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get_concept

Read-only

Fetch a concept node by slug or UID to view its frontmatter, body, and graph connections. Use body:full for complete content when answering questions.

Instructions

Fetch one node by exactly one selector: slug (canonical slug or unique alias) or immutable uid. Successful responses always carry both the permanent uid and current canonical slug; graph relations and graph-operation inputs remain slug-based. Returns frontmatter, body, direct graph neighbors, outgoingEdges (each {to, via, rationale?}, the rationale being the stored relation_notes sentence when one exists), and mtime. By default you get excerpt — the first prose paragraph only. The node body is where the construction rules put definition, evidence, confidence, and in-scope/out-of-scope, so pass body: "full" whenever you are reading a node to answer a question rather than just to identify it. bodyInfo always reports totalChars / returnedChars / truncated, so a partial read is never silent. For K specific selectors in one call use get_concepts({slugs: [...]}) or get_concepts({uids: [...]}). When a slug does not resolve, structured growth guidance remains available.

Input Schema

TableJSON Schema

Name	Required	Description
`uid`	No	Exact permanent node UID. Use instead of `slug`, never together with it.
`body`	No	`excerpt` (default) returns the first prose paragraph as `excerpt`. `full` returns the entire markdown body as `body` and omits `excerpt`. Use `full` when the answer depends on what the node actually says — evidence paths, confidence, scope boundaries.
`slug`	No	Vault-relative slug (e.g. projects/auth-platform), unique tail slug, or frontmatter `slug` alias. Omit the .md extension.

Output Schema

TableJSON Schema

Name	Required	Description
`uid`	Yes	Permanent immutable node identity.
`body`	No	Entire markdown body. Present only when the caller passed `body: "full"`.
`slug`	Yes
`mtime`	Yes
`excerpt`	No	First prose paragraph. Present only when `body` is `excerpt` (the default).
`bodyInfo`	Yes	How much of the body this response carries — always present, so truncation is never silent.
`warnings`	No
`neighbors`	Yes	Direct graph neighbor buckets.
`frontmatter`	Yes	Resolved markdown frontmatter.
`outgoingEdges`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.13.0Sep 11, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses critical behaviors: successful responses always include both uid and slug, graph relations are slug-based, and the default excerpt truncation is always accompanied by bodyInfo metrics so partial reads are never silent. This is rich context that the annotations alone do not convey, and it does not contradict them.

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?

The description is dense and front-loaded with the core selector logic, then builds to return details and usage notes. The bold key phrases help scanning, and every sentence carries information; however, it is on the longer side for a single-tool definition, so a 4 reflects the trade-off between completeness and brevity.

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?

Even though an output schema exists, the description still enumerates the return fields (frontmatter, body, neighbors, edges, mtime) and explains the excerpt/bodyInfo mechanism, making the tool fully understandable without opening the schema. It also covers the error case and points to the plural variant, so an agent has everything needed to invoke it correctly.

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 input schema already documents all three parameters with 100% coverage, so the baseline is 3. The description adds value by stating the exclusivity rule between uid and slug (which the schema implies but does not state globally) and reinforcing the body parameter's usage semantics, though it largely repeats the schema's own guidance. This pushes it above baseline but not to 5.

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 a specific verb-resource pair ('Fetch one node') and immediately clarifies the two selectors (slug or uid), making the tool's purpose unmistakable. It also distinguishes itself from the sibling get_concepts by explicitly routing bulk lookups there, so an agent can tell them apart without reading schemas.

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 gives explicit when-to-use guidance for the body parameter ('use full when you are reading a node to answer a question rather than just to identify it') and names the alternative for multi-selector calls ('For K specific selectors in one call use get_concepts'). It also hints at error behavior ('When a slug does not resolve, structured growth guidance remains available'), leaving little to inference.

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