Talking Heads on Markets

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds the contextual detail that it returns 'attributed views and catch-up' and expects a slug, but it does not disclose any other behavioral traits like pagination, data freshness, or whether it returns live data. Given the annotations cover the safety profile, a 3 is appropriate.

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, concise sentence with an example embedded, making it efficient and directly to the point. No filler words; it front-loads the result type and the key input.

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 a simple input (one slug) and an output schema that may describe the return structure, so the description need not explain return values. However, given the jargon 'talking head' and the lack of usage guidance, the description is not fully complete for an agent to call it correctly in all contexts. It is adequate for a simple read operation but leaves room for improvement.

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 0%, so the description must compensate. It provides an example slug ('lyn-alden') that hints at the format, but it does not explain what a slug is or what values are acceptable beyond the example. The parameter 'slug' is just a string in the schema; the description adds minimal meaning by giving an example.

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 the tool retrieves attributed views and catch-up for a talking head by slug, with an example slug provided. However, the term 'talking head' is jargon and not clearly defined, which may confuse agents. It is distinguishable from siblings like 'get_catchup' only by the focus on 'attributed views and catch-up' for a talking head, but the purpose is not as crisp as it could be.

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 when you have a talking head's slug, but it does not explicitly state when to use this tool versus alternatives. There is no mention of when not to use it or how it differs from 'get_catchup' or 'get_latest', which might also retrieve similar data. Clear guidance is missing.

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 declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to repeat safety. It adds useful context about the catalog's scope (analysts, topics, instruments) and its role as a name-resolution step, which goes beyond what annotations alone convey.

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 short sentences with no filler. The first sentence states what the catalog contains, and the second gives action-oriented usage guidance. The structure is front-loaded and 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 zero-parameter, read-only catalog tool with an output schema and strong annotations, the description is complete. It tells the agent what the catalog contains and when to use it, and nothing else is needed to 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?

The tool has zero parameters, so the baseline is 4. The description mentions the entity categories the catalog covers, which is semantically useful even though there are no parameters to document.

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 identifies the resource as the catalog of analysts, topics, and instruments tracked by Headge, and states its purpose: resolving names before other tools. It lacks an explicit verb like 'lists' or 'returns,' but the meaning is clear and it is implicitly differentiated from the individual getter siblings.

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 timing guidance: use this tool to resolve names before using other tools. It does not explicitly name alternatives or exclusion conditions, but for a zero-parameter catalog tool the context is sufficient.

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 declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint, fully covering the safety profile. The description adds useful context: the data is time-bounded to today and 'mix' is a count rather than a ratio or object. However, 'Headge has no house view' adds a cryptic caveat without explanation, detracting from behavioral clarity.

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 short sentences with the key categories front-loaded, so it is appropriately sized. However, the final sentence 'Headge has no house view' does not earn its place—it is unexplained jargon that raises questions rather than resolving them, so not every sentence is justified.

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 parameters, the description does not need to cover return values or argument semantics. It is adequate for a simple read tool but lacks usage context (when to call it) and leaves the 'Headge' caveat unresolved, which is a noticeable gap given quick sibling navigation would be helped by a usage pointer.

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 the schema needs no description, and the baseline is 4. The description's clarification that 'Mix is a count' addresses output semantics rather than parameters, which is acceptable since there is an output schema to carry the return format.

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 the resource (today's catch-up) and the categories it contains (mix by horizon, new views, flips, divergence), going beyond the name. However, it reads as output content rather than a clear purpose statement, and the jargon sentence 'Headge has no house view' is unexplained and obscures the tool's function. It does not distinguish this from siblings like get_latest or get_view.

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?

No guidance on when to use this tool versus the siblings (get_latest, get_view, get_topic, etc.). There is no mention of alternatives, exclusions, or the context in which a catch-up summary is preferred over a latest-items or view query.

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 declare readOnly, idempotent, and non-destructive behavior, so the safety profile is covered. The description adds that results include both attributed views and Headge-mapped related views, but it does not explain what 'Headge's mapping' means or disclose pagination/limit behaviors.

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 concise sentence with no filler. However, 'Headge's mapping' is unexplained and the sentence is a noun phrase rather than a clear action-oriented statement.

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-only tool with one parameter and an output schema, the definition is mostly adequate. The unexplained proprietary terminology and lack of sibling differentiation leave enough ambiguity that an agent may not fully understand the result set or when to call this 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 0%, but the description ties the sole parameter to the ticker being queried via 'this ticker', giving it practical meaning. It leaves format and notation unspecified, but for a single string parameter this is mostly sufficient.

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 that the tool returns attributed views naming the given ticker, plus related views labelled as Headge's mapping. This conveys the resource and scope clearly, although it lacks an explicit verb and does not contrast with siblings like get_view.

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 guidance on when to use this tool versus alternatives such as get_view or search. The only implicit context is the ticker parameter, which is not enough to route an agent confidently.

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 declare the tool read-only, idempotent, and non-destructive. The description adds meaningful behavioral nuance beyond annotations: the ET timezone definition, newest-first ordering, the Bullish/Bearish split, and the important caveat that it is publication day rather than forecast horizon. This is useful, though it does not address edge cases like empty-day 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?

The description is three tight sentences with no wasted words. The core message is front-loaded, and each additional clause adds meaningful precision without 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 no-parameter, read-only tool with an output schema, the description covers the essential contextual details: temporal scope, timezone, ordering, output grouping, neutral-view placement, and the publication-day caveat. An agent has enough information to invoke the tool correctly without needing further clarification.

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 there is no burden on the description to explain parameter behavior. The description's temporal context (US session day, ET) still helps calibrate what 'latest' means, but no parameter-level documentation is needed.

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 resource as today's placed views (US session day, ET) and specifies ordering and the Bullish/Bearish split. It does not explicitly name or contrast a sibling tool like get_view or get_catchup, but the temporal scope makes the purpose reasonably distinct.

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 call this tool: it returns today's placed views, newest first, and clarifies that 'today' is the US session day in ET. It does not state explicit exclusions or alternate-tool recommendations, so it falls just short of full usage routing 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 cover the read-only, idempotent, non-destructive nature of the tool, lowering the bar. The description adds modest context by noting the data is 'current' and restricted to a 'closed catalog', but it does not explain edge cases, authorization, or how 'attributed views' are defined.

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 with no filler. It conveys the key information—current views, one topic, closed catalog, example values—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 simple one-parameter, read-only tool with an output schema and strong annotations, this description is largely complete. The only notable gap is leaving the term 'attributed views' unexplained, but the overall context is sufficient 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 coverage for the single 'slug' parameter is 0%, so the description must compensate. It does so by illustrating valid values ('gold, inflation, xlk') and clarifying that slugs refer to topics in a closed catalog, giving an agent enough to format the parameter correctly.

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-resource pair: retrieving current attributed views for one topic in a closed catalog, with concrete examples ('gold, inflation, xlk'). It is specific enough to understand the core function, though it does not explicitly distinguish itself from siblings like get_catalog or get_view.

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 this is for fetching views on a single topic slug, but it gives no guidance on when to choose this tool over siblings such as get_view, get_latest, or search. No alternatives or exclusion criteria are mentioned.

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 cover read-only, idempotent, and non-destructive behavior, so the description only needs to add contextual detail; it does so by noting the result includes a source URL for citation. It does not disclose behavior for missing/invalid ids, but that is a minor gap given the 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?

The description is a single, front-loaded sentence with no filler. It conveys the resource, the retrieval criterion, and a distinctive output characteristic in very few words.

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 single-parameter schema, the presence of an output schema, and annotations that establish a safe read-only operation, the description covers the essential context. It could mention what 'attributed' means or behavior for missing ids, but nothing critical 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?

Schema description coverage is 0%, but there is only one parameter, view_id, which the description usefully ties to the 'by id' retrieval behavior. It adds minimal semantic value beyond the field name and type, but it is sufficient for a simple integer identifier.

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 ('get'), a resource ('view'), and a retrieval mode ('by id'), which clearly differentiates it from list/search siblings. The phrase 'attributed view' and 'source URL for citation' add helpful specificity, though what an 'attributed view' is could be clearer.

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 fetching a single view when you have its id, and the mention of citation hints at a use case. However, it gives no explicit guidance on when to choose this over siblings like get_latest or search, leaving exclusion logic 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 signal read-only, idempotent, non-destructive. The description adds that it resolves queries into three entity types, but does not mention ranking, limits, or query-matching behavior. No contradiction.

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?

One sentence, front-loaded, no filler. 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?

A simple single-parameter read-only search with an output schema. The description plus annotations are nearly complete; the only gap is usage-vs-siblings guidance.

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 describes q only as a string, with 0% description coverage. The tool description adds that q is a query and names result categories, but gives no syntax, format, or matching behavior for q.

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 ('Resolve') and resource ('analysts, topics, and instruments'), making the search scope clear and distinguishing it from the sibling get_* 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?

No guidance on when to use search instead of the get_* tools or how it relates to them. The intended context must be inferred from the name and siblings.

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