Skip to main content
Glama

Review a quote

get_quote
Read-onlyIdempotent

Review one quote in a standard shape, from a stored quote_reference (get_quotes) or a pasted quote — the dashboard's Copy JSON, a POST /quotes or run_quote response, or a bare engine output with debug (quote_gz: base64 gzip of the same JSON, for big pastes). Pass exactly one. Returns { source, quote_reference, project_reference, project_name, version_reference, version, created_at, outcome: { decision (quoted | declined | referred | error), result, valid, status, error, exec_time_ms, engine_time_ms, steps, slowest_steps }, input, output, rules: { exclusions, refers, excesses, endorsements: { fired_count, checked_count, fired: [{ step, name, exp, values, result }] } }, result_build: { formula, values, result }, valid_rule: { exp, values, result }, build: [{ order, id, name, type, description, ms, logic: [{ name, exp | formula, values, result }], lookups, table_rows, output, errors }], errors, has_trace, truncated, amendment, quote_url, version_url, replay, how_to_explain, next_steps }. outcome is always what the engine priced. amendment (stored quotes only; null when never touched) is { result, valid, sold, amended_at, log: [{ when, who, via (dashboard | api | mcp), result: { from, to }, valid, sold, note }] }: the price, validity or sold flag someone set afterwards (dashboard, API or amend_quote), and the log of who changed what. Step names, types, descriptions and collection lookups come from the version's model when it is on this instance. A quote without a step trace is re-priced against its version (replay: true forces it); replay reports the replayed vs stored result and whether they match. Nothing is saved. Responses are kept under ~80 KB: large quotes come back clipped or as an overview (truncated says which) — pass steps: [<id>, …] for those steps in full. If even the overview is too big the result is { too_large: true, outcome, rules counts, next_steps }: review a few steps at a time, or ask the user to paste the part they want explained. Explain the result back following how_to_explain.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_quote"
  }
}

Input Schema

NameRequiredDescriptionDefault
quoteNoA pasted quote: the dashboard's Copy JSON, a POST /quotes or run_quote response, or an engine output with `debug`. A JSON string is also accepted.
stepsNoOptional. Step ids to return in full (and only those in `build`). Use after a truncated review, or to focus on one step.
replayNoOptional. Re-price the quote's input against its version even when it has a step trace, and compare with the stored result. Never saved.
quote_gzNoBase64-encoded gzip of the quote JSON, instead of `quote` when it is too big to pass inline.
quote_referenceNoA stored quote's reference, from get_quotes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Goes well past the readOnly/idempotent annotations: states "Nothing is saved," discloses the ~80 KB response budget and how clipping/overview/`too_large` degrade, explains automatic re-pricing of untraced quotes and what `replay` reports, and documents that `amendment` reflects post-hoc changes via dashboard, API or amend_quote. These are exactly the operational traits an agent cannot get from structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening sentence and the trailing caveats are front-loaded and useful, but the middle is a single dense paragraph enumerating a very large return shape inline. With no output schema this content has to live somewhere, yet the wall-of-text field listing is hard to scan and would read better structured or pushed into an output schema.

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?

For a 5-parameter, nested-input tool with no output schema, the definition covers the return contract exhaustively — outcome, amendment log, rules breakdown, build steps, errors, truncation and next_steps — plus the edge cases (no trace, oversized payload). Nothing an agent needs in order to call it or interpret the response appears to be missing.

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 100%, so the baseline is 3, but the description adds real constraints the schema does not encode: the mutual-exclusivity rule between `quote` and `quote_reference` ("Pass exactly one"), when `quote_gz` is preferred over `quote`, and the two distinct uses of `steps`. That extra meaning justifies one point above baseline.

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?

"Review one quote in a standard shape" gives a specific verb and resource, and the description immediately distinguishes the two input modes (stored `quote_reference` from get_quotes vs. a pasted `quote`). An agent can tell this apart from run_quote and amend_quote 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?

Explicit routing instructions: "Pass exactly one" source, use get_quotes to obtain a reference, use `steps` "after a truncated review, or to focus on one step," and use `replay: true` to force re-pricing. What is missing is a direct statement of when to pick get_quote over run_quote or amend_quote — the reader must infer that this one is the non-mutating inspection path.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources