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numenews

numenews

by DisMosGit
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_history

Find when a number appeared in news articles: returns publication dates, item IDs, and snippets, newest first, within a specified day window (default 30).

Instructions

Return when a number was activated in the news, newest first, inside the last days days.

One entry per (news item, number) pair the ingest stored: the day the article was published, the item's id and the snippet the number was read in. The window ends today and includes it (days=1 is today). The original design sketch wrote the signature as get_history(number); the read is a window, so days is a parameter whose default of 30 matches the memory window. Needs Qdrant only.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "number": "<number>"
    },
    "name": "get_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoLength of the window in days, ending today.
numberYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses ordering (newest first), entry granularity (one row per news-item/number pair), the exact field contents returned, window inclusivity (days=1 means today), and the infrastructure dependency (Qdrant only). It omits pagination/result caps and empty-result behavior, but the behavioral disclosure is substantial.

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

Conciseness3/5

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

The core semantics are front-loaded, but the sentence about the original design sketch signature ('get_history(number)') is narrative filler that doesn't help an agent invoke the tool, diluting an otherwise tight description.

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?

An output schema exists so return values need not be explained, yet the description still sketches them helpfully. With no annotations, the added ordering, dependency, and window semantics make the definition complete enough for correct invocation; only result-limit behavior is unaddressed.

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

Parameters4/5

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

Schema coverage is 50% (days documented, number not). The description compensates well for days by explaining the window ends today, is inclusive, and that the default of 30 matches the memory window; number is only implied as the value to look up, which is the residual gap.

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?

States a specific verb+resource: returns when a number was activated in news, newest first, within a day window. This is clearly distinguishable from siblings like find_patterns or fetch_news, and it names the entity granularity (news item, number) pair.

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?

Usage is implied by the wording (a historical lookup over a window), but there is no explicit when-to-use/when-not guidance and no alternatives named among siblings such as find_patterns or query_qdrant. An agent can infer the intent but gets no routing help.

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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