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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds the sort semantics (velocity = 24h statements, size = window statements) which is useful behavioral context, but says nothing about result volume, pagination, or rate limits.

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 short clauses, all front-loaded: purpose first, then the sort semantics, then the symbol syntax. No filler sentences and nothing repeated from 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 7-parameter discovery tool with no output schema, the description covers purpose and sorting but leaves pagination (cursor), result shape, and the relationship to sibling search tools unexplained. Adequate to make a call, incomplete for calling it well.

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 86%, so the baseline is 3, but the description genuinely adds meaning the schema lacks: the sort enum values (recent/size/velocity) are undocumented in the schema and are explained here, and the comma-separated OR behavior for symbol is clarified. It omits the 'oldest' sort value and says nothing about limit, cursor, or min_statements.

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 ('List') and resource ('developments') with the three scoping axes (symbol, sector, theme). It does not differentiate itself from the sibling get_topic, which reads like the singular counterpart, so an agent cannot fully disambiguate from the description alone.

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 statement of when to use this tool versus search_statements, trending, or get_topic, and no exclusions or prerequisites. The sort explanations describe behavior of the call, not when the call is the right choice.

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 safety is covered. The description goes beyond them by disclosing the return shape (counts, source_mix breakdown, 20 statements with outlets) and the pagination mechanism via statements_cursor, which is genuinely useful behavioral 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?

Two sentences, zero filler, and the primary scope (what is returned) is front-loaded before the fallback routing to search_statements. Every clause carries information.

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 no output schema, the description carries the return-value burden and does so: it names counts, the source_mix composition, the 20-statement cap, and the cursor for deeper retrieval. For a single-param read tool this 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?

There is a single parameter with 100% schema description coverage, which already explains topic_id and where it comes from. The description only implies the topic via 'one development' and adds no syntax or format detail beyond the schema, 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 (retrieve one development in full) and enumerates what comes back: counts, source_mix, and the 20 newest statements. It also names the sibling (search_statements) it is not, so an agent can separate it from the other topic tools without opening schemas.

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 scopes this tool to the 20 newest statements and routes older-statement retrieval to search_statements, including the exact arguments to pass (topic_id and the returned statements_cursor). The when-to-use and when-to-use-something-else conditions are both stated.

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, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely useful behavioral context beyond them: the data is stable and should be fetched once rather than repeatedly. It does not mention response shape, but with no output schema this is a modest gap.

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 enumerated contents, then the operational hint. The first sentence is a dense list but every element earns its place. No wasted preamble.

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 no output schema, the description carries the burden of explaining what comes back, and it does list the returned categories (window/size, incidents, theme ids, accepted enum values). A caller knows what to expect. It could be more explicit about the structure of those values, but it is adequate.

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 there is nothing for the description to disambiguate; the baseline of 4 applies. No parameter-level confusion is possible.

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 the concrete contents returned: the data window and size, known incidents, themes with their ids, and accepted enum values. That is far more specific than the generic name 'reference'. It does not explicitly distinguish itself from the sibling 'themes', which plausibly overlaps on the theme list, so it falls 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 only guidance is 'Call once; it rarely changes,' which addresses call frequency and caching rather than when to choose this tool over siblings like 'themes' or 'find_topics'. Usage is implied (consult for available enum values) but no alternatives or exclusions are named.

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, openWorld), so the description's job is supplementary — and it delivers: it enumerates the returned row fields (mentions, topics, sources, sentiment counts, score, change) and warns that omitting entity_kinds mixes companies with rates, commodities and central banks. This is meaningful behavioral context 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-loaded with the purpose and a quotable use case before diving into parameter nuance. Dense but largely waste-free; the parameter detail could be tightened marginally, and the second sentence is a slightly redundant gloss on the first.

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 7-parameter filtering tool with no output schema, the description anticipates the important gaps: it lists the row fields that will be returned, explains the period windows, and flags the entity_kinds default mixing behavior. Only minor omissions remain (e.g. what 'score' represents, limit interaction).

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 71%, and the description compensates for the gaps well: it documents the full entity_kinds vocabulary (equity, etf, index, rate, fx, crypto, commodity, org, private, country) that the schema only shows as a bare string, states that sector applies only when rank=symbols, and explains the sort=change incompatibility with period=window. These are cross-parameter constraints the schema cannot express.

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?

Opens with a precise verb+resource: "Rank symbols (or the 11 GICS sectors) by news attention," and adds a concrete use case ("which tickers are suddenly in the news"). It is clearly distinguished from siblings like get_topic or sentiment_series, though the relationship to the closest sibling `trending` is left implicit.

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 clear context for when to reach for it (sudden news attention on tickers) and conditional guidance — sort=change is unavailable for period=window, and entity_kinds should be set to "equity,etf" for tradable tickers. No explicit when-not or named-alternative routing to siblings, so it stops 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 readOnly, idempotent, open-world and non-destructive, so safety is covered. The description adds real behavioral context beyond that: results are newest-first, pagination works by passing next_cursor back as cursor, and null means no more pages, plus filter semantics for importance_min and source_type.

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 purpose in sentence one, then uses tight parameter annotations. Every line earns its place, though several lines duplicate schema descriptions rather than adding new information.

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 an 11-parameter, no-output-schema search tool, the description covers ordering, pagination, and the key filters, and annotations cover the safety profile. It is largely complete, though it could say more about what a 'statement' contains and the unused sector/theme_id/topic_id filters.

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 the schema already documents all 11 parameters. The description largely restates schema text (limit range, ISO-8601 format, comma-separated symbols, source_type effects), adding only the clarification that since/until apply to the article's publication time. 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?

States a specific verb+resource ('Search extracted news statements') and adds ordering ('newest first'), which distinguishes it from sibling lookups like get_topic or themes. It does not explicitly name an alternative, but the resource is concrete enough for an agent to recognize.

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?

"Use for 'what is the news saying about X'" gives a clear activation context, and the symbol/source_type lines hint at narrowing behavior. There are no explicit exclusions or named alternatives, so it falls short of a 5.

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

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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: it documents the omitted empty buckets, and warns that unless `until` is set the series ends on a still-incomplete day/hour so a low last bucket must not be read as a drop. That is precisely the kind of interpretive gotcha an agent would otherwise misread as data.

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?

Purpose and scoping rule are front-loaded in the first sentence, followed by the return-bucket contract and then the last-bucket caveat. The bucket specification sentence is dense with seven field names and a formula in one breath, but nearly every clause carries information, so the length is defensible.

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 no output schema, the description carries the full burden and meets it: it defines each bucket field, the score formula, source counting, empty-bucket omission, and time-range defaults. An agent can both call the tool correctly and interpret its results from this text alone.

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 86%, so the baseline is 3, but the description adds a cross-parameter constraint the schema cannot express: the four entity parameters are all optional and nullable in the schema, yet the description imposes 'exactly one of' and specifies the interval default windows. That is genuine semantic value above the field 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 first line states a specific resource (news volume and sentiment), a specific shape (over time), and an exact scoping rule (one of symbol, sector, theme_id or topic_id). That is enough to separate it from siblings like search_statements, trending and themes 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?

It gives concrete selection guidance: pick exactly one entity dimension, and interval=hour is bounded to 14 days (default 7) while interval=day covers the whole window. It never names a sibling tool or states when to prefer `trending` or `search_statements` over this one, so the 'vs alternatives' half of the bar is unmet.

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), so the bar is lower. The description still adds real behavioral context: the non-obvious caveat that counts remain whole-theme even when filtered by symbol/sector, plus the id-reuse contract with other tools. No return-shape or pagination detail, but that is minor here.

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 what a theme is and what it returns, then the filter caveat and the id hand-off. The middle sentence is slightly convoluted ('the counts are still those of the whole theme, so use...'), but every clause 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 no output schema, the description does the work of enumerating the returned fields and the filter caveat, and it explains the id contract for downstream calls. Adequate for a 3-param, 0-required list tool; only the missing sibling differentiation keeps it from being fully 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 coverage is 100%, so baseline is 3. The description goes beyond the schema by explaining the semantics of the symbol/sector filter (themes are matched, but the counts are not scoped to that symbol), which is the one behaviorally surprising parameter effect and is not captured in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

It names the resource ('standing subjects the news is grouped into') and enumerates what each item carries (developments, statements, 24-hour volume, sources, sentiment counts), which is more specific than a tautology. It distinguishes itself from search_statements but never contrasts with the sibling find_topics, which an agent could easily confuse it with.

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 a clear conditional: 'With symbol or sector: only the themes that have statements about it,' and routes the agent to search_statements when per-symbol statements are wanted. It also states the follow-on usage ('use the returned id as theme_id in the other tools'). Missing is any guidance on when to prefer this over find_topics or get_topic.

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/openWorld/non-destructive, so safety is covered. The description adds real behavior: the time windows per kind, that kind=slot caps at 10 stories per slot over 7 days, that `trending` labels encode slot membership and rank, and that each item carries source/sentiment counts and a newest statement.

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 the one-line purpose and the when-to-use trigger, then structured by parameter. Dense but each sentence carries a distinct fact; the only mild redundancy is restating the kind live/slot windows already in 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?

No output schema exists, yet the description characterizes the return payload (source count, sentiment counts, newest statement, trending slot/rank labels) and the slot-range limit caveat, which is what an agent needs to call and interpret this 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%, so baseline is 3, but the description adds constraints not obvious from the schema: symbol takes one code only, and limit is taken from the top of the API ranking with `total` in the result revealing the true count. kind semantics are reinforced rather than merely repeated.

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 (the developments most outlets are reporting) and its live/slot scopes, and names the sibling find_topics as the alternative for a different time window. An agent can distinguish it from siblings 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?

Explicit routing instructions: use for 'what is moving right now' (kind=live, last 2 hours), and if you want the whole day rather than 2 hours, use find_topics with sort=velocity. It even tells the agent to raise limit when kind=slot's top-of-slot isn't enough.

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