Moxlade — Upwork buyer intelligence

What a result field means

describe_fields

Read-onlyIdempotent

What every field of a result MEANS — the glossary the schema cannot deliver.

Call it the moment a field puzzles you, instead of guessing from its name. Every result field this server returns is documented: what it is, its type, the closed set of values where it has one, and — for anything nullable — what a null MEANS, which is never the same as zero.

Pass tool for one tool's fields. Omit it to get the list of tools with a field count each, which is small; asking for everything at once is not offered because the whole glossary is large and you rarely want all of it.

Free: read-only, unmetered, and it answers on every plan state. It documents the RESPONSE CONTRACT — what a field means — never how a number is computed.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`tool`	No	The tool whose fields you want, spelled exactly as tools/list names it ("get_buyer_quality"). Omit it to get the list of documented tools with a field count each, which is how you find the name to pass. An unknown name is refused, not silently emptied.

Output Schema

TableJSON Schema

Name	Required	Description
`note`	No	How to ask for one tool, on the listing form.
`tool`	No	The tool these fields belong to. Absent when you asked for the listing.
`tools`	No	The tools and their field counts, returned when you call with no argument.
`fields`	No	Every documented field of that tool's result, sub-shapes flattened and named by `shape`.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The description adds substantial behavioral context beyond the annotations: it is read-only, unmetered, and works on every plan state; unknown tool names are refused; nullable fields have distinct null semantics; and the tool never explains computation. This goes well beyond the readOnlyHint and idempotentHint annotations without contradicting them.

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 front-loaded with the core purpose, then moves logically through when to call, what is documented, how to use the parameter, and cost/scope. Every sentence earns its place; there is no filler or redundant restatement of the tool name.

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?

The description covers purpose, usage triggering, parameter behavior, output scope, limitations, and operational characteristics. Since an output schema is present, the description does not need to enumerate return values, and the provided context is fully sufficient for an agent to select and invoke this tool correctly.

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?

The schema already documents the `tool` parameter thoroughly, including spelling, omission behavior, and unknown-name refusal, so the baseline is 3. The description reinforces the parameter behavior and adds the useful detail that the full glossary is intentionally not returned at once, but it does not materially expand on the schema's parameter documentation.

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 strong, specific statement: it is the glossary explaining what every result field MEANS, which the schema cannot deliver. It clearly identifies the resource (result fields returned by the server) and distinguishes this tool from data-retrieval siblings by framing it as the response-contract documentation tool.

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: 'Call it the moment a field puzzles you, instead of guessing from its name.' It also explains the two invocation modes — pass `tool` for one tool's fields, omit it to get the small list of documented tools — and sets an exclusion: it documents meaning, never computation.

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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TDQS

A4.6/5.0

Disambiguation5/5

Each tool maps to a distinct resource or action: search, filter validation, saved-search management, buyer lookup, buyer quality, job scoring, market rates, and account/plan introspection. The get_* tools are cleanly separated by complements such as get_job vs get_job_score and get_buyer vs get_buyer_quality, so an agent should not struggle to pick the right one.

Naming Consistency5/5

All tool names consistently use snake_case verb_noun or verb_adjective_noun patterns, such as search_jobs, check_prefilter, delete_saved_search, and get_buyer_quality. There are no camelCase names, vague verb-only names, or mixed conventions.

Tool Count5/5

At 15 tools, the server sits exactly within the ideal range and each tool earns its place in the workflow. The set covers discovery, enrichment, saved-search lifecycle, and account introspection without obvious redundancy.

Completeness4/5

The core workflow is well covered: search, prefilter validation, job detail, scoring, buyer identity, payment quality, saved-search create/list/delete, and plan/activity visibility. The main gap is the lack of an update operation for an existing saved search, such as changing its filter or attaching a webhook later; this is a minor workaround rather than a blocking dead end.

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