It is still a bit thin on which parameters trigger live fetching versus offline parsing, but the essential information for calling it is present.

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

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

Schema description coverage is 100%, so all four parameters are already documented in the schema, giving a baseline of 3. The description adds only the output-format detail and does not clarify how act, url, article, and raw_html relate to each other or which combinations are valid.

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 action (extraction) applied to a specific resource (the article text of a Russian normative legal act) and even specifies the output format (Markdown). It doesn't explicitly differentiate itself from search_legislation, which also touches legislation, but the extraction/cleanup focus is distinct enough that an agent can identify 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?

The description never states when to use this tool rather than search_legislation or check_norm_status. The only usage hint ('url from search_legislation results') appears in the schema, not the description, so the description itself provides no routing guidance or preconditions.

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. It discloses the authoritative portals and query modes, but says nothing about result ordering, return format, rate limits, or permissions; the search nature implies read-only behavior but does not state it.

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. The main purpose, query modes, and source filtering are all packed efficiently into one line.

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 covers purpose, query modes, and authoritative sources, which is a reasonable minimum for a search tool. But with no output schema and no annotations, it should say more about what a result contains and how results are ranked or limited.

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 three parameters thoroughly. The description reinforces the query and source-filter semantics but adds little beyond what the schema examples and enum already provide.

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 ('Поиск') and resource ('статей, кодексов и законов РФ'), plus supported query modes and source filtering. It does not explicitly differentiate from sibling tools such as get_norm_text, so it falls 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 description implies when to use the tool by mentioning semantic queries, article-number queries, and authoritative-portal filtering. However, it gives no explicit when-not-to-use guidance or comparison to alternatives like get_norm_text or check_norm_status.

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 behavioral burden. It implies a read-only lookup and describes the returned status fields, but it does not disclose side effects, permissions, rate limits, or error 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 sentence with no filler, front-loading the core purpose and then listing the concrete data returned. Every element 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 one-parameter lookup with no output schema, the description sufficiently explains what information is returned. It could be more complete by mentioning what happens for ambiguous or missing bill numbers, but the core context is present.

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

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

Schema coverage is 100%, and the single query parameter is documented with an example bill number and keyword option. The description adds no parameter-specific meaning beyond what the schema already provides, 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 gives a specific verb and resource ('Отслеживание прохождения законопроектов') and enumerates the tracked fields: stage, readings, committee, and links. It is clear what the tool does, but it does not explicitly differentiate itself from siblings like check_norm_status or search_legislation.

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 to track a bill's progress when you have a bill number or keywords. However, there is no explicit guidance on when to choose this over search_legislation or check_norm_status, nor any exclusions.

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