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Glama

resolve_value

Resolves a phrase, code, or spelling against a column's published values to return the stored spelling needed in a filter, or the closest matches when no exact value exists.

Instructions

Resolve a phrase, a code or a spelling against one column's published values, before writing a literal into a filter whose stored spelling get_table_context does not already list in full. Answers, in order of preference: stored - the text is a listed value, or folds to one, and the reply carries the spelling a predicate must use; definition - the text names what a value's note says it means; nearest - the listed values closest to the text, ranked; none; or unavailable where the column publishes no value list, lost it on the latest print, or redacts it. Every reply carries the column's coverage and how many values the print listed, plus a caveat sentence wherever that list is a sample - a spelling absent from a sample is not evidence it is absent from the column. An exhaustive list of at most fifty values rides along whole as domain, so a small vocabulary needs one call; on a table read in part, exhaustive is false, the reply carries the table's scope and row_count, and domain is the scanned rows' whole domain. Paged: every page repeats the scalar keys; the answer list comes before domain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
partNoA part of the column, by its path as the print keys it (`.status`, `[*]`); omit it to resolve against the column itself
textYesThe phrase, code or spelling from the question, as written
tableYesFully-qualified table name
columnYesColumn name as the print spells it
cursorNo`next_cursor` from this call's previous page; omit for the first page
connectionNoWhich database to read, by connection name; needed only when the server serves several, and the error for a missing one lists them. Omit it for the server's default

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations the description carries the full burden and mostly does: it enumerates the reply variants (stored/definition/nearest/none/unavailable), the `coverage`/`listed` fields, the sample caveat, `exhaustive`/`scope`/`row_count`, and paging semantics. It never explicitly states the operation is read-only or side-effect-free, leaving safety to inference.

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?

Purpose and the key filter caveat are front-loaded, and most sentences carry real information (reply precedence order, sampling caveat, paging). It is dense and idiom-heavy ('the print', 'rides along whole', 'lost it on the latest print'), which slightly hurts scannability but isn't wasted words.

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?

There is no output schema, so the description must explain return values, and it does thoroughly — reply variants, coverage/listed counters, sample caveat, `domain` for small vocabularies, partial-read `scope`/`row_count`, and paging order. Nothing an agent needs to call and interpret this tool correctly is missing.

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%, so the six parameters are already documented (including `part` path syntax and `cursor`). The description adds only marginal parameter-level meaning, mainly paging notes that are really about the reply shape; baseline 3 is appropriate.

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+resource+scope: resolving a phrase/code/spelling against one column's published values. It explicitly distinguishes itself from sibling `get_table_context` by describing the exact gap it fills ('whose stored spelling get_table_context does not already list in full').

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?

Names the trigger condition clearly — use before writing a literal into a filter when the stored spelling isn't fully listed by `get_table_context` — and the `unavailable`/`none` branches hint at when it won't help. It stops short of explicit when-not guidance or naming other siblings, but the context is concrete.

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