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What will a lawyer cost?

estimate_legal_cost
Read-onlyIdempotent

Fee information for a matter type or a specific lawyer, labeled as published fees, confirmed quotes or sourced market figures. Says plainly when data is insufficient instead of guessing. Not a quote.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNo
stateNoUS state, two-letter code or name, e.g. CA or California
budget_maxNoTotal budget the user mentioned, in US dollars
attorney_idNo
descriptionNoShort description of the legal need in the user's words. Used only to pick a practice area; not stored.
practice_areaNo
billing_preferenceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior4/5

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

Annotations already cover safety (readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=false), so the description's real contribution is disclosing output provenance — published fees vs. confirmed quotes vs. sourced market figures — and the failure behavior of stating plainly when data is insufficient. That is genuine behavioral context beyond the 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.

Conciseness4/5

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

Three short sentences, front-loaded with what the tool returns before the honesty caveat. Slight redundancy between 'instead of guessing' and 'Not a quote', but no filler sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description usefully characterizes the returned fee labels and the insufficient-data case, which is the right thing to disclose. However, for a seven-parameter tool with 43% schema coverage it leaves input semantics largely unexplained, so an agent can invoke it but not confidently populate the optional filters.

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

Parameters2/5

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

Schema description coverage is only 43% across seven parameters, so the description must compensate and does not. It loosely gestures at matter type and specific lawyer, but says nothing about scope, state, budget_max, billing_preference, or the free-text description field, leaving the two undescribed enums unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource — fee information — for either a matter type or a specific lawyer, which maps onto the practice_area and attorney_id inputs. It is clearly distinct from siblings like get_attorney_profile or compare_attorneys, though the verb 'estimate' from the name is only implied by the 'fee information' phrasing.

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

Usage Guidelines2/5

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

The only guidance is the caveat 'Not a quote', which frames the output rather than when to call the tool. With nine siblings in the matching family, no alternative is named and no condition for choosing this tool over get_attorney_profile or compare_attorneys is given.

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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