tgden — Telegram catalog

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

No annotations are provided, so the description must carry the full burden. It discloses the output fields (channel name, @username, subscriber count, language, description) and states ranking by subscribers, which is useful. However, it does not explicitly confirm read-only behavior, describe error handling for invalid categories, or mention any rate limits or pagination.

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 defines the tool's function, the second gives usage examples, and the third lists return fields. No redundancy or filler, and the most important information is front-loaded.

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 2 parameters and no output schema, the description is nearly complete. It covers purpose, usage triggers, and return fields. It omits edge cases like invalid category behavior, but these are not essential for core usage, and the schema covers parameter constraints.

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 parameters, with the category parameter listing all valid values and limit having min/max/default. The description adds no additional parameter-level meaning beyond what the schema already provides, so the baseline of 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 clearly states the tool returns top Telegram channels ranked by subscribers for a given category, using a specific verb and resource. It distinguishes itself from sibling tools like search_telegram by focusing on 'best' rankings and provides concrete example queries (e.g., 'best telegram channels for [topic]').

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 says 'Use this when someone asks...' with concrete examples, making the intended use case clear. It does not explicitly mention when not to use it or name alternatives, but the provided triggers are strong enough to guide an agent in choosing this tool 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?

With no annotations provided, the description must convey behavioral traits. It indicates a read-only retrieval (full record) and lists return fields, which is useful. However, it does not mention error handling, authentication requirements, or rate limits. For a simple lookup this is adequate but not deeply transparent.

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 immediately states the tool's purpose and key output fields. Every word earns its place, with 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?

Given the tool has only one parameter and no output schema, the description provides a reasonably complete picture by enumerating expected fields (subscribers, category, language, trust score, description). It lacks explicit handling of not-found cases or return format nuances, but it is sufficient for a straightforward lookup 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 100% for the username parameter, so the baseline is 3. The tool description adds no extra parameter meaning beyond restating that lookup is by @username. The schema already documents that the '@' is optional, so the description adds no new semantic value.

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 this tool retrieves the full record for a single channel by @username, listing specific fields (subscribers, category, language, trust score, description). This distinguishes it from sibling tools like best_channels_by_category or market_listings, which focus on lists or market data.

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 implicitly signals use for individual channel lookups, but it does not explicitly state when to choose this over alternatives or mention any exclusions. For example, it does not say 'for a list of channels, use best_channels_by_category'. This is implied usage rather than explicit 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 must disclose behavioral traits itself. It mentions the listings are 'fresh' and 'extracted from Telegram groups,' which adds context about data source and timeliness. However, it does not explicitly state that this is a read-only operation, nor does it describe return format, pagination behavior, or any caveats—leaving some ambiguity for an agent.

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, well-structured sentence that front-loads the core purpose, then expands with geographic scope and available filters. Every phrase contributes meaningful information without redundancy or fluff.

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 has no output schema and no annotations, so the description carries the full burden. It successfully conveys the tool's purpose, data source, geographic coverage, and filter options—sufficient for an agent to select and invoke it correctly. It could be improved by hinting at the response format, but the description is largely complete for a simple browse/filter 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?

The schema fully documents all parameters with enums and descriptions, including the meaning of 'wanted' and country codes. The description only adds a general statement about filtering by country and type, providing minimal additional value beyond the schema fields. Thus, the baseline score of 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 clearly states the tool's function: browsing fresh classified listings from Telegram groups across multiple countries. It specifies the resource (classified listings), the scope (OTC network, specific countries), and the filtering capabilities (country and listing type), distinguishing it from general search tools like search_posts.

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 clear context for when to use the tool—when browsing marketplace listings from the listed Telegram groups. It implicitly differentiates from siblings by focusing on classified listings, but it does not explicitly state when not to use it or name alternatives, so it falls 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?

With no annotations, the description carries the full burden. It adds useful detail about the specific markets (th, ae, tr, vn, ge, us) and grouping dimensions (country/type). However, it does not disclose potential limitations, such as whether totals include all listing types or only active ones.

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 that is front-loaded and free of unnecessary wording. It conveys the essential scope and grouping information 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 parameterless stats tool, the description is mostly sufficient. It explains the output granularity and marketplace scope. It could clarify what 'type' refers to, but the tool is simple enough that this is not a major 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?

The input schema has zero parameters, so the baseline is 4. The description adds no parameter information but mentions the dimensions of the output, which is helpful context.

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 provides listing totals, grouped by country and type, for the OTC marketplace. It distinguishes from siblings like market_listings, which would provide individual listings. However, it lacks an explicit action verb, slightly reducing its directness.

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 context about the tool's output (totals by country/type) but does not explicitly state when to prefer it over siblings like market_listings or channel_stats. The usage is implied but not directly contrasted with alternatives.

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 transparency burden. It discloses the search scope (catalogued channels, 1k+ view posts) and the return structure (text snippets, channel, view counts). It does not mention ordering or pagination, but for a search tool this is reasonably transparent.

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, information-dense sentence with no redundant phrases. It efficiently conveys scope and return value.

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 simple 2-parameter schema and no output schema, the description adequately covers the tool's purpose, scope, and return shape. Minor gaps exist around usage guidance relative to sibling tools, but the description is complete enough for reliable use.

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 100% coverage with clear descriptions for query and limit. The description adds context that the search is full-text and returns snippets, reinforcing query semantics, but it does not add syntax or formatting 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 clearly states the tool performs full-text search over recent posts from catalogued channels, specifically those with 1k+ views. It distinguishes itself from sibling tools like search_telegram by scoping to catalogued channel posts and specifying return contents.

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 for searching recent posts within catalogued channels with a view threshold, but it does not explicitly say when to prefer this over search_telegram or other siblings. No exclusions or alternative guidance are 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?

With no annotations, the description carries the full burden. It discloses inherent behaviors: requires no Telegram account, searches public catalog, and returns subscriber counts, categories, and trust scores. It doesn't detail pagination or sorting, but covers auth needs and result 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?

The description is two sentences, the first front-loading the core functionality and data scope, the second delivering key usage context. Every sentence contributes meaning, with no waste 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?

It provides catalog scale, data attributes, and the no-account requirement, giving enough context for a search tool without an output schema. It omits exact response formatting and limit behavior, but the schema covers limit semantics, so the description is sufficiently 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 schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds a minor note about using 'type' to restrict entity kind, but this is already implied by the enum. No other parameter meaning is added 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 identifies the tool as performing full-text search over the tgden catalog, specifying exact resource (channels, chats, bots) and scope (public catalog, not user-joined). This distinguishes it from sibling tools like search_posts or channel_stats, which have different purposes.

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 states when to use it: when the user has not joined the communities, and that no Telegram account is needed. It also instructs to use the 'type' parameter to restrict entity kind. However, it doesn't explicitly name alternatives or when-not-to-use relative to specific siblings.

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