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Get an engineering concept

get_concept
Read-only

Return one engineering concept's definition, a cited ≤60-word answer, and the books it's grounded in (EP-217, derived from bicycle-guide's canonical guide bodies).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesConcept slug, e.g. prompt-engineering-quality.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
laneYes
nameYes
slugYes
answerYes
apex_urlYes
definitionYes
api_versionYes
grounded_inYes
source_guidesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already establish the safe read-only, closed-world profile, and the description adds genuinely new context: the answer is cited and capped at 60 words, and results carry the grounding books and a source lineage (bicycle-guide canonical guide bodies, EP-217). It does not say what happens for an unknown slug, which keeps it out of 5 territory.

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?

A single front-loaded sentence that wastes nothing and puts the payload shape before the provenance aside. The trailing "EP-217" internal code is opaque to an outside agent, but it is contained in a parenthetical and does not obscure the main claim.

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 one-parameter read tool with an output schema, the description covers purpose, return contents, and data provenance, so an agent has enough to call it correctly. Only the failure behavior for an invalid slug is left unstated, a minor gap given the output schema exists.

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 lone slug parameter is documented with a concrete example, so the schema does the heavy lifting. The description adds no further format or naming guidance beyond what the schema already provides, making 3 the correct baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ("Return") and a specific resource ("one engineering concept's definition") plus the exact shape of what comes back. It implicitly separates itself from get_library_book, but it never names a sibling or states the distinction explicitly, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance and no named alternative among the six siblings. The slug-based lookup model is only inferable from the parameter, leaving the agent to guess whether this or search_library is the right entry point.

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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