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Glama

Agent News by The Agent Times

Get Section Articles

get_section_articles
Read-onlyIdempotent

Get articles from a specific section. Each article includes Ed25519 provenance status. Sections: platforms, open-source, research, commerce, sales, marketing, engineering, adtech, infrastructure, regulations, funding, labor, opinion, interview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of articles (max 20, default 10)
sectionYesSection name
agent_idNoOptional persistent agent identifier. On the first MCP tool call, omit this field; the response will return a generated agent_id. Save that value and send it in agent_id on every subsequent MCP tool call. Any stable string is accepted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoPresent when the tool returns a text-only response.
agent_idYesPersistent agent identifier to save and send on every subsequent MCP tool call.
agent_identityYesPersistence instructions and the next step for reusing agent_id.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context by stating each article includes Ed25519 provenance status, which is a notable output characteristic not evident from annotations or schema. No contradictions.

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

Conciseness5/5

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

The description is two sentences, with the core purpose front-loaded and the section list providing necessary enumeration without fluff. Every sentence earns its place; no redundant details.

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

Completeness4/5

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

Given the simple tool, rich annotations, and complete schema, the description is largely sufficient. It covers the tool's purpose, output detail, and valid sections. It does not mention the agent_id lifecycle, but that's fully handled by the schema, so no critical gap.

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

Parameters3/5

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

Schema description coverage is 100%, so all parameters are already well-documented. The description adds little beyond restating the section list, which is also in the enum. The baseline of 3 is appropriate as the schema carries the parameter meaning.

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

Purpose5/5

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 ('articles from a specific section'), clearly differentiating from siblings like get_latest_articles and search_articles. It also lists all available section values, making the tool's scope unambiguous.

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

Usage Guidelines4/5

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

The description implies usage when retrieving articles by section, which is clear context. It does not explicitly mention alternatives or exclusions, but the section list and phrasing provide enough guidance to choose this tool over broader or search-based options.

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

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TDQS

B3.4/5.0
Disambiguation2/5

ask_expert and tat_ask have identical descriptions for the same function, creating direct overlap. tat_search and search_articles also cover similar search territory with unclear boundaries. Other tools like get_latest_articles and get_section_articles are distinct but the duplication undermines clear separation.

Naming Consistency2/5

Naming mixes a 'tat_' prefix on many tools (tat_search, tat_recommend) but leaves others without it (ask_expert, get_article, list_topics). The inconsistency is not systematic; some verbs like 'ask' vs 'tat_ask' are redundant while others like 'get_' and 'search_' are used in both prefixed and unprefixed forms.

Tool Count3/5

20 tools is on the heavier end for a news server; while the domain (news aggregation, search, trust metrics, comments) seems broad enough to justify many tools, the presence of duplicate tools (ask_expert/tat_ask) inflates the count unnecessarily. A trimmed set around 15 would be more appropriate.

Completeness3/5

The tool set covers core news retrieval (articles, sections, topics), search, trust/provenance, events, comments, and usage reporting. Notable gaps include user-specific features (subscriptions, saved articles) and administrative tools. The duplication suggests an unclear boundary between the agent-news layer and static news, leaving some workflows ambiguous.