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

With no annotations, the description carries the disclosure burden. It discloses that output is converted to readable text and lists the returned fields, which is useful. However, it does not mention max_chars truncation behavior, what happens when multiple or no identifiers are provided, or any error conditions.

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 two dense sentences with no filler. It front-loads the core action, then the return contents, then the key invocation constraint. Every part 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 4-parameter tool with no output schema, the description covers the main invocation rules and return content well. It is missing explicit handling of max_chars and error cases, but an agent can correctly call the tool with the information provided.

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 adds value beyond the schema by specifying the exclusive-or relationship among id/slug/url and by noting that id comes from oppcircle_search. It does not add much for max_chars, but the schema already documents that parameter well.

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 ('Fetch'), names the resource ('a single opportunity'), and enumerates the returned content in enough detail to distinguish it from sibling list/search tools. It clearly identifies that this is the detail-getter for one known record, not a discovery 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?

It gives actionable guidance: provide exactly one of id/slug/urlческое and even notes that id comes from oppcircle_search. It does not explicitly say 'use this after search for full details instead of search results', but the 'single opportunity' framing makes the intended context clear.

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 discloses two key behaviors: filtering out expired opportunities and ordering by newest first, plus optional type filtering. However, it omits details like pagination, default limit (though the schema covers it), and what fields are returned, which would matter for an agent deciding how to interpret 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?

Two sentences with zero fluff. The core purpose and ordering are front-loaded, and the convenience-shortcut note is positioned second. Every word 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 list tool with two optional params and no output schema, the description covers the essential semantics: what is returned (latest, non-expired), ordering, and the type filter. It names the alternative tool. Minor gaps like return format and pagination behavior are acceptable given the tool's simplicity.

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 are already documented. The description adds minimal value by restating the type restriction ('optionally restrict to one type') but doesn't elaborate on valid values or the limit parameter. Baseline 3 is appropriate when the schema fully covers parameter meaning.

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 ('return'), the resource ('opportunities'), and the scope ('most recently posted (non-expired)'), plus the ordering ('newest first'). It also explicitly names its relationship to the sibling tool oppcircle_search, distinguishing it as a convenience shortcut for the 'what's new' use case.

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 explicitly frames the tool as a shortcut over oppcircle_search for 'what's new', giving clear guidance on when to use it. It doesn't enumerate exclusions (e.g., when to prefer search), but the convenience-shortcut framing implies search is for more complex queries, which is sufficient 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?

No annotations are provided, so the description carries the full burden. The verb 'List' implies a read-only operation, which is a useful behavioral hint. However, it does not explicitly state that no side effects occur, nor does it mention authentication requirements, rate limits, or ordering of results. For a simple list tool the coverage is adequate but not exhaustive, warranting a 3.

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 two sentences, front-loaded with the primary action and output details, followed by the usage purpose and optional filtering. No wasted words; every sentence earns its place, making it concise 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?

For a simple tool with one optional parameter and no output schema, the description is complete. It tells the agent what will be returned (categories, slugs, counts), how to use the result (as a filter), and the optional search behavior. No critical information is missing 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 already provides a complete description for the only parameter `search`, covering its meaning and example. The tool description adds context about how the returned slugs are used as filters, which is helpful for the overall workflow but does not add new meaning to the search parameter itself. Since schema coverage is 100%, a 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 clearly identifies the verb 'List' and the specific resource 'opportunity type categories', and distinguishes it from sibling tools like oppcircle_list_tags by focusing on categories. It also states the output includes slugs and counts, making the tool's purpose 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 description explicitly states when to use this tool: to obtain slugs for use as the `type` filter in oppcircle_search and oppcircle_latest. It also mentions the optional search filtering, giving clear context for how to use the tool without leaving the agent to infer its role.

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 usefully discloses that results are ordered by popularity and that omitting the search term returns the most-used tags overall. However, it does not mention whether matching is prefix/substring/case-insensitive, what the response shape is, or whether the endpoint is read-only and safe to call repeatedly.

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 sentences, each earning its place: the first states the primary purpose, the second enumerates the tag taxonomy content, and the third gives practical search guidance and ordering behavior. It is front-loaded, readable, and free of 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 2-parameter, no-output-schema tool, the description covers purpose, usage trigger, taxonomy scope, and behavioral notes. It could add the output shape or clarify matching semantics, but the combination of schema and description is sufficient for an agent to invoke it correctly in the intended workflow.

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, but the description adds value beyond the schema: it explains the purpose of the `search` parameter with concrete examples ('germany', 'fully funded', 'phd'), notes that omitting it returns popular tags, and clarifies how returned tags map to filter keys. This enriches the schema's dry 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 states a specific verb ('Search the tag taxonomy') and resource ('13k+ tags'), then explicitly frames the purpose: discovering valid slugs for the `country`, `funding`, and `tags` filters of oppcircle_search. It also lists the dimensions tags encode (countries, funding, level, orgs, deadline months), making it clearly distinct from sibling tools like oppcircle_list_categories.

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 clear context for when to use this tool: before querying oppcircle_search with country, funding, or tags filters, to find valid slugs. It does not explicitly list exclusions or name alternatives, but the use case is specific enough to guide selection. The advice to 'Provide a search term for best results' adds practical usage direction.

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 disclosure burden. It communicates a read-only, aggregate view through 'High-level snapshot' and specifies the output categories, which conveys non-mutating behavior. However, it does not explicitly state that no changes are made, nor does it mention caching, freshness, or permission 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?

Two sentences: the first fronts the value proposition and returned content, the second gives a usage cue. No filler or repetition; every clause contributes to helping an agent decide to call it.

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 overview with no output schema, the description names the key return dimensions (site info, active opportunities, type counts) and explains why that matters (selecting type slugs). It is complete enough to invoke correctly, though 'site info' remains somewhat vague.

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 zero parameters and 100% schema description coverage, so there are no parameter semantics for the description to add. Baseline 4 applies because nothing is left ambiguous for callers.

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 uses a specific verb/resource pair ('High-level snapshot of the Opportunities Circle catalog') and enumerates the exact dimensions it covers (site info, active opportunity count, type breakdown). The phrase 'Good first call' plus the sibling list distinguishes it as the catalog-level overview rather than a search, get, latest, or listing operation.

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 when to call it ('Good first call to understand what's available and which type slugs to use'), giving a clear entry-point context. It does not explicitly name alternatives or exclusions, but the sibling set and the 'first call' framing make the boundary clear.

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 disclosure burden; it usefully reveals default exclusion of expired opportunities and that a formatted list is returned. However, the claim that results are 'newest-first' by default is unqualified and conflicts with the schema's orderby default (relevance when a query is given), and the description never explicitly confirms the operation is read-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?

Five sentences with no filler: purpose, filter model, default behavior, return/next-step, and slug-discovery tip are each front-loaded in a logical order. The category enumeration is a slight length cost but earns its place by clarifying catalog scope.

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 an 11-parameter, zero-required search tool with no output schema and no annotations, the description covers defaults, return semantics, and how to get full details, and the schema covers the rest. It is somewhat vague about the exact content of the 'formatted list,' and the sort-default ambiguity 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 baseline is 3, but the description adds value by grouping parameters ('free-text query plus optional filters by opportunity type, country, funding, and free-form tags') and explaining how to obtain valid slugs. This helps an agent understand which parameters are meant to be combined and where to look up accepted values.

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 'Search the Opportunities Circle catalog' and enumerates the covered opportunity categories, making the verb, resource, and scope unambiguous. Calling it 'the main discovery tool' and pointing to oppcircle_get for full details differentiates search from sibling lookup/listing tools.

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 explicitly positions the tool as the main discovery entry point and gives concrete routing guidance: use oppcircle_get with the returned id for details and list_categories/list_tags for valid slugs. It does not explicitly state when to prefer oppcircle_latest or oppcircle_overview, so the guidance is strong but not fully exclusive.

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