Skip to main content
Glama

list_sections

List every section of a report with its size, before you decide what to pull. Returns sections (titles, in order) plus section_details — same order, one entry per section with title, has_tables, chars and estimated_tokens. Use estimated_tokens to avoid pulling a chapter that would blow your context, and has_tables to know whether the chapter needs special handling (tables are the part RAG pipelines usually get wrong). Then call get_section with a heading keyword — the headings are in the report's own language.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idYesReport id, from list_reports items[].id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden, and it does meaningful work: it discloses the exact return shape (`sections` and `section_details` with title/has_tables/chars/estimated_tokens) and explains how to use estimated_tokens and has_tables. It does not state permissions or that this is a read-only, non-mutating operation, which is the remaining gap.

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-loads the core action and the payoff (sizes before pulling), then describes the return shape and the follow-up. Slightly dense with the parenthetical aside about RAG pipelines, but nearly every clause carries actionable information.

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?

There is no output schema, so the description correctly compensates by enumerating the returned fields and their meaning, and it links to the next tool in the workflow. Nothing needed to invoke or interpret this call 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 coverage is 100% and there is only one parameter, so the schema already documents document_id fully (including its provenance from list_reports). The description adds no syntax or format detail for it, so the baseline 3 applies.

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 (list) and resource (sections of a report) plus the scope (with size, in order). It is clearly distinguishable from get_section, which pulls a single chapter, and from list_reports, which enumerates reports.

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?

Explicitly frames the call as a prerequisite step ('before you decide what to pull') and routes the agent to the follow-up tool: 'Then call get_section with a heading keyword.' The when-to-use and the alternative are both named.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.