get_publication_fulltextFull OCR text of a publication, optionally returning ~2000-char excerpts around keyword matches (accent-insensitive; capped — see match_count vs excerpts_returned).
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | No | ||
| max_excerpts | No | Default 10, max 25 | |
| context_chars | No | Default 2000, max 5000 | |
| publication_id | Yes |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Input schema / additionalPropertiesRemoved value: -falseInput schema / properties / context_chars / maximumAdded value: +9007199254740991Input schema / properties / context_chars / minimumAdded value: +-9007199254740991Input schema / properties / max_excerpts / maximumAdded value: +9007199254740991Input schema / properties / max_excerpts / minimumAdded value: +-9007199254740991Input schema / properties / publication_id / maximumAdded value: +9007199254740991Input schema / properties / publication_id / minimumAdded value: +-9007199254740991Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnly/idempotent annotations, the description discloses accent-insensitive keyword matching, capped excerpts, and a subtle distinction between match_count and excerpts_returned. This is valuable behavioral context that helps set expectations about output limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It efficiently conveys the main purpose and key optional behavior in under 25 words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description leaves some ambiguity about the return structure (e.g., what exactly match_count and excerpts_returned are, and whether full text is always returned). It provides a hint but not a complete specification of the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 50% schema coverage, the description partially compensates by explaining the role of keyword (excerpts around matches) and context_chars (~2000 chars). It doesn't clarify publication_id, but that is self-evident from the tool name. The capping mention also hints at max_excerpts semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns full OCR text of a publication and optionally excerpts around keyword matches. It is specific about the resource (publication) and operation, but it does not explicitly differentiate from sibling tools like get_document or get_article.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: use when you need full OCR text or keyword-matching excerpts. However, there is no explicit guidance on when to choose this over alternatives, nor any exclusions or prerequisites.
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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