asha-news

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

With no annotations provided, the description carries the behavioral disclosure burden. It usefully notes that results are persisted and only meaningful when status=available, and warns against misinterpreting empty/unavailable responses. It does not detail return format or permissions, but for a read-only retrieval tool this adds meaningful operational 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?

The description is two dense sentences, front-loaded with the resource identity and immediately followed by a critical usage caveat. Every word contributes to the agent's understanding, with no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With four optional, well-documented filters and no output schema, the description conveys the core return concept (blindspots/coverage gaps) and the critical posture-status caveat. It could mention the response shape or typical fields, but the existing caveat prevents the most likely misuse.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and each parameter already has clear meaning (limit, topic, min_mci, posture). The tool description adds no parameter-level details beyond the schema, so the baseline score of 3 is appropriate.

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

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

The description identifies the resource as 'Persisted Asha Blindspots / coverage gaps from posture analysis' and clearly implies a retrieval operation, distinguishing it from sibling search/brief tools. However, it lacks an explicit verb such as 'list' or 'get', making it slightly less direct than ideal.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool ('Use only when status=available') and provides a clear exclusion ('do not infer gaps from empty or unavailable responses'). It does not name alternative tools, but the conditional usage guidance is strong and actionable.

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

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

With no annotations, the description carries a heavier burden. It discloses important behavior: returns a delta of breaking items with age/expiry and should be polled with a since cursor. It does not detail auth/rate limits or exact response shape, which a full dialogue would still need.

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 dense sentences and no wasted words. The description front-loads the core resource and then provides the integration pattern, making it highly readable and actionable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool without an output schema, the description covers the essential task, return content concept, and polling pattern. It lacks a precise indication of the response format or how expiry is represented, but is otherwise complete enough to proceed.

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 description adds meaning to the 'since' parameter by recommending its use as '{last generated_at}' for polling deltas. Schema coverage is only 50%, but this definition compensates for the most significant parameter; 'limit' remains under-described but is inferable.

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's resource scope: 'active alerts plus breaking-flagged articles with age and expiry.' It distinguishes this from general asha feed/digest tools, though it lacks an explicit action verb like 'list' or 'retrieve.'

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 explicit usage context: 'Poll every 60s with since={last generated_at} for deltas; notify your user on new items.' This is strong operational guidance, but it stops short of contrasting with sibling tools or stating when not to use 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?

No annotations are provided, so the description carries the transparency burden. It does disclose that results are 'grouped multi-source coverage,' which is useful behavioral context, but it does not mention pagination, sorting, error behavior, or side effects. 'Search' implies read-only, but this is implicit.

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 deliver the core purpose and output behavior with no filler or redundant wording. 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 simple two-parameter search tool, this description is minimally adequate: it states the purpose and high-level return shape. However, with no output schema and no annotation support, it leaves the 'grouped multi-source coverage' structure underspecified and does not clarify how limit affects results.

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. 'By topic' clarifies the required q parameter, but the optional limit parameter receives no semantic explanation. This is partial but insufficient for full parameter understanding.

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

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

The description uses a specific verb and resource: 'Search story clusters by topic.' It also adds a distinguishing outcome—'Returns grouped multi-source coverage'—which differentiates it from generic siblings like asha_search and asha_search_articles.

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 'by topic' implies that this tool is appropriate for topic-based cluster searches, but it does not explicitly state when to use it over sibling search tools or when not to use it. No alternatives or exclusions 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?

With no annotations provided, the description carries the transparency burden. It discloses that the tool is server-rendered, structured by category, Palestine-desk led, and includes publish time/ages per item; it also indicates that the content should be relayed unmodified. It could add more about default, size, or limitations, but it gives meaningful behavioral context beyond the raw 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?

The description is compact and front-loaded: the first sentence establishes the tool's output, the second lists output formats, and 'Relay as-is' adds a clear consumption hint. Every clause adds value, with no filler or repetition.

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 tool with two optional parameters and no output schema, the description covers the main behavioral, content, and formatting aspects well. It does not mention the per_section limit or explicitly distinguish from similar daily-brief sibling tools, but the core rubric arguably covers that gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema describes only 50% of parameters, and the description enriches the format enum by specifying markdown for chat, html for a standalone page, and json for structured data. However, the per_section parameter is not addressed at all beyond its numeric bounds, so the agent has to infer its meaning from the 'per item' text and the parameter name.

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 tool as a server-rendered daily brief with categorized sections, item publish times, and age, so the core function is comprehensible. It is not explicitly phrased with a verb like 'retrieve' or 'get', and it does not contrast itself with closely related siblings such as asha_digest or asha_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?

The description instructs when to choose markdown, html, or json output and says 'relay as-is,' which is useful for the format. However, it offers no guidance on when to use this daily-brief tool versus the many sibling tools (digest, breaking, feed, market context, etc.), so an agent may not know whether this is the appropriate tool for a given request.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it does very little. The description doesn't explain that 'clustered' implies grouped/related stories, whether the result set is deduplicated, how many clusters to expect, whether the digest is time-bucketed, or what the JSON response shape looks like. The format parameter is documented in the schema, so the description's only contribution is the word 'clustered,' which is not enough context for an agent to predict the tool's behavior.

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 sentence with 12 words, making it extremely efficient. The format explanation is also concise and the parameters are simple with only two total. While one could argue the description is too sparse, for a simple read-only endpoint with two parameters, this level of conciseness is appropriate. The structure is front-loaded with the key identifier 'public news digest' followed by the format caveat.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with only 2 optional parameters and no required fields, the description covers the essential behavior of retrieving a news digest and explaining the format switch. The sibling named asha_daily_brief suggests a potential alternative that an agent might confuse this with, and ideally the description would clarify how a 'digest' differs from a 'brief.' However, given the tool's simplicity and the lack of an output schema, the description is reasonably complete 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 coverage is 50%: the format parameter has a description ('Default markdown') that clarifies its default value but not its semantics, while limit is undocumented beyond its type and range. The description's mention of format=markdown vs JSON maps directly to the format parameter. This is a borderline case: the description adds a little value by explaining the format parameter's output distinction (prose vs clusters), but the 'clustered' semantics of the JSON output remain unclear.

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 'Clustered public news digest' clearly identifies the tool's resource (news digest) and hints at its function (clustering), which places it at a basic level of clarity. However, 'digest' is used as a noun rather than a verb, so the tool's action is implicit rather than stated, and the description doesn't distinguish it from siblings like asha_daily_brief or asha_feed. The format parameter detail adds functional meaning but doesn't clarify the core purpose beyond what the name suggests.

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 is provided for when to use this tool versus alternatives like asha_clusters_search or asha_feed. The description does not explain what 'clustered' means in practice, when a user would prefer this over the daily brief, or what kind of news items appear here that wouldn't appear elsewhere. The only usage signal is the format parameter description, which is insufficient for an agent to make an informed 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?

No annotations are provided, so the description carries the full burden. It discloses the tool's nature as a reference contract and its key principles (evidence-first, pro-Palestine, citations preserved), but it doesn't describe what the tool returns (e.g., is it a text blob? a structured list?) or any side effects. Since it's a read-only reference tool, the lack of side-effect disclosure is less critical, but the return format is unspecified.

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 sentences, front-loaded with the core purpose and followed by a clear usage directive. Every word earns its place; no fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema, no annotations), the description is complete enough. It explains what the tool is, its key principles, and when to use it. It could mention what the output looks like (e.g., 'returns the guidelines text') but that's a minor gap for a reference 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?

The tool has zero parameters, and the schema coverage is 100% (vacuously). The description adds meaning by explaining the tool's content and purpose, which is sufficient for a parameterless tool. There is no parameter ambiguity to resolve.

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

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

The description clearly states the tool's purpose: it provides the editorial voice contract for Asha News, specifying evidence-first, openly pro-Palestine, and citations preserved. It distinguishes itself from sibling tools by being a reference/guideline tool rather than a content generation or search tool, though it doesn't explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs to read this before generating derived briefs, titles, or social posts, which provides clear context for when to use it. It doesn't explicitly state when not to use it or name alternative tools, but the instruction is actionable and contextually clear.

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

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

With no annotations, the description adds the return format and the 'source-backed' nature of the news. However, it does not disclose filtering capabilities, default behavior, or any limitations. It provides minimal but non-trivial behavioral context, so a 3.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose, and no redundancy. Efficient and well-structured, a 5.

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 explains what the tool returns but omits usage context and differentiation from the many sibling news tools. Given the schema covers parameters, the description is adequate but leaves a significant gap in guidance, so a 3.

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 100% coverage with descriptions for q, limit, category, and timeframe. The description adds no additional parameter context, 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?

The description uses 'Returns' as the verb and specifies the resource ('Latest source-backed news from the Asha News archive') plus the key fields returned (publish time, source, citation links). It is clear but does not explicitly contrast with sibling tools like asha_breaking or asha_search, so it's a 4.

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 statements about when to use this tool vs alternatives. The description only states what it does without indicating exclusions or preferred use cases, so a 2.

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?

The description says 'Public' which hints at safe read-only behavior, and lists return fields. However, without annotations, it does not fully disclose side effects, data freshness, error behavior, or whether results are limited. It provides some context but leaves gaps.

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 sentence that front-loads the core purpose and return values. Every word earns its place; there is no fluff 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?

The tool is simple with one optional parameter and no output schema. The description explains the main return components (quote source, timestamp, instrument rows) and the schema covers parameter defaults. This is sufficient for basic invocation, though 'instrument rows' is vague.

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 already provides full coverage for the single 'symbols' parameter with a clear description and default behavior. The tool description adds no extra meaning about parameters, so the baseline score of 3 applies.

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

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

The description clearly states the tool's function: providing public market price context for supported instruments. It also specifies the return contents (quote source, timestamp, instrument rows), which distinguishes it from the sibling news/search 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 is given on when to use this tool versus alternatives. There is no mention of appropriate use cases, exclusions, or how it differs from the sibling tools. The description is purely declarative.

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

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

With no annotations provided, the description carries the full burden. It discloses important behavior: 'Idempotent — the same target always returns the same code' and the social preview metadata feature. These are meaningful behavioral traits not present in the schema, though it omits potential details like authentication or error behavior.

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 sentences, front-loaded with the core purpose, followed by a key behavioral trait and usage advice. Every sentence earns its place with zero waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with only 2 parameters and no output schema, the description adequately covers purpose, usage, and idempotency. It is complete enough for an agent to select and invoke the tool, though it does not describe return values or failure modes, which are not required given the absence of an 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?

Schema description coverage is 100%, so baseline is 3. The description restates the enum values ('article, generated brief, story cluster, or allowlisted route') which adds minor clarity over the schema ('What is being shared'), but does not provide substantial new semantic information beyond that.

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 function: 'Mint the stable asha.news/s/<code> short link' for specific target types. It distinguishes itself by emphasizing the short link's social preview metadata and its use instead of long URLs, differentiating from sibling sharing 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?

The description gives clear usage context ('Use this instead of pasting long URLs') and mentions a key benefit ('carries social preview metadata'). It does not explicitly name alternative sibling tools or state when not to use it, so it lacks exclusions but still provides useful guidance.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It discloses the content structure (timeline, evidence classes, freshness indicator, section map) but omits important behaviors: how the freshness indicator is computed, whether the tool filters by status or limit, what the default response looks like, and whether any side effects or authentication are involved.

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, information-dense sentence. It front-loads the main content (timeline) and adds the section map component. No unnecessary words, but the density might slightly reduce readability. Still, it is appropriately concise for the content covered.

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 no output schema, no annotations, and two parameters with zero explanation, the description is incomplete. It explains what the tool provides (timeline and section map) but not how to control the query via parameters, what the freshness indicator means, or the structure of the returned data. Sibling tools suggest a broader news desk context, but the description fails to connect to that context.

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%. The description does not mention the 'limit' or 'status' parameters at all, nor does it explain how they affect the timeline. The enum values (verified, cross_verified, pending, leak) are self-explanatory from the schema, but the tool description adds no meaning beyond 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?

The description clearly identifies the resource: a timeline of evidence-classed Palestine desk events with a freshness indicator, plus a section map. It distinguishes from siblings by specifying the Palestine desk focus and the inclusion of section wings and canonical URLs, though it lacks an explicit verb like 'get' or 'list'.

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 guidance on when to use this tool versus alternatives such as asha_breaking, asha_daily_brief, or conflict_events. The description implies it is for timeline and section navigation, but does not state use cases, exclusions, or alternative tool references.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the unified nature and the 'before choosing a narrower endpoint' guidance, but does not disclose return format, pagination, or any side effects. For a search tool, this is adequate but not rich.

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 sentences with zero waste. It front-loads the core purpose and adds a single actionable usage hint. 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?

Given the tool's moderate complexity (3 params, no output schema, no annotations), the description is reasonably complete. It explains the unified scope and provides usage guidance. It could mention result ordering or default behavior, but the schema covers defaults (limit default 10).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters. The description adds the 'unified' context and the 'before choosing a narrower endpoint' guidance, but does not add syntax or format details beyond the schema. Baseline 3 is appropriate.

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

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

The description clearly states the tool performs a unified search across three specific content types (articles, story clusters, generated briefs), which distinguishes it from narrower search tools like asha_search_articles and asha_clusters_search. The verb 'search' plus the resource scope is specific and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs to use this tool before choosing a narrower endpoint, providing clear usage context. However, it does not explicitly state when NOT to use it or name specific alternative tools, though the sibling list implies alternatives exist.

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

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

No annotations are provided, so the description shoulders the burden. It adds a useful behavioral instruction (cite source URLs and Asha article URLs when present), which informs the agent's output behavior. However, it does not disclose search behavior details like recency definition, result ordering, or potential limitations.

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 exceptionally concise, consisting of two short sentences. Every sentence adds value: one describes the core function, and the other provides actionable guidance about citing URLs. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple nature of the tool (two params, no output schema, no nested objects), the description is adequately complete. It states what is searched, the scope (recent), and adds a citation instruction. It could mention result format or expected output behavior, but those are less critical for a basic 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 100%, so the schema already fully documents both parameters (q and limit). The description adds no extra parameter-level detail, but the baseline of 3 is appropriate when the schema already provides complete information.

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 performs a keyword search across recent Asha News articles, using a specific verb ('search') and a clear resource ('Asha News articles'). It also adds a distinct scope ('recent') that helps differentiate it from broader sibling tools like asha_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by limiting to 'recent Asha News articles,' but it does not explicitly state when to use this tool over alternatives or mention exclusions. At best, the intended scope is implied rather than directly guiding tool selection.

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

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

With no annotations, the description carries the burden. It discloses the found=false behavior, which is helpful, but does not mention other behavioral aspects such as whether it's read-only, any rate limits, or what the package contains. Additional context on side effects or response structure is missing.

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 concise sentences that directly state the purpose and a key behavioral outcome. No filler or repetition, with information front-loaded and easy to parse.

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 no output schema, so the description should explain what the response contains. It only mentions found=false for absence and 'share-ready package' without detailing its structure (e.g., fields, URL, payload). This leaves significant ambiguity for the agent on what to expect from a successful call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed descriptions for both q and url, so the baseline is 3. The tool description adds no parameter-specific insight beyond what the schema already provides, such as example formats or precedence rules, which are already 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?

The description clearly states the tool provides a share-ready package for a published, cited Asha brief/story, with a specific resource and action. It distinguishes from generic search or feed tools by focusing on share-readiness, though it does not explicitly differentiate from sibling tools like asha_share_payload or asha_mint_share_link.

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 via the parameters (q for search, url for exact match) and notes found=false when unavailable, but it does not explicitly state when to use this tool over alternatives. Context is clear but exclusions or alternative recommendations are absent.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the payload is ready-to-post, within platform limits, and includes the imperative to 'Post verbatim; keep attribution.' This adds behavioral context beyond the schema (e.g., exact text usage, attribution requirement), but does not mention error handling or auth needs, which are likely minimal for a generation tool.

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 that efficiently states purpose, lists platforms, enumerates output components, and gives an implementation directive. No wasted words or redundant phrasing.

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 should clarify the return structure. It lists components (text, hashtags, image, intent URL) but does not specify whether the output is a string, JSON object, or array, nor how the agent should extract and post each part. The instruction 'Post verbatim' clarifies the text usage but not the parsing or assembly of the payload. For a simple tool with 2 params, this is borderline adequate but leaves room for ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for both parameters, so the baseline is 3. The description enriches the platform parameter by listing valid values and implies format constraints via 'within platform limits,' but does not add substantial meaning beyond the schema. The article_id is already well-described as sourced from asha_feed/asha_search_articles.

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 purpose: generate ready-to-post social share payloads for an article, listing explicit platforms and content components (text, hashtags, image, intent URL). This is a clear verb+resource combination that distinguishes it from siblings like asha_share_pack or asha_mint_share_link.

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 needing share payloads for an article) and includes a direct instruction to post verbatim and keep attribution, but it does not explicitly state when not to use this tool or mention alternatives such as asha_share_pack. Guidance on tool selection 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?

No annotations are provided, so the description carries the burden of behavioral disclosure. It communicates that the data is a public directory of sources with metadata, which suggests a read-only, publicly accessible operation, but it does not explicitly state read-only semantics, how many sources are returned, or how the trust metadata is structured.

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 sentence of about 10 words. It states the resource, its source, and important metadata traits without filler or repetition, making it efficient and easy to parse.

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 only one optional parameter and no nested objects, which lowers the complexity ceiling, but a lack of output schema and sparse guidance leaves the response shape and typical use case incompletely specified. The description is enough for a basic sense of purpose but not fully self-sufficient for a first-time agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema contains one optional 'limit' parameter with min/max constraints, but schema_description_coverage is 0%. The description does not mention 'limit' or clarify how the parameter affects the direction result, so it adds no semantic meaning beyond the raw 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?

The description identifies the tool as the 'Asha News public source directory' and explains that it carries 'provenance and trust metadata,' making the resource clear and distinguishable from sibling news and search tools. It lacks an explicit verb such as 'list' or 'get,' so it is slightly under-specified, but the noun 'directory' strongly implies a list/gathering operation.

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 siblings such as asha_search, asha_feed, or asha_daily_brief, and no mention of exclusions or alternatives. The word 'directory' implies a query for sources, but the description does not explain when a user would need source provenance or trust metadata versus other Asha News resources.

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 without annotations, the description discloses key behaviors: it emails a confirmation link, nothing is delivered until click, and the assistant cannot confirm on behalf of the user. This is transparent about the tool's side effects and limitations.

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 concise and well-structured, using two sentences to convey the action, process, and usage constraints. No redundant or verbose language, making it easy for an agent to parse.

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 subscription tool with three parameters and no output schema, the description adequately covers the essential context: the double opt-in mechanism, the prerequisite (user-provided email), and the follow-up action (tell user to check inbox). It is complete for the intended use.

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 already provides descriptions for all three parameters (100% coverage), so the baseline is 3. The tool description does not add extra meaning beyond the schema; it only reiterates the email requirement in a usage context. No additional parameter-specific details are provided.

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 starts a double opt-in newsletter signup for an email address, specifying the verb and resource. It explains the confirmation process, distinguishing it from general subscription tools. This is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage instructions: only submit an address the person gave you in this conversation, and tell them to check their inbox. It also states the limitation (cannot confirm on their behalf), giving clear when-to-use and how-to-proceed guidance.

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

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

No annotations are provided, so the description carries the full burden. It describes data contents and filter parameters but does not disclose that it is a read-only operation, any authentication requirements, or rate limits. There is no mention of side effects or response behavior beyond raw data retrieval.

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 sentences, front-loaded with the core purpose, and includes all essential usage hints without redundancy. Every clause adds value, making it highly concise and well-structured.

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 tool's modest complexity (3 optional parameters, no output schema), the description covers event types, summary attributes, and filtering/delta usage. It does not mention ordering, pagination behavior (beyond limit), or error states, but these are not critical for basic usage. Slight gap in not referencing related sibling tools, but overall 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?

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful context by explaining the bbox format ('w,s,e,n') and the purpose of 'since' for delta polls, which goes beyond the schema's generic 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 description clearly identifies the resource (geolocated conflict events) and specifies event types, data attributes (severity, verification, summaries), and filtering options. It effectively differentiates from sibling tools like conflict_state by focusing on event-level data with geolocation.

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?

Provides clear context for usage: filtering by bbox and delta polling via since. Implies it is for retrieving event data, but does not explicitly mention when to prefer this over alternatives or when not to use it. No exclusions or alternative tool names are given.

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

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses the 'degraded flag', 'per-tier freshness' semantics, and the envelope/delta mechanism — valuable operational context. It doesn't address auth, rate limits, or failure behavior, but for a snapshot tool the transparency is above average.

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 dense sentences, every phrase adds value — content inventory, freshness semantics, cursor usage, and an actionable alternative URL. Perfectly front-loaded and zero wasted 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?

For a single-optional-parameter snapshot tool with no output schema, the description covers the key facets: data contents, freshness/degradation, delta retrieval, and streaming alternative. It slightly over-delivers given the tool's simplicity, though it could have hinted at the relationship to conflict_events or polling cadence.

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% — 'since' is already well-defined as an 'Envelope sequence cursor; returns only envelopes with seq greater than this.' The description's 'Pass since={seq} for envelope deltas' mostly restates this with the 'envelope deltas' framing. Baseline 3 applies since the schema does the heavy lifting.

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 a specific verb+resource ('Live Middle East Conflict Monitor snapshot') and enumerates its scoped content (official alerts, geolocated OSINT events, story clusters, theater brief, freshness flag). It's specific and informative, but doesn't explicitly differentiate from sibling tools like conflict_events, 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?

Provides clear context: 'Pass since={seq} for envelope deltas' explains incremental usage, and 'Streaming clients can use SSE... instead' explicitly points to an alternative integration path. It stops short of naming when to use sibling tools like conflict_events versus this one, so not a full 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?

No annotations are provided, so the description carries the behavioral burden. It discloses rate-limiting and the nature of the output (claim family, verdict, evidence-backed answer, citation URLs). It implies a read-only operation with 'check', but does not explicitly state non-mutating behavior or any side effects. This is adequate but not exhaustive.

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 concise, consisting of two sentences that front-load the purpose and return format, followed by a rate-limit note and instruction to relay citations. There is no unnecessary detail or repetition, and it fits the information density needed for this tool.

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 a single parameter, no annotations, and no output schema, the description covers the essential aspects: what it checks, what it returns (claim family, verdict, evidence answer, citations), and usage constraints (rate limit, single claim). It provides a complete mental model for a simple tool without overcomplicating.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description for the single parameter 'claim' is already complete ('The claim to check, as one plain-language sentence.'). The tool description adds minimal value beyond that, only reinforcing the need for a 'single clear claim' in the usage guideline. With 100% schema coverage, the baseline of 3 is appropriate.

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

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

The description clearly states the tool's function: 'Check one claim about Palestine against the desk's claim library and evidence archive.' It specifies the resource (claim library and evidence archive) and the action (check) and distinguishes itself from sibling search tools by emphasizing claim verification with a structured verdict and citations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides usage constraints ('Rate-limited — send a single clear claim per call') and instructs to relay citations, which implies when to use it (for one claim at a time). However, it does not explicitly mention alternatives or scenarios where this tool should not be used, leaving the comparative guidance 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?

With no annotations provided, the description carries the full behavioral disclosure burden. It does this well by explicitly stating that the tool returns aggregate counts only, never names unreviewed records, and includes caveats about interpreting statuses and the ingest_enabled flag. It stops short of describing the full response shape or exact fields, but for a zero-parameter health tool, it discloses the key behavioral expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact but information-dense, with no filler or repeated content. It front-loads the core purpose, then adds essential caveats in logical order: what it reports, what it never does, when to use it, and how to interpret flags. Every sentence earns its place and contributes to safe, correct use.

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 there is no output schema, the description does a good job of explaining the conceptual contents of the response: source states, review queue depth, published counts, and pointer reachability. It also names the degraded_reasons field and the ingest_enabled flag, giving the agent concrete anchors for interpretation. It could be more complete by enumerating exact response fields, but it provides enough context for correct invocation and basic interpretation.

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 the schema is fully described with an empty properties object, so there is no parameter semantics burden on the description. The description instead focuses on the meaning of the output, which is the more relevant semantic content for this tool. Baseline 4 is appropriate for a 0-parameter tool.

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 health/status monitor for the Palestine evidence pipeline, listing exactly what it reports: source collection status, last success times, review queue depth, published counts, and external pointer reachability. It also distinguishes itself from sibling tools by stating it provides aggregate counts only and never names unreviewed records, making its role distinct from evidence_search or evidence_record.

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 a direct use case: 'Use it to answer "is this archive current?" honestly before citing it.' It also provides interpretive guidance, telling the agent to read degraded_reasons rather than relying on status alone and explaining that ingest_enabled:false means configured off, not broken. This prevents common misuses and clarifies when the tool is appropriate.

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

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

With no annotations present, the description carries the full burden and delivers richly: it discloses that media candidates are third-party and never hosted by Asha, that graphic or ungraded content requires explicit consent before loading, and that a 404 means 'not published' rather than 'does not exist.' These are meaningful behavioral traits beyond schema, especially the consent-gating and 404 semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences with zero waste: the first front-loads purpose and payload, the second covers media-gating behavior, the third covers error semantics. Every sentence earns its place and the most critical operational facts (consent, 404 meaning) come quickly.

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 one parameter, no output schema, and no annotations, so the description must explain return content, behavior, and error handling — it does all three. It states what the response contains, how media behaves, and how to interpret a missing ref. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% — the schema already documents ref as a 'Stable public ref, e.g. gl-2810.' The description reinforces the example and adds the nuance that an unresolved ref may simply mean the record hasn't cleared editorial review. This is marginal added meaning, so the baseline 3 applies.

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

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

The description identifies a specific resource (a single Palestine evidence record), the lookup key (stable ref, e.g. gl-2810), and the record's contents (categories, incident links, related records, media candidates). It distinguishes itself from siblings like palestine_evidence_search and palestine_evidence_health by being the point-lookup variant. It lacks an explicit verb like 'retrieve' or 'fetch', which keeps it just 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?

Usage context is implied: since lookup is 'by its stable ref,' an agent can infer this tool is for when a ref is already known, whereas palestine_evidence_search is for discovery. However, no explicit when-to-use/when-not-to-use guidance or named alternatives are given, leaving the choice between this tool and its search/health/taxonomy siblings to inference.

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

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

With no annotations provided, the description carries the full burden, and it excels: it explains facet counts, the upstream.classification vs asha.finding distinction, attribution requirements, bot_can_cite semantics, and that Asha only holds metadata/links while media opens upstream. This gives the agent critical post-invocation guidance.

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 information-dense sentences, each earning its place: purpose, facet output, attribution semantics, and citation/trust behavior. No filler, no repetition of schema details, and the most critical usage constraint is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is remarkably complete for a tool with no output schema and no annotations: it covers search purpose, result facets, record-level semantics, citation rules, and media behavior. It stops short of minor operational details like pagination defaults or what happens with no filters, but it is sufficient for correct invocation 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?

Schema coverage is 63%, so the schema already documents most parameters. The description adds useful thematic context for filtering (dates, places, categories, sources) but does not systematically explain parameters like page, page_size, or the exact usage of from/to. It neither fully compensates for the 37% gap nor is it redundant with 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?

The description opens with a specific verb and resource: 'Search the Palestine evidence graph', then details the exact record contents (dates, places, categories, source). It distinguishes itself from broader sibling search tools by emphasizing 'reviewer-approved records' and the evidence-graph scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when this tool is appropriate: searching the evidence graph and using facet counts to understand corpus shape before narrowing. However, it does not explicitly name alternatives or state when not to use this tool versus siblings like asha_search or conflict_events.

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

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

With no annotations provided, the description carries the behavioral burden. It discloses the important provenance behavior that legal_category terms are editorial-only, never derived from text, and record a named authority's characterization. It does not describe the response format, but for a simple taxonomy lookup this is sufficient.

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 sentences with no filler. The core taxonomy is front-loaded, the usage directive follows immediately, and the special editorial caveat is placed last. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter enum tool with no output schema, the description is largely complete: it explains what the tool is, when to call it, and the key semantic distinction of legal_category. The only minor gap is that it does not state what happens if the optional vocabulary parameter is omitted or what the exact response shape looks like.

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?

Despite the schema having no descriptions and the parameter being a bare enum, the description gives each enum value a semantic gloss: incident_type (what happened), theme (what was hit), affected_group (who), and legal_category (what a named body says it amounts to). This fully compensates for the 0% schema coverage.

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 the controlled vocabulary behind the Palestine evidence graph and enumerates its four categories with concise glosses. It is clearly distinguishable from sibling evidence search/record tools, though it relies on an implicit 'returns/lists' action rather than an explicit verb like 'retrieve'.

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?

'Call this before filtering so you use real slugs' explicitly tells the agent when to use the tool. It gives clear usage context but does not state exclusions or named alternatives, so it stops short of full when-to-use/when-not-to-use guidance.

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

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

With no annotations, the description must convey behavior. It does state that it relays characterizations exactly, keeps citation URLs, and clarifies terminology (provisional measures vs. merits, warrants vs. charges), which indicates output fidelity. However, it does not mention side effects, safety (read-only), or response formatting beyond content.

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 moderately detailed but well-structured, starting with the core purpose and then adding clarifications and output components. It avoids fluff while providing necessary nuance, making it appropriately concise for the tool's complexity.

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 absent output schema, the description sufficiently outlines the expected output (full record, casualty figures, timeline, FAQ) and instructs on exact relay and URL retention. It lacks explicit limitations or error handling, but covers the core context comprehensively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero parameters, so there is nothing to explain. The description does not add parameter-level detail because none exist, resulting in a neutral score based on the baseline for high schema coverage.

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

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

The description clearly states the tool's purpose: it provides the full genocide-case record from the Asha News Palestine desk. It distinguishes itself by specifying that it covers the complete case, including court/UN body findings, attributed casualty figures, timeline, and FAQ, which differentiates it from search or sharing 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?

The description implies usage by indicating it provides the full case record, but it does not explicitly state when to use it versus alternatives like search tools. No when-not-to-use or alternative tool references are given, so 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?

The description indicates that results carry stable IDs and canonical URLs, implying a read-only search behavior. However, it does not disclose potential side effects, limitations, error scenarios, or any rate limits. Given no annotations, the description alone provides modest transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-constructed sentence that efficiently conveys the tool's purpose, content scope, and a key instruction about citation. No unnecessary words or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides essential context: what the archive includes, the nature of results, and guidance on citation. It omits details like error handling or authentication, but for a straightforward search tool, the given context is largely sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully describes each parameter (q, page, type, page_size) with types and defaults. The description does not add extra semantic detail beyond what is in the schema, so it contributes little to parameter understanding.

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 function as searching the Palestine evidence archive, and enumerates its content types (media records, victims memorial, claim library). It also highlights the nature of results (stable IDs, canonical URLs), making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a specific usage directive ('cite those instead of scraping') but does not elaborate on when to prefer this tool over its siblings or under what conditions to use it. It offers limited guidance on tool selection or scenario appropriateness.

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