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feedmyagent

by makash
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Query Security Feed

query_security_feed
Read-only

Search AI technology, compliance, and security news for agents by natural-language query to find items relevant to a current task or topic. Returns ranked results; no API key required.

Instructions

Search the ainews feed for items relevant to what your agent is about to do — technology, compliance, and security news for AI agents — ranked by relevance to your natural-language query. Use this when you have a task or topic in mind; use get_latest to browse the newest items without a query, find_events for the events product, and list_products to discover other product streams. Needs no API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoOptional tags an item must all carry (AND), lowercase and hyphenated, e.g. ["mcp", "prompt-injection"] or ["advisory"]. Call get_latest without tags first if you don't know the vocabulary.
limitNoHow many items to return; smaller values keep responses short.
queryYesWhat your agent is doing or researching, in plain language; matched against item titles, summaries and tags. Example: "adding an MCP server to our coding agent" or "EU AI Act obligations for chatbots".
productNoOptional product stream to read (default ainews).ainews

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesMatching feed items.
sourceYesProvenance of the payload.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.50.0
    • changedInput schema / properties / limit / description
      Previous value: -"Maximum number of items to return."New value: +"How many items to return; smaller values keep responses short."
    • changedInput schema / properties / query / description
      Previous value: -"Natural language description of what the agent is doing."New value: +"What your agent is doing or researching, in plain language; matched against item titles, summaries and tags. Example: \"adding an MCP server to our coding agent\" or \"EU AI Act obligations for chatbots\"."
    • changedInput schema / properties / tags / description
      Previous value: -"Optional tag filters applied to feed search."New value: +"Optional tags an item must all carry (AND), lowercase and hyphenated, e.g. [\"mcp\", \"prompt-injection\"] or [\"advisory\"]. Call get_latest without tags first if you don't know the vocabulary."
  2. First observedv0.4.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/non-destructive, and the description adds useful context beyond them: results are relevance-ranked rather than chronological, and no API key is required. It doesn't discuss rate limits or result freshness, but with a full output schema the remaining burden is small.

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?

Three sentences: capability first, routing second, a short operational note last. No filler, and the highest-value information is front-loaded.

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

Completeness5/5

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

With an output schema present, annotations covering the safety profile, and 100% parameter coverage in the schema, the description only needs to cover purpose and routing — both of which it does thoroughly. Nothing needed for correct invocation is missing.

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 the schema already documents query matching (titles, summaries, tags), tag AND semantics, and the limit default. The description adds only the framing of query as 'what your agent is about to do', which is marginal 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.

Purpose5/5

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

States a specific verb (Search) and resource (ainews feed), specifies ranking by relevance to a natural-language query, and explicitly contrasts itself with get_latest, find_events, and list_products. An agent can select it without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit when-to-use condition ('when you have a task or topic in mind') and names three alternatives with the condition that selects each (browse newest, events product, discover other streams). This is textbook routing guidance.

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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