Antevo Executive Brief

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail about what is returned: dated events, the signal to read, and category, while also specifying the days_ahead range and default. 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?

Two tight sentences carry all the essential information: the resource, the output shape, the key parameter, and the question it answers. No filler or redundant restatement of the tool name.

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 is callable with defaults and the core days_ahead behavior is explained, and an output schema exists to document return values. However, scope and market remain unexplained, and with several sibling tools that could plausibly overlap, the description does not fully disambiguate when this tool should be preferred.

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 for missing parameter documentation. It explains days_ahead's range and purpose, but scope and market are left entirely to inference from their names and defaults, with no allowed values or behavior described.

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 defines the tool as a forward calendar of dated events the Executive Brief is watching, including signals and categories. It gives a concrete question the tool answers, so an agent can tell it apart from general market or risk tools, though it does not explicitly contrast with siblings like get_world_events.

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 use context: answering 'what's coming up that could move things?' and explains how to set the horizon via days_ahead. It does not offer exclusions or compare against alternative tools, but the guidance is specific enough for common use.

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 safety profile (readOnly, idempotent, non-destructive, closed-world), so credit here goes to what the description adds: that the institutional read is 'longer and assumes more', and that omitting as_of silently returns the newest edition. Both are real behavioral facts not derivable from structured fields.

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?

Very compact — one paragraph with the core capability front-loaded before parameter details. The em-dash clause and parenthetical defaults are dense but every clause carries information; nothing is padding.

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 values need no explanation, and all three parameters get semantic treatment. The one gap is how an agent discovers valid 'area' values — no pointer to list_coverage — which is minor but real for a required parameter.

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 carries the full burden and largely meets it: it enumerates scope values with the default, gives the as_of date format and its fallback behavior, and provides example area slugs. The area parameter's accepted vocabulary is still only shown by example, not defined.

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 resource — one coverage area's note, in full — and anchors it with concrete area slugs ('real-assets-shipping', 'real-assets-aviation'). The 'one ... in full' framing contrasts implicitly with the sibling list_coverage, though no sibling is named explicitly, which keeps it short of a 5.

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 explains how to use the scope and as_of parameters (defaults, what 'institutional' implies, newest vs past edition), which is useful operational guidance. It never says when to reach for this tool rather than list_coverage or the executive-note siblings, so usage routing is only implied.

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?

Even though annotations already mark the tool as read-only, idempotent, and non-destructive, the description adds meaningful behavioral detail: as_of returns the brief as published on a past date, the full brief is large, sections limits the payload, and 'plain_language' provides a specific desk-rendering with sub-fields. This goes well beyond what the annotations reveal and helps an agent predict output shape and cost.

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 dense but efficient: it opens with the product identity, then gives parameter usage, then closes with concrete section examples. Every sentence contributes useful information, and the examples make the section filtering behavior concrete without feeling 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?

The description covers the tool's purpose, historical behavior, scope options, and section-level customization, and an output schema exists so return-value documentation is not the description's burden. The missing 'market' parameter and the lack of explicit sibling differentiation are material but not fatal gaps. Overall, an agent can use this tool effectively in most cases.

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?

With schema description coverage at 0%, the description must compensate for all parameters. It does explain as_of with a date format, scope with valid values, and sections with a rich list of examples. However, it provides no explanation for the 'market' parameter, leaving 1 of 4 parameters entirely undocumented, which is a clear gap for correct invocation.

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—the Antevo Executive Brief—and its editorial contents: hero takeaway, regime, themes, key risks, and market snapshot. It uses retrieval verbs like 'retrieve' and 'fetch,' so an agent can understand what the tool returns. However, it does not explicitly distinguish this from sibling tools like get_executive_desk or get_executive_note, so differentiation is implied rather than stated.

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 concrete usage guidance: pass as_of for a past publication date, choose 'retail' or 'institutional' scope, and use sections to avoid fetching the large full brief. It also includes practical examples for section values. It does not mention when to choose this tool over related sibling tools or state exclusion criteria, so it falls just 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?

Annotations already declare this read-only, idempotent, and non-destructive, so the description carries little safety burden. It adds some useful context—'for today' signals a dated, changing result—but it doesn't disclose anything beyond that temporal framing.

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 with the key differentiator ('longer-form') and finished with content type. No wasted words or repetition of schema details.

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 tool with an output schema and safety annotations, very little is needed to invoke it. The main gap is routing among the closely named siblings get_executive_brief and get_executive_note, which is only hinted at by 'longer-form' rather than stated.

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 there is no parameter documentation burden. The 100% schema coverage plus 0-parameter count make the baseline 4 appropriate; no description-level parameter guidance 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 names a specific resource ('the desk read') with a clear retrieval verb and adds the useful qualifier 'longer-form,' which roughly separates it from the executive brief/note siblings. It doesn't explicitly define what a 'desk read' is or name the sibling it is not, so it falls just short of full clarity.

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 phrase 'longer-form desk read for today' implies this is the in-depth daily analysis option, but the description never states when to prefer it over get_executive_brief or get_executive_note. Usage context is implied rather than explicit, with no alternatives or exclusions 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 declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds that this is the 'permanent record of what was published that day,' usefully implying an immutable historical snapshot, but it says nothing about error behavior for invalid/future dates or missing dates, so it adds only modest 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?

A single compact sentence that front-loads the core action ('One dated Executive Brief in full') before the date format and example use case. Dense but no wasted clauses; slightly clipped phrasing ('One dated ... in full') costs it a point.

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-value detail is not required, and the annotations carry the safety profile. Still, for a 3-parameter tool with zero schema coverage, the description leaves scope/market semantics and the note-vs-brief sibling relationship unexplained, which is a real gap 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% across three parameters, so the description must compensate and largely does not. It documents the as_of format (YYYY-MM-DD), but completely omits the scope and market parameters, including their retail/global defaults, leaving their accepted values and effect unspecified anywhere.

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+resource: fetching ONE dated Executive Brief in full, with the date format called out. It distinguishes itself from list-style siblings by emphasizing a single dated record, though the wording 'Executive Brief' invites confusion with the separate get_executive_brief sibling, which it never disambiguates against.

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 embedded question ('what did the brief say about X back then?') implies a historical/single-date lookup use case, which is useful implicit guidance. However, it never names an alternative such as list_executive_notes for browsing or get_executive_brief, nor states when NOT to use it, leaving the routing decision 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 establish readOnly, idempotent, and non-destructive behavior, so the bar for additional disclosure is lower. The description adds meaningful context about the time-window behavior and the type of information returned, which goes beyond the structured 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?

A single well-structured sentence with no filler. The core purpose is front-loaded and the parameter usage follows naturally.

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?

This is a simple, optional-parameter read-only tool with an output schema and comprehensive annotations. The description covers what the tool returns and how the parameter affects results, leaving no significant gap for an agent 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?

Schema description coverage is 0%, so the description must carry the parameter meaning. It does so by providing the valid range (1..365), the default (30), and the effect on the result (market movement over the period). It does not clarify the odd string typing of the parameter, but it provides substantial 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 a specific verb and resource ('Major indices') and adds the distinguishing element of recent history over a configurable period. It does not explicitly call out how it differs from sibling tools like get_market_snapshot, so it stops short of a 5.

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 explains the intended use of the days_back parameter and what the data shows, giving implied usage context. However, it does not state when to choose this tool over alternatives or mention any exclusions or complementary tools.

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/non-destructive, and the description adds real behavioral context on top: data is QUARTERLY levels, it lags, the newest point is a quarter end and 'never today', and the response states the most recent observation date. That freshness expectation is exactly the kind of trait an agent cannot infer from annotations or 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?

Three dense sentences with zero filler; the core purpose and ordering come first, the freshness caveat and optional window follow. Nothing repeats the title or 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 read-only series fetch with an output schema, the description supplies enough: scope, ordering, lag caveat, and time-window controls. The only gap is the undocumented limit parameter, which an agent could easily get wrong.

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 carry parameter meaning. It does cover since/until (with the YYYY-MM-DD format and narrowing behavior) and implies ticker, but the limit parameter (default 120) is never mentioned, leaving half the parameters undocumented anywhere.

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 names a specific verb+resource (a single macro series by ticker) and specifies scope and ordering (newest first), which cleanly separates it from the sibling search_macro_indicators, which implies multi-series lookup. An agent can pick the right tool without opening either 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?

It tells the agent that since/until optionally narrow the window and that data is quarterly and lagged, which implies the appropriate context of use. However, it never states when to choose this tool over search_macro_indicators or what qualifies as a valid ticker, so the routing guidance is only implicit.

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=true, idempotentHint=true, and destructiveHint=false, so the description does not need to repeat safety behavior. It adds useful context about temporal freshness ('right now') and coverage, but does not disclose deeper behavior such as data delays or aggregation logic.

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, compact, front-loaded sentence that conveys the tool's purpose and coverage with no filler. Every word adds meaning.

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 snapshot tool with an output schema and clear annotations, the description is sufficient. It tells the agent what the snapshot contains and the broad asset classes included.

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 there is nothing for the description to elaborate on beyond the schema. The baseline of 4 applies because no parameter 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 states the tool's scope: a broad, real-time view of markets across indices, FX, commodities, and crypto. It differentiates from narrower siblings like get_indices and get_macro_series, though it does not use an explicit imperative verb like 'Get' or 'Return'.

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 phrase 'right now' implies it is for a current, broad market overview, and the asset-class list suggests coverage. However, it gives no explicit guidance about when to prefer this over related sibling tools such as get_indices or get_risk_radar.

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, non-destructive, and closed-world, so the safety profile is covered. The description adds that the radar is a judged forward-looking assessment with an associated regime, which is useful framing, but it discloses nothing about freshness, latency, or how the as_of snapshot is reconstructed.

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 dense content sentence followed by a short operational sentence; the key payload is front-loaded and no sentence is filler. It is longer than strictly necessary but every clause describes a real attribute of the return.

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, return values need not be explained, and annotations cover the safety profile, so the core is adequate for a read-only tool. The gap is the two undocumented filtering parameters, which neither the schema nor the description makes usable.

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 carries the burden. It documents as_of well (format YYYY-MM-DD, meaning 'radar as it stood on a past date') but says nothing about scope or market, whose defaults of 'retail' and 'global' are unexplained and whose accepted values are unknown.

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 names a specific resource (the risk radar) and enumerates its content: trends, impact, probability, rationale, the governing regime, and confirming/killing indicators. An agent knows exactly what comes back, though it never contrasts itself with the similarly-named sibling track_risk_evolution.

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?

Usage is implied rather than stated: the as_of sentence tells the agent this tool can be called for a historical snapshot, which implies retrospective use. There is no explicit when-to-use, no conditions separating it from get_catalysts, get_executive_brief, or track_risk_evolution.

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/non-destructive, so the bar is lower, yet the description adds real behavioral context: all six layers run large with two truncating, one or two layers return deeper, and row_limits discloses what was in force to distinguish exhausted vs cut-off layers. That is meaningful nuance 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?

Front-loads the core purpose, then layer mechanics, then truncation semantics, then opt-in layers. Dense with parentheticals, but every sentence carries information; 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?

With an output schema present, return values needn't be explained, and the tool covers parameters, defaults, layer behavior and truncation. Complete enough to invoke correctly; lacking only explicit sibling routing.

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 0%, so the description must compensate, and it does: days_back is documented as 1..90 with default 7, and layers enumerates the six named values plus comma-separated syntax and two opt-in layers. Minor gap: no format/type clarification for the string-typed params.

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+resource (geopolitical events over a look-back window) plus scope and payload categories (conflict, chokepoints, sanctions). It names the layer vocabulary and distinguishes itself from siblings like get_risk_radar and get_catalysts by being the raw event feed.

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?

Clear guidance on narrowing with layers, on which layers are in the default set, and on the opt-in reference layers (disasters, displacement). It doesn't explicitly name an alternative sibling tool for when a different view is wanted, which keeps it from 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds the useful operational fact that no account is required, which goes beyond the annotations and helps an agent understand access 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?

The description is two short, information-dense clauses with no wasted words. It front-loads the core purpose and adds the no-account detail without repeating the title or 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 parameterless, read-only, idempotent discovery tool with an output schema, the description provides sufficient purpose and auth context. There are no input parameters to explain, and return values are covered by the output 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?

The tool has zero parameters and schema coverage is 100%, so there are no parameter semantics for the description to add. With no parameters to document, a baseline of 4 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 states that the tool lists what the Antevo Executive connector exposes, and the resource 'capabilities' is clearly distinct from the sibling data-retrieval tools. It avoids pure tautology by adding connector-specific scope, though it does not explicitly name or distinguish a sibling 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?

There is no guidance on when to use this tool versus alternatives such as list_coverage or list_executive_notes. The only usage-adjacent detail is 'No account required,' which is a prerequisite rather than a comparison or selection rule.

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=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds that each item carries the date of its most recent note, a modest behavioral detail, but says nothing about ordering or how many topics to expect.

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 front-loaded sentence; the topic enumeration is long but directly informative about the resource. No filler or repetition, though the trailing list could be trimmed.

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, the description need not explain return values, and annotations carry the safety profile. For a zero-parameter list tool it is essentially complete, with only the sibling disambiguation 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 takes zero parameters, so per the rubric the baseline is 4. The description correctly implies a no-argument enumeration and adds no misleading parameter claims.

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 conveys that the tool returns the set of topics the desk covers, each with a most-recent-note date, so the resource is identifiable. However, it never uses a clear verb like 'list' and does nothing to distinguish it from the sibling get_coverage, leaving the agent to guess which coverage tool to call.

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 explicit when-to-use guidance and no mention of any alternative tool, despite a confusingly similar sibling (get_coverage) and other list_* tools. The phrase 'beyond the daily brief' hints at scope but does not tell the agent when to prefer this tool.

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, destructiveHint=false and openWorldHint=false, so safety is covered. The description does add real behavioral context beyond annotations: results are ordered newest first and each entry carries date, title, subtitle and hero line. It stops short of describing pagination or how the archive is bounded.

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, which is good, but the trailing appositive 'what has been covered, the date of a story, and how a theme developed over time' is muddled and reads as a restatement of the earlier field list rather than new information, costing clarity.

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 shape need not be explained, but the two inputs remain entirely undocumented and there is no routing guidance among five closely related executive_* siblings. For a list tool in a dense sibling cluster, this leaves meaningful gaps.

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% for both parameters (limit, market), and the description says nothing about either — not the meaning of 'market' (default 'global') nor how limit interacts with the archive. With such low coverage the description was the place to compensate and does not.

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 the resource (the archive of past Executive Briefs) and a key property (newest first), so an agent can tell it is a listing/retrieval tool rather than a single-item fetch. Slight friction: the name says 'executive_notes' while the description says 'Executive Briefs', and the sibling set contains get_executive_note, get_executive_brief and get_executive_desk, so the distinction is not spelled out.

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 when-to-use guidance and no named alternative. The description never says to call this to browse history versus get_executive_note to fetch one item, leaving the agent to infer usage from the verb alone.

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 destructiveHint=false, so safety is covered. The description still adds genuinely behavioral context beyond them: dataset breadth (180 countries, some back to 1920), that results carry each series' ticker and actual covered span, and that the corpus is too large to enumerate.

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?

Four sentences, each earning its place: domain scope first, dataset scale second, result shape third, parameter format last. No filler, no repetition of the title, and the key scoping fact 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?

An output schema exists so return values need not be explained, and annotations cover the safety profile, leaving little for the description to carry. It covers domain, scale and the `country` format, with only `limit` semantics missing — a minor gap for a read-only search 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%, so the description carries the full burden and only partially discharges it. It documents the `country` parameter well, including the accepted formats ('Switzerland' or ISO-3 'CHE'), and the opening clause implies what `query` matches, but `limit` (an oddly string-typed field defaulting to 25) is never mentioned at all.

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 ('Find a macro-economic series by name or country') and enumerates the content domain (CPI, rates, indices, house prices, commodities), which is far more than the title restates. The closing line 'they are searched rather than listed' implicitly separates it from the get_macro_series and list_* siblings, so an agent can route without opening a 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?

The description gives clear context for when to reach for search ('There are tens of thousands of series, so they are searched rather than listed'), which is a real usage constraint. It does not, however, name the sibling (get_macro_series) or state the when-not condition explicitly, so the agent must infer that retrieval by known ticker goes elsewhere.

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/non-destructive, so the burden is light. The description nonetheless adds real behavioral context: risks are NOT linked across boards because the brief rephrases them, and detail trades payload size for depth with a concrete size ratio. It omits pricing/rate-limit info, hence not a 5.

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?

Front-loaded with purpose, then scoping and parameter behavior. Dense but each sentence earns its place; nothing is repeated from the schema or annotations.

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 structure needn't be described, and the description handles the temporal semantics and size tradeoffs well. However, with 0% schema coverage it leaves scope and market entirely unexplained, which is a real gap for a 4-parameter 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% for 4 params, so the description must compensate. It thoroughly documents days_back bounds/default and the three detail modes, but says nothing about scope or market (only inferable from defaults 'retail'/'global'), leaving half the parameters undocumented.

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+resource ('track risk evolution') and immediately defines it as the multi-week historical board series, oldest first, which cleanly distinguishes it from the snapshot sibling get_risk_radar. An agent can select it without opening the 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?

Gives explicit context for use ('every risk radar the brief published over recent weeks') and rules for days_back (7..90, default 30) and detail levels. It does not, however, explicitly name when to choose this over get_risk_radar or get_executive_brief, leaving the alternative implicit.

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