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Read a library publication

read_publication
Read-onlyIdempotent

Fetches a case-library publication's full text by ID so you can verify whether the reference discloses the claim requirements.

Instructions

Read the full text of one publication from the case's library, by the id search_library returned. Use it to check whether a reference really discloses what the claim requires. Counts against the tool budget.

Input Schema

NameRequiredDescriptionDefault
episode_idYesThe episode id returned by start_task, e.g. ep_3f9c2a1b0d4e5f6a7b8c9d0e
publicationYesPublication id from search_library results, e.g. US20190012345A1

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.3
    • addedInput schema / properties / episode_id / description
      Added value: +"The episode id returned by start_task, e.g. ep_3f9c2a1b0d4e5f6a7b8c9d0e"
    • addedInput schema / properties / publication / description
      Added value: +"Publication id from search_library results, e.g. US20190012345A1"
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare the read-only, idempotent, non-destructive, closed-world profile, so the description doesn't need to repeat safety facts. It adds genuinely new behavioral information by warning that the call 'counts against the tool budget', which is not encoded anywhere in the annotations. It stops short of noting result size or truncation behavior for full texts.

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 short sentences, front-loaded with what the tool returns, followed by why to use it and the budget cost. No filler and nothing buried.

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 simple two-parameter read tool with full annotation coverage, the description covers purpose, input provenance, motivation, and cost. It leaves the return value underspecified beyond 'full text' (length, truncation, not-found behavior), which is a minor gap given there is no output schema.

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 coverage is 100%, with both episode_id and publication documented with format examples, so the baseline is 3. The description only restates the publication id's provenance from search_library — which the schema already says — and adds nothing about episode_id or id format.

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 (read) and resource (full text of one publication), and scopes it to 'one publication from the case's library', which cleanly separates it from the sibling search_library. An agent can tell exactly what this retrieves without opening the schema.

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 explicit usage context: obtain the id from search_library, then use it to verify whether a reference actually discloses what a claim requires. It names the sibling that produces the input but doesn't spell out exclusions (e.g., don't call it just to preview a title), so it stops short of a full when/when-not rubric.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.