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get_context

Retrieve a query-matched paragraph from an article along with its surrounding context paragraphs (with numbers) for close reading and verbatim quoting.

Instructions

单篇精读:返回该文章中命中 query 的段落及前后 window 段上下文(带段号)。 需要逐字引用原话时,必须从这里或 get_article 的返回文本中原样复制。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
windowNo
article_idYes
Behavior3/5

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 core behavior — matching paragraphs plus a window of context and paragraph numbering — and the verbatim-quoting requirement. However, it does not disclose what happens on no match, whether the operation is purely read-only, or any rate/effort limits, which would be more material given zero annotation coverage.

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?

Two sentences, zero filler. The core purpose is front-loaded, and the quoting requirement is appended as a tight second sentence that earns its place. No redundant restating of the tool name or schema.

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?

For a moderate-complexity tool (3 params, 2 required) with no output schema and no annotations, the description covers the essential call semantics: what is returned, how it is structured (paragraphs + window, with numbers), and when to use it for quoting. The only gaps are edge-case behaviors like no-match handling, which are non-critical for a straightforward close-reading operation.

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 0%, so the description must compensate. It explains the semantic of 'window' (the before/after context range) and 'query' (the matching basis for paragraphs); article_id is implied by '该文章'. This partially compensates for the missing schema docs, but it does not spell out window bounds, the query format, or the interaction between window and the returned segment count.

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

Purpose4/5

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

States a specific verb ('returns paragraphs that hit the query in a single article') with a clear resource (article_id) and an explicit window-context behavior with paragraph numbers. The phrase '单篇精读' (single-article close reading) and the mention of get_article's returned text distinguish it from the full-article sibling, though it never names a sibling outright.

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

Usage Guidelines3/5

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

The second sentence gives actionable guidance: when verbatim quoting is required, copy the text from here or from get_article. This implies a usage context (close reading/quoting vs. search or list_articles) but provides no explicit when-to-use vs. when-not-to-use guidance relative to the search or get_article siblings that overlap with it.

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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