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knaisoma

data-olympus MCP server

by knaisoma

KB Get Document

kb_get
Read-onlyIdempotent

Retrieve a document by ID from the governance knowledge base, returning full markdown content and metadata, including freshness status even for expired docs.

Instructions

Retrieve a document by id (STD-U-001, ADR-002, T-NNN, etc.). Returns the full content markdown plus metadata. Use this when you have a specific id (from kb_search results or session memory); use kb_search instead when you need to find a document by topic.

Always resolves regardless of expiry (ids never dangle): an expired document is still returned, with its full validity object and a computed freshness indicator (stale/expired/upcoming).

verbose: False (default) returns the full content_markdown body (kb_get exists to read the doc) with a trimmed envelope: path, git_remote_url, and last_modified_source are dropped and empty status/type/applies_when/description/validity/freshness are omitted; source_commit and last_modified provenance are kept, and in_force: false is emitted when the computed in-force predicate says the doc does NOT currently govern (deviation-only; an in-force doc omits the key). verbose=True returns the full legacy envelope with every field plus the computed in_force: bool (the single-sourced status + validity-window + not-inbox predicate; never stored in frontmatter).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesStable KB document id to retrieve.
verboseNoFalse returns the compact response; true includes all fields.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description deeply explains behavior: full content markdown plus metadata, handling of expired documents with validity and freshness, and the specific differences between verbose=false and verbose=true including which fields are dropped/kept and the computed in_force predicate.

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 for the level of richness it provides. It is front-loaded with the core purpose, then usage, then detailed envelope behavior. Each sentence earns its place; nothing is redundant or filler.

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?

Given the tool's complexity and the presence of an output schema, the description covers all essential aspects: return content, metadata, edge cases like expired documents, and the computed in_force field. It is fully sufficient for an agent to select and invoke the tool correctly.

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

Parameters5/5

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

Even though the schema has 100% coverage for both parameters, the description adds significant meaning, especially for the verbose flag. It details exactly what the compact response includes/omits and contrasts with the verbose envelope, providing far more insight than the schema's 'true includes all fields.'

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 starts with a specific verb+resource: 'Retrieve a document by id' and provides concrete id examples. It clearly differentiates from sibling tools by explicitly stating 'use kb_search instead when you need to find a document by topic.'

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?

This description gives explicit when-to-use guidance: 'Use this when you have a specific id (from kb_search results or session memory)' and the alternative 'use kb_search instead when you need to find a document by topic.' It also notes the always-resolves behavior for expired documents.

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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