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

With no annotations provided, the description carries the full burden. It discloses the read-only nature ('Find', 'Returns') and specifies the output content (tool names, episode references, YouTube links). It does not mention pagination or ordering, but for a simple lookup tool this is adequate and adds value beyond the schema.

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 the core purpose and return value, with no filler. Every phrase adds value, and the optional filter is mentioned succinctly.

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 search tool with no output schema, the description fully explains what to expect: results include tool names, episodes, and timestamped YouTube links. It is self-contained and sufficient for an agent to invoke 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%, with both limit and query fully documented, so the description does not need to compensate. The description only reiterates the optional keyword filter, adding no extra semantic detail beyond the schema 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?

The description uses a specific verb ('Find') with a clear resource ('community tools and open-source projects discussed on Entra.Chat episodes') and explicitly states what it returns (tool names, episodes, timestamped links). This differentiates it from sibling tools like search_entra_podcasts, which likely handle broader podcast search.

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: to locate tool mentions across episodes, with an optional keyword filter. It does not explicitly name alternatives or exclusions, but the purpose is distinct enough that an agent can infer when 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.

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

With no annotations, the description carries the full behavioral burden. 'Retrieve' implies a read-only operation and it describes the return contents, but it does not address permissions, rate limits, pagination, or error behavior. It adds useful output context but only partially covers behavioral traits.

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 the core action and identifiers, then the return contents. Every sentence earns its place and there is no 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 low-complexity retrieval tool with rich schema descriptions, the definition is complete. It explains the return payload even though no output schema exists, and the input semantics are covered by 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 100%, so the schema already documents both parameters in detail. The description adds that the lookup can be by video ID or publication date, but this is largely redundant with the schema 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 and resource: retrieve a specific Entra.Chat episode. It clearly distinguishes itself from list/search siblings by emphasizing a single episode identified by video ID or publication date.

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 context for when to use it: when you have a YouTube video ID or publication date for a specific episode. However, it does not explicitly name alternatives such as list_episodes or search_entra_podcasts or state 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?

With no annotations, the description carries the burden of explaining behavior. It discloses that partial names match, that returning guests show all their appearances, and enumerates the exact fields returned. It does not mention error handling or auth, but the read-only nature is clear from 'Get'.

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 focused sentence that front-loads the core purpose before detailing the return contents. Every clause adds useful information, 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?

For a one-parameter lookup with no output schema, the description does a good job of specifying the return structure: profile links and episode details (number, title, date, URL). It omits edge-case behavior like multiple partial matches, but overall it gives an agent enough context to understand what the tool returns.

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 already describes the 'name' parameter well (case-insensitive, partial names match), and the description mostly restates this. High schema coverage means the description adds little beyond what is already in the input schema, so 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 opens with a specific verb and resource: 'Get a specific Entra.Chat guest by name.' It clearly distinguishes this from sibling tools like list_guests or get_episode by focusing on a single guest and describing the exact return payload (profile links and episode appearances).

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 the tool is for targeted guest lookups ('specific guest by name') and notes that partial names match, but it does not explicitly contrast with alternatives such as list_guests or search_entra_podcasts. There is no when-to-use or 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?

No annotations are provided, so the description carries the burden; it discloses the return fields (title, date, duration, guests, URL), which helps. However it says nothing about pagination defaults/total counts, result caps, or auth needs, and those behaviors are only implied by the schema. Adequate but not rich given zero annotation coverage.

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 tightly written sentences with zero waste: purpose and filters first, return payload second, routing guidance last. Nothing redundant or padded.

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 read/list tool with full schema coverage, the description covers purpose, filters, and return shape, which is what the agent needs. It omits any mention of pagination behavior, but since limit/offset are self-documented in the schema and no output schema exists, the gap is minor.

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 year/month/guest/limit/offset are already fully documented in the schema. The description restates the filtering dimensions (year/month/guest) but adds no syntax or format detail beyond what the schema already gives, 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?

States a specific verb and resource ("Browse the Entra.Chat episode archive") plus the filterable dimensions, and names the sibling tools (get_episode, search_entra_podcasts) it is distinct from. An agent can tell this is the enumeration tool versus the retrieval/search tools without opening any 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?

Explicitly routes the agent: "Use this to discover what episodes exist before using get_episode or search_entra_podcasts." It gives clear context and names alternatives, but does not explain when to prefer search_entra_podcasts over this list tool (e.g. for keyword lookups), so the boundary between the two discovery paths is left 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains what the tool returns and implies a read-only nature via 'Browse.' It also indicates the tool does not provide full episode lists, directing to get_guest for that. The description does not explicitly mention side effects, but for a directory listing tool, the behavior is well-understood and clearly described.

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 three sentences, each earning its place. The first sentence states the purpose, the second details the return contents, and the third provides a pointer to an alternative. It is front-loaded with the primary purpose and contains no 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?

Given that there is no output schema, the description appropriately explains the return structure (profile links, episode count, latest appearance). It also covers the tool's scope and directs users to a sibling tool for more detail. The input schema handles parameter documentation, and the description provides the necessary context for a listing tool. The tool is simple enough that this description is 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the input schema already provides. The parameters (limit, query, offset) are fully described in the schema, and the description focuses on the return structure rather than parameter details. No additional value is added here.

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: 'Browse the directory of Entra.Chat podcast guests.' It specifies the resource (guest directory), the verb (browse), and the return structure (profile links, episode counts, latest appearance). It also distinguishes itself from the sibling tool get_guest by directing users there for full per-guest episode lists.

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 explicit guidance on when to use this tool versus an alternative: 'Use get_guest for a full per-guest episode list.' It implies that this tool is for browsing the directory and getting summary information, and it gives a clear pointer for a more detailed need. However, it doesn't explicitly discuss other siblings like search_entra_podcasts or list_episodes, but the context is sufficient for most use cases.

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 carries the full burden and does well: it discloses the hybrid fusion algorithm (Reciprocal Rank Fusion), the external dependency (OPENAI_API_KEY), and the nature of responses (excerpts, metadata, deep links). It does not cover fallback behavior when the API key is missing or any error/rate-limit behavior, but for a read-only search tool this is acceptable transparency.

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, no fluff. The first sentence states the action and resource, the second describes the return values and search algorithms, and the third provides configuration guidance. Every sentence contributes, and key 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?

The description covers the tool's purpose, output contents, mode behavior, and dependencies. It lacks a precise output schema (none provided) but gives enough detail that an agent can infer what to expect. It does not explicitly say it searches across all episodes, but that is implied. Overall, it is adequate for the tool's complexity.

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 baseline is 3. The description adds real value by explaining what hybrid mode does (BM25 + semantic via RRF) and the API key requirement for semantic mode. This exceeds simple schema labels and helps the agent choose the right mode.

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 transcripts of the Entra.Chat podcast' — a specific verb and resource. It clearly distinguishes from siblings (get_episode, list_episodes, list_guests, find_tool_mentions) by focusing on cross-transcript search. It also enumerates the output: excerpts, episode metadata, guest names, and timestamped deep links.

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 clarifies when to use this tool: for natural language or keyword search over transcripts. It explains the three modes (hybrid, semantic, keyword) and gives practical guidance — semantic requires OPENAI_API_KEY, keyword works with none. It does not explicitly contrast with sibling tools, but the purpose and sibling names imply the distinction.

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