token-pilot

read_section

Read a specific section from Markdown, YAML, JSON, or CSV files by heading name, top-level key, or row range. Avoid reading the entire file to save tokens.

Instructions

Read a specific section from Markdown, YAML, JSON, or CSV files. Markdown: by heading name. YAML/JSON: by top-level key. CSV: by row range (rows:1-50). Much cheaper than reading the whole file. DOCS/DATA ONLY — heading is required; this does NOT read code by line/symbol. For source files use read_range (line range) or read_symbol (one symbol).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>",
      "heading": "<heading>"
    },
    "name": "read_section"
  }
}

Input Schema

Name	Required	Description	Default
`path`	Yes	Path to .md, .yaml, .yml, .json, or .csv file
`heading`	Yes	Section heading (Markdown), top-level key (YAML/JSON), or row range "rows:1-50" (CSV). Case-insensitive.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.47.0Jun 24, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the tool is read-only, cheap, and does not read code. It explains case-insensitivity and required heading parameter. Minor omission: no mention of error behavior if section is missing, but overall sufficient.

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 concise and front-loaded with the main purpose. Every sentence adds value, including format-specific details, cost hint, and exclusions. No waste or redundancy.

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?

The description is largely complete given no output schema or annotations. It covers file types, input format, case sensitivity, cost, and provides alternatives. A minor gap is the lack of explicit information about the return format, but the purpose is clear enough.

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 parameter descriptions in the schema are already very detailed (e.g., explaining heading types). The tool description adds usage context but does not significantly extend parameter semantics beyond what the schema provides. 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?

The description clearly states the tool reads sections from Markdown, YAML, JSON, or CSV files, specifying the extraction method for each format. It also distinguishes from siblings by explicitly naming alternatives (read_range, read_symbol) for source files.

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?

The description provides clear guidance on when to use this tool (for document/data files) and when not to (for source files). It explicitly mentions alternatives and notes that it's cheaper than reading the whole file, aiding decision-making.

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