Egleze

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

Annotations already declare idempotentHint=true and destructiveHint=false, but the description adds that it records 'privacy-safe operational telemetry for reliability and aggregate usage measurement'—a behavioral disclosure beyond annotations. It also clarifies output limits (no transcript). No contradiction with annotations.

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 compact and front-loaded: purpose, returned artifact, exclusion, and telemetry in four short sentences with no filler. Every sentence contributes to agent understanding.

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 format is covered elsewhere. The description covers what it returns, what it doesn't, and side effects. A minor gap: it doesn't state behavior when both show and episode are omitted (since no parameters are required), which could be ambiguous for the agent.

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 (show, episode, limit) with descriptions. The description only reiterates that filtering is by show and/or episode, adding no syntax or format detail beyond the schema. Baseline 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 states the verb 'Get' and the resource 'episode summary and key points', specifies how to select (by show name and/or episode title), and distinguishes itself by explicitly saying it does not return the full transcript. This separates it from siblings like search_moments or list_shows.

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 provides a clear negative usage guideline ('Does not return the full transcript') and states the tool returns a canonical episode-hub link. However, it does not name any sibling tools as alternatives for cases like full transcripts or latest episodes, leaving some routing to inference.

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?

Annotations already mark idempotentHint=true and destructiveHint=false. The description adds meaningful context: it records privacy-safe telemetry (a side effect) and mentions attribution-verified content and canonical links. This goes beyond what annotations state, though it does not contradict them.

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, front-loaded with purpose and features, and a brief mention of telemetry. No wasted words; every clause contributes to agent understanding.

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 tool with two optional params, an output schema, and clear annotations, the description covers purpose, filtering, and side effects. It does not mention pagination or defaults, but those are in the schema. It is sufficiently complete 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% (both limit and category have descriptive schema text). The description only restates 'optionally filtered by category' without adding new meaning, so it does not exceed the baseline for fully-covered schemas.

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 verb ('Get'), the resource ('newest attribution-verified public podcast moments'), optional filtering, and canonical links. It differentiates from siblings like search_moments and list_shows by focusing on recency.

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 use for browsing the newest moments but does not explicitly contrast with search_moments or other alternatives. It mentions optional category filtering but provides no guidance on when not to use this tool or when to prefer a sibling.

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?

Annotations provide idempotentHint=true and destructiveHint=false, indicating a safe read operation. The description adds valuable behavioral context by noting it 'records privacy-safe operational telemetry for reliability and aggregate usage measurement,' which explains why readOnlyHint is false. This goes beyond annotations and helps the agent understand side effects.

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 no wasted words. The primary purpose is front-loaded, followed by usage guidance and a brief note on telemetry. Every sentence 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?

Given zero parameters, an output schema exists (as indicated by context signals), and annotations cover safety, the description is complete. It explains what the tool does, how to use the results, and the telemetry behavior. Nothing an agent needs to call it correctly is 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?

The tool has zero parameters, so per calibration the baseline is 4. The description doesn't need to add parameter details since there are none, and it correctly focuses on the output and usage.

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 purpose: 'List the topic categories Egleze covers.' It identifies the resource (topic categories) and the action (list), and immediately differentiates it from siblings by explaining how the values are used to filter search_moments and get_latest. This is a precise, actionable definition.

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 to use these values to filter search_moments and get_latest, giving clear context for when this tool is relevant. It doesn't explicitly state when not to use it or mention alternatives like list_shows, but the purpose and usage are clear enough for an agent to select it appropriately.

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?

Annotations already signal idempotent and non-destructive behavior, and the description adds meaningful context by disclosing that the tool records privacy-safe operational telemetry, which helps explain why readOnlyHint is false. It also surfaces the 'attribution-safe' privacy constraint beyond the annotations.

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 the core action front-loaded and the telemetry caveat in the second sentence. Every word earns its place and there is no redundancy with the schema.

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 list tool with an output schema and safety annotations, the description covers purpose, scope condition, and side-effect behavior. Nothing essential is missing for an agent to select and invoke it correctly.

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% for the single limit parameter, including min, max, default, and a clear description ('Max shows (1-200)'). The tool description adds no additional parameter meaning, 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 clearly states a specific verb ('List') and resource ('podcasts/shows represented by currently attribution-safe public Egleze moments'), and includes the output detail 'with moment counts'. This distinguishes it from siblings like list_categories and search_moments by focusing on shows rather than categories or individual moments.

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 context is implied: use this when you need shows that have attribution-safe public moments. However, it does not explicitly compare against sibling tools such as get_latest or list_categories, and provides no 'when not to use' 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?

Annotations already mark the tool as idempotent and non-destructive. The description goes further by disclosing that full transcripts or quotes are not returned, and that telemetry is recorded for operational reliability – useful behavioral expectations beyond the structured annotations. No contradiction with annotations.

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 with no filler. The first sentence front-loads the core action and scope, the second clarifies output limitations, and the third addresses side effects. Every sentence 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?

With an output schema present and zero required parameters, the description is complete: it states what is searched, what is returned, what is excluded, and the telemetry side effect. An agent has all the context needed to invoke this tool correctly without further inference.

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 fully documents all five parameters. The description mentions keyword, topic/category, and date range, which maps to query, category, since, and until, but adds no syntax or format details beyond the schema. Baseline 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 uses a specific verb ('Search') and a specific resource ('Egleze ... public podcast moments'), and further specifies the search dimensions (keyword, category, date range). It clearly distinguishes from siblings like get_episode_summary and list_categories by focusing on moments rather than summaries or catalog listings.

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 clearly implies the intended use: search for moments by keyword, category, and/or date range, with output limited to headlines and summaries. It doesn't explicitly name alternatives or state when not to use it, but the context is clear enough for an agent to select it over siblings.

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