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ai_summarize

Read-onlyIdempotent

Any text → crisp bullet points — Compress up to 16K characters of anything — articles, transcripts, email threads, reports — into 3-5 precise bullet points, one micro-payment per call. No API key, no subscription, no prompt engineering: send text=, get bullets back as clean JSON. The digest step for agent pipelines that read more than they can carry in context. Required input: text. Priced $0.03 per call over x402 on Base; send a prepaid x-credit-token header for unlimited calls (no free tier on this tool). No API key required.

Input Schema

NameRequiredDescriptionDefault
textYesText to summarize

Output Schema

NameRequiredDescriptionDefault
dataNoThe result payload. Shape is service-specific; every field is documented in the tool description.
serviceNoThe service id that answered.
checkedAtNoISO-8601 timestamp of when the underlying reads were taken.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / properties / data / description
      Previous value: -"The result payload. Shape is service-specific; every field is documented in the service description above."New value: +"The result payload. Shape is service-specific; every field is documented in the tool description."
  2. Changed1 schema field changed
    • removedOutput schema / required
      Removed value: -[
      -  "data"
      -]
  3. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description adds the operationally critical details those annotations cannot: exact cost ($0.03/call over x402 on Base), the prepaid x-credit-token header for unlimited calls, absence of a free tier, and no API key/prompt engineering required. This is exactly the payment/auth context an agent needs before calling a metered tool.

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

Conciseness4/5

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

Front-loaded with the punchline (any text → crisp bullets) and efficiently structured, but there is redundancy: 'No API key' appears twice, and 'one micro-payment per call' is restated as '$0.03 per call'. Minor waste keeps it below a 5.

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?

An output schema exists, so return-shape detail is unnecessary, and the description covers purpose, input limit, payment/auth mechanics, and pricing. For a single-parameter read-only tool, nothing an agent needs to invoke it correctly is missing.

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 100% and the single param is documented, so baseline is 3. The description adds a real constraint absent from the schema — the 16K-character input limit and the 'send text=, get bullets back' calling convention — which meaningfully supplements the bare 'Text to summarize' field.

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 and resource: compress any text (up to 16K chars) into 3-5 bullet points, with concrete input examples (articles, transcripts, email threads, reports). The purpose is unmistakable, but no sibling tool (ai_extract, ai_translate, web_extract) is named to distinguish the boundary between summarization and extraction/translation.

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?

Gives clear usage context: 'The digest step for agent pipelines that read more than they can carry in context.' This tells the agent when the tool fits. However, it offers no explicit exclusions or named alternatives (e.g. use ai_extract for structured fields), so the routing guidance stops short of a 5.

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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