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sebastienrousseau

inclusio-mcp

by sebastienrousseau
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Python
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Count registered documents

doc_count
Read-onlyIdempotent

Count registered documents in data/meta.yaml for an initial health and connectivity check before deeper inspection.

Instructions

Count the documents registered in data/meta.yaml.

    Purpose:
    Fast, lightweight health and connectivity probe that counts registered documents in the manifest.

    When to use:
    - When verifying server availability and project manifest readability with minimal payload size.
    - When performing initial connectivity checks before deeper inspection.

    When NOT to use:
    - Do NOT use when full metadata (doc_id, class, title) is needed; use `list_docs` instead.

    Behavioral transparency:
    Read-only, instantaneous manifest header check.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.7

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so the safety profile is covered structurally. The description adds genuinely useful behavioral context beyond them: it is 'fast, lightweight', has 'minimal payload size', and is an 'instantaneous manifest header check', which tells the agent about cost and scope. It stops short of describing the return shape, but the output schema covers that.

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-loaded with a one-line summary, then cleanly sectioned into Purpose, When to use, When NOT to use, and Behavioral transparency. The section headers make it scannable, though the Purpose section partially restates the opening sentence, adding mild redundancy.

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?

For a zero-parameter, read-only probe with an output schema and rich annotations, the description covers everything an agent needs: what it counts, its cost profile, when to prefer it, and which sibling to use instead. Return values are correctly left to the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, which is the baseline-4 case; there is no parameter semantics to document. The description correctly implies the tool requires no input by describing a manifest header read.

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?

Starts with a specific verb+resource ('Count the documents registered in data/meta.yaml') and frames the tool as a health/connectivity probe. It explicitly distinguishes itself from the sibling `list_docs`, so an agent can choose between them without opening either schema.

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?

Provides explicit 'When to use' (availability checks, initial connectivity probes) and 'When NOT to use' (full metadata needed → use `list_docs`), naming the alternative tool directly. This is the strongest possible routing guidance.

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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