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ReliaSim

get_chapter_narrative

Long-form narrative for the selected chapter — what the chapter adds to the complexity ladder and the key teaching point. Use when the user asks 'walk me through this' or wants the conceptual primer. Pure prose, no numerical claims; safe to summarize.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chapterNoWhich curriculum chapter the tool should answer about. Format: `bs<1-5>-<ct|leds>`. Both tracks run on the same real plant data — `ct` = Constraint-Level (interrupts rolled up to one Weibull per machine, 5 total) and `leds` = LEDS-Level (interrupts drilled down to named failure modes, 36 total). Defaults to bs1-ct when omitted.bs1-ct

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / chapter / enum
      Previous value: -[
      -  "bs1-ct",
      -  "bs2-ct",
      -  "bs3-ct",
      -  "bs4-ct",
      -  "bs1-leds",
      -  "bs2-leds",
      -  "bs3-leds",
      -  "bs4-leds"
      -]New value: +[
      +  "bs1-ct",
      +  "bs2-ct",
      +  "bs3-ct",
      +  "bs4-ct",
      +  "bs1-leds",
      +  "bs2-leds",
      +  "bs3-leds",
      +  "bs4-leds",
      +  "cmp-buffer-reliability",
      +  "cmp-shared-palletizer"
      +]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description itself discloses important behavior: the output is 'pure prose' and makes 'no numerical claims,' which tells the agent what to expect and avoid in the response. The phrase 'safe to summarize' adds a light safety/read-only signal, though it is somewhat ambiguous compared to an explicit read-only statement.

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?

The description is two sentences and front-loads the core purpose before giving usage guidance. Every clause earns its place: what the tool returns, how the user might ask for it, output style, and a safety hint.

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 tool with one optional parameter and full schema coverage, the description provides sufficient context about content, format, and usage triggers. It does not describe return structure or pagination, but the 'long-form narrative' phrase makes the expected output clear enough, and no output schema exists to carry that burden.

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%, and the schema already explains the chapter enum, the ct/leds distinction, defaults, and fallback behavior. The description references 'the selected chapter' but adds no parameter-level meaning beyond what the schema provides, so the baseline score of 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?

The description opens with 'Long-form narrative for the selected chapter — what the chapter adds to the complexity ladder and the key teaching point,' which clearly identifies the specific verb, resource, and content scope. It distinguishes itself from siblings like get_chapter_facts and explain_concept by framing the output as a conceptual narrative rather than facts or a standalone explanation.

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?

The description explicitly says to use it when the user asks 'walk me through this' or wants a 'conceptual primer,' providing clear context for when this tool is appropriate. It does not explicitly state when not to use it or name alternative tools, but the usage triggers are concrete enough to route an agent correctly.

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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