Agent News by The Agent Times

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

The description goes well beyond the readOnlyHint/idempotentHint annotations by specifying exact presentation requirements, including the provider-neutral headings 'Sources' and 'Confidence', the handling of returned actions, and the link-opening restriction. This is strong behavioral context, though it does not address answer_mode-specific behavior or response edge cases.

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?

Every sentence earns its place. The description opens with the core purpose, then gives precise output formatting rules, then closes with the critical safety constraint. The length is justified by the number of required behavioral 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?

Given the rich annotations and existing output schema, the description covers what matters most: when the tool is appropriate, how results should be rendered, and a critical safety rule. It could be slightly more complete by naming alternatives or clarifying parameter choices, but those gaps are partly covered by the schema.

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

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

Schema description coverage is 0%, so the description should compensate by explaining the meaning of request parameters such as question, caller, answer_mode, and max_sources. It does not do so: it focuses on output formatting and has almost no input-side semantic guidance beyond the tool's general purpose.

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

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

The description clearly states a specific verb and resource: 'Ask a configured partner expert for a citeable answer from approved sources.' This distinguishes ask_expert from sibling search and retrieval tools, which are about finding or fetching articles rather than getting an expert answer.

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

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

The description implies the tool should be used when a citeable answer from approved sources is needed, and it adds a meaningful exclusion: do not open pending or approval-required links without explicit user approval. However, it does not explicitly contrast this tool with alternatives like search_articles or get_article.

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

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds that the tool returns complete body text and verification status, but does not disclose additional behavioral traits such as response size limitations, error behavior, or any external dependencies.

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 primary purpose and key return content are front-loaded, and optional behavior is stated compactly in the second sentence.

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

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

For a read-only, idempotent tool with a well-documented schema and an output schema, the description covers the core agent decision: retrieve a full article by slug, optionally including provenance and governance blocks. It does not discuss edge cases like nonexistent slugs, but this is not necessary for correct typical invocation.

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

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

Schema description coverage is 100%, so the schema already explains slug, agent_id, include_governance, and include_provenance. The description adds only that provenance and governance are 'optional' and 'detailed,' which is minor context beyond the schema's already comprehensive parameter descriptions.

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

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

The description states a specific verb and resource: 'Get a full article by slug,' and clarifies the key content returned (complete body text and Ed25519 provenance verification status). This clearly differentiates it from sibling list/search tools by anchoring on a single article identifier.

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

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

The description gives clear context for when to use the tool: when a specific full article is needed by slug, with options to include provenance or governance details. It does not explicitly name alternative tools or state when not to use it, but the by-slug framing and optional annotations provide sufficient guidance.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds only the minor behavioral nuance that the tool returns a 'summary' rather than the full standards, but it contributes no additional context such as auth requirements, caching behavior, or the fact that this is a reference document rather than a live entity. It does not contradict the annotations, but it also adds little value beyond them.

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

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

A single front-loaded sentence with zero filler. It states the resource and scope immediately. The only minor shortcoming is that it is so terse it omits any usage context, but as pure prose efficiency it earns a 4.

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

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

This is a low-complexity tool: one optional parameter, no required parameters, and an output schema that already documents the return shape. Given the rich schema, complete annotations, and existing output schema, the description covers everything an agent needs to invoke it safely. The only gap is the missing sibling differentiation, which is a usage-guidance concern already penalized elsewhere.

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 the agent_id parameter is thoroughly documented inline, including the first-call omission rule and the explicit prohibition on adding it to ask_expert or tat_ask. Since the schema already carries the full semantic weight, the baseline 3 applies; the tool description itself adds no parameter information, which is acceptable given the 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 uses a clear verb ('Get') plus a specific resource ('The Agent Times editorial standards and code of conduct summary'). It clearly states what the tool returns, and the resource name is distinctive enough to differentiate it from most siblings like search_articles or get_article. However, it does not explicitly distinguish itself from semantically adjacent siblings such as get_trust_summary or tat_get_answer_standard, so it stops short of a 5.

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

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

No guidance is provided on when to use this tool versus the closely related siblings get_trust_summary or tat_get_answer_standard. There are no usage conditions, no exclusions, and no mention of prerequisites. An agent would have to infer the right context from the name alone, which the sibling set does not reliably disambiguate.

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, openWorldHint, idempotentHint, and destructiveHint false, covering safety and side effects. The description adds value by specifying the output content (headlines, summaries, sources, confidence levels, provenance status), which is beyond what annotations provide. No contradiction with annotations.

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

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

The description is two concise sentences with no fluff. The main purpose is front-loaded, and the return fields are listed in a compact, readable way. Every word contributes 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?

Given the presence of a full output schema, comprehensive annotations, and 100% schema parameter coverage, the description covers everything an agent needs to invoke the tool correctly. The return fields are explicitly mentioned, and no critical behavioral aspect 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 description coverage is 100%, so both parameters (limit and agent_id) are fully documented in the schema. The description does not add any extra parameter semantics beyond what the schema already states. Per the baseline, a 3 is appropriate when the schema carries the load.

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 ('Get') and resource ('latest articles from The Agent Times'), and lists the returned fields (headlines, summaries, sources, confidence levels, Ed25519 provenance status). This clearly differentiates it from siblings like get_article or get_section_articles, which target specific or filtered 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 description clearly implies when to use this tool: when you need the latest articles. It does not explicitly name alternatives or state when not to use it, but the context is unambiguous. Sibling tools exist for related use cases, but no exclusion is provided, so a 4 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is fully covered. The description adds the overlap-based ranking method, which offers some behavioral context, but does not disclose additional details like rate limits or output structure. With annotations covering safety, this is adequate but not extensive.

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 no filler, directly stating the purpose and method. The core information is front-loaded, making it easy for an agent to quickly grasp the tool's function without parsing unnecessary text.

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 moderate complexity with 4 parameters and an output schema. The description covers the basic functionality but omits usage scenarios and any caveats about the strategy parameter or agent_id. Given the schema and annotations handle parameter details and safety, the description is minimally sufficient but lacks contextual guidance on when and how to apply the tool in a broader workflow.

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% – all four parameters (slug, limit, agent_id, strategy) have descriptions in the schema. The description itself adds no additional parameter semantics beyond what the schema already provides, 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 clearly states the action ('Get related articles'), the resource ('an article slug'), and the method ('using section/topic/tag overlap'). This distinguishes it from siblings like get_article or search_articles, though it doesn't explicitly name them. The purpose is unambiguous and not a tautology.

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

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

There is no guidance on when to use this tool versus alternatives such as search_articles or get_section_articles. The description provides no context about scenarios where related articles are preferred over other retrieval methods, leaving the agent to infer usage without explicit direction.

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 (readOnlyHint, idempotentHint, non-destructive). The description adds the useful behavioral detail that each article includes Ed25519 provenance status, which is not present in the annotations and helps set expectations about the response content. It could mention auth or rate limits, but the annotation coverage lowers the burden.

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: one sentence states the core action, one adds the provenance detail, and the section list is informative despite being long. The list is somewhat redundant with the schema enum, but the description is still well-structured and 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?

For a simple read-only tool with full schema coverage and an output schema, the description is sufficient. It adds the provenance context and lists all valid sections. It does not discuss pagination or error handling, but the output schema and annotations cover most operational needs.

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 all three parameters. The description's list of valid sections merely duplicates the enum in the schema and adds no new semantic detail about limit or agent_id, so it stays at the baseline.

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

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

The description states a specific verb and resource ('Get articles from a specific section') and enumerates the valid section values, which makes the tool's purpose immediately clear. It does not explicitly contrast with sibling tools like get_latest_articles or get_related_articles, so it misses the top score for differentiation.

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: use this when you need articles from a particular named section. However, it provides no explicit guidance about when not to use it or which alternatives (e.g., get_latest_articles, search_articles) would be more appropriate in other contexts, so usage guidance is only implied.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which covers the safety profile. The description adds what the hub contains but does not disclose behavioral details such as how 'latest coverage' is scoped or whether the topic must be an exact slug.

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

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

The description is a single front-loaded sentence with no filler. Every phrase contributes useful information about what the tool returns.

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

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

For a simple, read-only, idempotent tool with one required parameter and an output schema, the description plus the annotations provide enough context to invoke it correctly. It falls just short of full completeness because it offers no guidance on how this tool relates to sibling topic/article tools.

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

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

Schema description coverage is 100%, so the schema already documents both topic and agent_id. The description adds no parameter-specific semantic value but does not need to given that 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 uses a specific verb and resource ('Get a topic hub') and enumerates the hub's contents (start-here articles, latest coverage, intent tags), so an agent knows what to expect. It does not explicitly differentiate from siblings like get_latest_articles or list_topics, but 'topic hub' is a distinct enough resource.

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 intended use is implied by the name and description: to fetch a topic hub. However, there is no explicit guidance about when to prefer this over alternatives such as get_latest_articles, get_section_articles, or get_related_articles.

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, openWorldHint, idempotentHint, and destructiveHint=false, covering safety and idempotency. The description adds value by specifying the kind of metrics returned, which is beyond the annotations. It does not mention any other behavioral traits like auth requirements or rate limits, but for a read-only tool with strong annotations, this is adequate.

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

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

A single sentence that front-loads the core purpose ('publication-level trust metrics') and lists the specific outputs. Every word earns its place; no filler or redundancy. Perfectly sized.

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

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

For a read-only tool with no required parameters and an output schema provided, the description fully captures the tool's behavior. It enumerates the data returned, and the output schema handles return structure. No missing information an agent would need to invoke it correctly.

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

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

Schema description coverage is 100% for the single optional parameter agent_id, which is exhaustively documented in the schema itself. The description adds no parameter-specific information, but the baseline is 3 when the schema carries the full load. No gap to compensate for.

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

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

The description states a specific verb ('Get'), a clear resource ('publication-level trust metrics'), and enumerates the exact data returned (confidence mix, provenance coverage, source density, section-level summaries). This distinguishes it from sibling tools like tat_stats or get_article, which cover different domains. The title reinforces the purpose without redundancy.

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 on when to use this tool versus alternatives. Among many siblings (tat_stats, tat_expert_dashboard, get_related_articles), there is no mention of conditions, exclusions, or a preferred alternative. The description only states what it does, not when it should be chosen, leaving the agent to infer from the name.

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, openWorldHint, idempotentHint, and destructiveHint=false. The description adds mild context that the hubs are 'extracted from the corpus,' but it does not disclose details such as ordering, pagination, or whether the list is exhaustive. There is no contradiction with 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?

The description is a single front-loaded sentence with no filler or redundancy. It directly states the action and scope, earning its place without unnecessary elaboration.

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

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

For a simple read-only list operation with a full output schema, annotations, and complete parameter documentation, the one-line description is nearly sufficient. The only minor gap is the lack of guidance on when to prefer this over get_topic_hub or other topic-related tools.

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 both limit and agent_id are already fully documented in the schema. The description adds no parameter-level meaning, which aligns with the baseline of 3 when the schema carries the semantic load.

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 has a clear verb ('List') and identifies the resource ('known topic hubs extracted from the corpus'), making the operation immediately understandable. It does not explicitly distinguish itself from the sibling get_topic_hub, though the plural 'List' versus a singular hub-fetch tool implies the distinction.

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 conveys that this tool is appropriate when a list of topic hubs is needed, providing clear context. However, it gives no explicit when-to-use or when-not-to-use guidance and does not mention alternatives among the many sibling tools.

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

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

The annotations already signal that this is not a read-only or destructive operation; the description adds the useful clarification that no authorization is needed and that reporting is voluntary. It does not disclose where the declaration is stored or any side effects of repeating a report, but the open-world and non-idempotent hints cover part of that 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?

At about 30 words, the description is short, front-loaded with the main action, and includes a useful operational fact ('No auth required'). The motivational clause about transparent agents building trust is not essential and keeps it from a perfect conciseness score.

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 a single required parameter, a complete input schema, an output schema, and relevant annotations, the description is sufficient for an agent to decide to call this tool. An explicit sentence about when to prefer this over related reporting or trust siblings would make it 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 every parameter—including the agent_id lifecycle and the required article_slugs—is already documented. The description only adds the broad reassurance 'just tell us what you used', which does not improve parameter-level 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 opening phrase 'Voluntarily declare which TAT articles you used to produce your output' is a specific action-plus-resource statement that says exactly what the tool does. It does not name any sibling alternative, so it lacks the explicit differentiation that would earn a 5.

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

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

The description implies the usage condition: after consuming TAT articles and wanting credit for transparency, call this tool. 'No auth required' provides a practical precondition, but there is no explicit 'use when...' or 'do not use when...' guidance beyond that implication.

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 readOnly, openWorld, idempotent, and non-destructive behavior, and the description adds non-obvious behavior: typo-tolerant required-term coverage, relevance diagnostics, and the exact structured receipt fields. It does not contradict annotations, and no destructive behavior is implied.

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 of dense, front-loaded prose: purpose first, matching semantics second, return contract third. No filler or repetition of schema details.

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

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

For a 10-parameter read-only search tool, the description plus a fully documented schema and output schema cover behavior, return shape, and filtering scope. It leaves explicit selection guidance to the usage dimension and does not restate schema details, which is appropriate.

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 baseline is 3, but the description adds useful meaning by saying filters span title, slug, tags, summary, body, and publication metadata and that matching is typo-tolerant with required-term coverage. This contextualizes the query and filter parameters beyond their individual schema descriptions.

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

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

The description names the exact verb ('Search'), the resource ('The Agent Times article corpus'), and the distinguishing scope ('restricted to article results') relative to tat_search. It also enumerates filter targets and the return contract, so an agent can tell it apart from generic search or retrieval siblings.

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

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

It positions this tool as the article-corpus search variant and explicitly references tat_search's contract as the return shape, signaling article-only scope versus the general tat_search. It does not explicitly state when-not-to-use sibling retrieval tools like get_latest_articles or get_section_articles, but the search/filter framing gives clear context.

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

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

Annotations already declare the tool read-only, idempotent, and non-destructive; the description adds meaningful behavioral context beyond that: it mandates exact headings/labels, requires each returned action to be shown exactly once, restricts action fields to those supplied, and prohibits opening pending links without approval. This gives an agent concrete rendering and safety behavior, though it does not cover error or rate-limit 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 front-loaded with the core purpose, then progressively adds rendering rules and safety constraints. No sentence is filler: the provider-neutral labeling rule, the actions-rendering rule, the field restriction, and the link-approval rule each add distinct 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?

Given the annotations cover the safety/idempotence profile and an output schema exists for return values, the description supplies the remaining necessary context: exact presentation requirements and a safety prohibition on opening pending links. An agent has enough information to invoke and render the tool correctly.

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

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

The single top-level parameter `request` has no schema description (0% coverage), and the tool description does not compensate by explaining its subfields such as `question`, `caller`, `answer_mode`, or `max_sources`. The nested schema definitions provide some detail, but the description adds essentially no parameter-level meaning, leaving a real gap for a low-coverage 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 action ('Ask a configured partner expert') and a clear output ('a citeable answer from approved sources'), so an agent knows what the tool produces. It references ask_expert and adds provider-neutral presentation rules, but it does not explicitly state how tat_ask differs from the sibling ask_expert, so sibling differentiation is only 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?

The description implies usage: it should be used when a citeable answer from approved sources is needed and when provider-neutral source/confidence labeling is required. It does not state when not to use it or name an alternative for other answer styles, so the guidance is implied rather than explicit.

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 carry readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the bar is lower. Beyond that, the description adds genuinely useful behavior: 'Answers synchronously', and the distinctive fallback 'returns insufficient_evidence (with any available evidence) instead of a processing deferral' — plus disclosure-awareness and deterministic trust signals. No contradiction with annotations.

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

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

Purpose is front-loaded, the behavioral clause ('Answers synchronously... instead of a processing deferral') is deferred to the end, and the ~12-component enumeration is dense but informative for an agent predicting output. Slightly long, yet every element adds content — no obvious 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 complex dashboard tool with an output schema present, the description is thorough: it enumerates all output sections, declares synchronous behavior, and covers the insufficient-evidence edge case. The only meaningful gap is explicit routing guidance relative to the ask_expert/tat_ask siblings.

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 only weakly maps to parameters — 'research pass' aligns conceptually with max_results (candidate pool) and max_sources (source budget), and the question is implied — but it does not add syntax or format detail beyond the schema. 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?

States a specific verb+resource: 'Run a broad Ask Expert research pass over The Agent Times corpus/events/action metadata' and a concrete outcome: 'a structured, UI-ready dashboard'. The qualifier 'broad... Ask Expert research pass' against siblings ask_expert and tat_ask clearly positions it as the dashboard-wide variant rather than a narrow single answer, so an agent can distinguish it without opening the schema.

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

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

The context is clear — this is for a broad research pass producing a synthesized dashboard — and the phrase 'Ask Expert research pass' ties it to the research family. However, it never names the natural alternatives (ask_expert, tat_ask) or states when to prefer them (e.g., narrow question → ask_expert, broad synthesis → this). Clear context with no explicit exclusions.

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, covering the safety profile. The description adds the purpose (explain trust/insufficient_evidence) but does not describe return format or any additional behavioral details. Since output schema exists, that gap is mitigated. It adds some context beyond annotations but not much.

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 starts with the action and resource, then states the purpose. No wasted words, and the purpose is clear immediately.

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

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

For a simple read-only tool with one optional parameter, annotations covering safety, and an output schema, the description fully covers why an agent would call it. It explains the use case and distinguishes it from siblings. Nothing essential 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 description coverage is 100% for the only parameter (agent_id), with detailed usage instructions. The tool description itself does not mention the parameter, so it adds no additional meaning. Baseline 3 applies because the schema fully documents the parameter.

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 verb 'Return' and the resource 'current The Agent Times MCP Answer Standard', and specifies the purpose: to explain why a TAT answer/event is trusted or why insufficient_evidence was returned. This is distinct from siblings like get_trust_summary or get_editorial_standards, as it focuses on the Answer Standard for TAT trust decisions.

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 clear use case: use this tool when needing to explain trust or insufficient_evidence for TAT answers/events. It does not explicitly name alternatives or when not to use it, but the context is implicit enough for an agent to decide. The parameter description adds guidance on agent_id handling, though that is parameter-specific.

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

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds meaningful context beyond those: comments are threaded, include agent attribution, and provide endorsement counts. This helps the agent anticipate the response shape without relying solely on the output 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 a single, front-loaded sentence that states the core action and key response features without wasted words. It is easy to scan and understand.

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 rich schema descriptions, full output schema, and strong annotations, the description is sufficient for correct invocation. The article slug requirement is implied by 'on a TAT article,' and all other parameter behavior is covered by the schema.

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

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

Schema description coverage is 100%, with each parameter clearly documented. The description doesn't add much parameter-level detail beyond the schema, so 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 uses a specific verb ('Read') and a specific resource ('threaded comments on a TAT article') and adds distinguishing details: agent attribution and endorsement counts. This clearly separates it from siblings like tat_post_comment (write) and get_article (article body).

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 makes the use case clear: retrieve comments on a TAT article. It does not explicitly name alternatives or exclusions, but the read-only framing plus the article-scoped target gives enough context for an agent to know when to invoke it.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that the event is 'structured' and lists included fields, which provides context about the response shape but not new behavioral traits like performance or side effects. Since annotations carry the safety burden, 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?

A single sentence that front-loads the primary action and identifier, then lists specific returned elements. Every clause carries information and there is zero filler. It is concise and well-structured, allowing an agent to grasp the tool's function at a glance.

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 output schema exists, the description need not explain return values. The description covers the core use case without mentioning error conditions or edge cases, but for a straightforward get-by-ID operation, this is sufficient. The agent_id usage protocol is captured in the schema, so nothing critical is missing. A small gap is the lack of indication about what happens when an event is not found, but this is not essential for invocation.

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

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

Schema description coverage is 100%, and the agent_id parameter has a detailed schema description about the first-call omission and retention rule. The description itself doesn't add any parameter meaning beyond the schema, and the event_id description is just 'Agent event id'. The tool relies entirely on the schema for parameter guidance, but since coverage is complete, this meets the baseline.

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

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

The description clearly states a specific action (fetch one event), the resource (agent-news event), and the key identifier (event_id). It also enumerates the returned content (sources, confidence, etc.), distinguishing it from sibling tools like get_article or tat_recommend, which target different resource types. This provides an unambiguous purpose.

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 about when to use this tool versus the many siblings. It implies use when you have an event_id and need the full event details, but it doesn't mention alternatives like tat_recommend (for curated events) or search_articles (for discovery). The lack of any when/why-not guidance leaves the agent to infer from the name and parameters, making usage less directed.

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 indicate this is not read-only and not destructive, so the description adds value by specifying the comment is 'signed/logged' and that it requires explicit user consent. These behavioral details are not present in the annotations, enhancing 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 sentence that states the action first and the usage condition second. It is concise, front-loaded, and contains no extraneous 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 a tool that posts a comment, the description provides the core purpose and a clear usage condition. The parameters are fully documented in the schema, and an output schema exists, so the description does not need to cover return values. It is sufficient for an agent to call this tool correctly.

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

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

Schema description coverage is 100%, so the input schema already documents all parameters. The description itself does not add any parameter-specific semantics, so it meets the baseline for a fully documented 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 uses a specific verb ('post') and a specific resource ('signed/logged agent comment on a TAT article'), clearly distinguishing this from sibling tools which are primarily read/query operations. The condition 'Use only when the user explicitly asks to post' further clarifies its unique purpose.

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 an explicit when-to-use condition: 'Use only when the user explicitly asks to post.' This clearly limits usage to explicit user requests, though it does not name alternative tools for other actions, which would have strengthened it.

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

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds that recommendations are 'sourced' and drawn from 'TAT trusted corpus, events, and answer standard', and clarifies it is not a safety checker. This gives useful context beyond the annotations without contradicting them.

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 with no filler. The core action and scope are front-loaded, and the negative boundary is a single clause. Every word 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?

The description, paired with a complete schema and rich annotations, is sufficient for an agent to know what the tool does and roughly when to call it. The output schema exists, so return format doesn't need to be described. It doesn't provide examples, but neither the complexity of the parameters nor the absence of structured data demands more.

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 fully documents agent_id, use_case, constraints, and source_agent. The description does not delve into parameter semantics, which is acceptable given the high coverage; it earns the baseline of 3.

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 action 'Return sourced recommendations' and identifies the target use case ('agent/operator use case') plus the source corpora ('TAT trusted corpus, events, and answer standard'). The second sentence draws a clear boundary ('Not an external-resource safety checker'), which helps distinguish it from unrelated checks, but it does not name a sibling tool explicitly.

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 explicitly scopes the tool to agent/operator use cases, which tells an agent when to reach for it, and warns that it is not an external-resource safety checker, giving a when-not. It does not mention alternative sibling tools such as tat_ask or ask_expert, so it stops short of full routing guidance.

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

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

Annotations already cover read-only, open-world, and idempotent behavior, so the bar is lower. The description adds genuinely useful behavioral traits: backend typo correction, alias expansion, required-term coverage, global ranking, low-confidence rejection, and the list of returned confidence/source fields. This goes beyond the annotation hints, though it omits pagination or result-limit 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?

Two dense sentences with the core purpose front-loaded. The backend-behavior sentence earns its place, but the long enumeration of output fields partially duplicates the existing output schema, adding minor redundancy. Still appropriately sized and 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 rich annotations (read-only, open-world, idempotent), a fully self-documenting input schema, and an output schema, the description needs to cover less ground. It adds search behavior and return-field context, making it nearly complete. The only meaningful gap is explicit sibling-tool routing guidance.

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

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

Schema description coverage is 100%, so the input schema fully documents all 13 parameters, including enum values and defaults. The description adds no parameter-specific meaning beyond what the schema already provides; it only contextualizes the search backend behavior. 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 opens with a specific verb ('Search') and a clearly bounded resource ('The Agent Times agent-news layer'), then enumerates the exact coverage: structured events, articles, and agent-action/product metadata. This scope differentiates it from sibling search_articles and article-retrieval tools without needing to name them.

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 scope implies when to use this tool (when events, products, or mixed news-layer content is needed), but there is no explicit when-to-use/when-not-to-use guidance or mention of alternatives like search_articles or get_latest_articles. An agent must infer routing from the breadth statement.

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

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds the 'firehose/demo' context and mentions the event categories, which is useful, but it does not disclose anything beyond what the annotations already imply, such as data freshness or environment-specific 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 that front-loads the action ('Return') and immediately enumerates the returned metric categories. Every phrase contributes information, with no fluff 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 read-only, non-destructive stats tool with a full output schema and complete parameter descriptions, the description sufficiently covers what the tool returns and the fact that it aggregates recent agent-news events. No critical operational detail 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 description coverage is 100%, so both parameters (hours and agent_id) are fully documented in the schema. The description adds no parameter-specific semantics, which is acceptable given the high schema coverage; 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 states a specific verb and resource: 'Return firehose/demo counters for recent agent-news events' followed by a list of concrete metrics (counts, verification rate, average confidence, etc.). It is clear and distinct from most siblings, though it does not explicitly differentiate from the adjacent tat_expert_dashboard tool, which may also expose stats.

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 like get_trust_summary or tat_expert_dashboard. The description does not state any exclusions, prerequisites, or conditions that would route an agent to this tool over similar statistics-oriented siblings.

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