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Find nodes by exact tag match. Returns near tags if none match, helping refine queries, with results sorted newest-first.

Instructions

List nodes whose tags array contains the given tag — exact match. Common tag families: kind:<type> (observation, experiment, idea, reference, …), sig:<level> (low/medium/high), role:<role> (jot/review/synthesise/revised), lang:<code> (ru/en/mixed/other — auto-detected from body), topic:<word> (up to 5 auto-derived tokens — a node's MOST-MENTIONED words, weighted toward a name somebody chose; a compound like figma-макет is also tagged by its parts), status:<state> (hypotheses and tasks). Exact match, no stemming — but a miss comes back with the near tags that DO exist in scope, so an empty answer tells you what to ask instead. For loose matching over text use search prefix*. Newest-first when multiple match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagYesTag value (case-sensitive).
initiativeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.5

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does so well: it discloses exact-match/no-stemming behavior, that misses return near tags in scope, and that results are newest-first. That is meaningful operational context beyond the schema, though it says nothing about result size, pagination, or scoping by initiative.

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-loads the core purpose in the first clause, then layers detail. It is one long sentence and the tag-family enumeration is verbose, but nearly every clause conveys a distinct, useful fact rather than restating the name.

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 list tool with no output schema and no annotations, the description covers matching semantics, fallback behavior, and ordering well. The main gap is the undocumented `initiative` scoping parameter, which an agent would need to understand before constraining a query.

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?

Schema coverage is 50%: `tag` is documented in the schema as case-sensitive, but the description enriches it substantially by enumerating tag families (kind:, sig:, role:, lang:, topic:, status:) and their value shapes. The `initiative` parameter is undocumented in both schema and description, keeping this below a 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?

States a specific verb and resource ('List nodes') plus the exact matching semantics ('tags array contains the given tag — exact match'). It also distinguishes itself from the sibling `search` by noting that loose text matching belongs there. An agent can tell this apart from `search` or `recall` without opening any schema.

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

Usage Guidelines4/5

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

Explicitly names the alternative for loose matching ('For loose matching over text use `search prefix*`') and describes the miss/fallback behavior that tells the agent what to query instead. It gives clear usage context but does not enumerate when-not to use it against the many other retrieval siblings.

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