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GigNGo: US locals for home jobs and errands

See what people budget for a job

check_job_price
Read-onlyIdempotent

Use this when someone asks what a home job or errand costs or what to pay for it, e.g. "how much to mow a lawn", "what do movers charge", "what should I pay for TV mounting". Returns the middle budget and the middle half of budgets that people set when they posted that job on GigNGo, with how many posts it counts and a link to the cost guide. These are budgets from across the US, not quotes, not local prices and not prices paid for finished jobs: say so, with the number of posts. A job with fewer than 5 posts has no figure; the reply then lists the jobs that do. Pass on the limits field.

Input Schema

NameRequiredDescriptionDefault
jobYesThe job in a few words, e.g. "lawn mowing", "moving help", "tv mounting".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare it a safe read, and the description adds substantial context beyond them: the data is US-wide posted budgets, explicitly not quotes, not local prices and not prices paid, must be reported with the post count, has a 5-post minimum, and the `limits` field must be relayed. That is exactly the kind of caveat an agent would otherwise get wrong.

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 trigger condition is front-loaded, followed by what is returned, the mandatory caveat, the empty-result behavior and the `limits` handoff. Each sentence carries a distinct instruction; nothing repeats the schema or the title.

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?

With no output schema, the description carries the return-value burden and does: median, interquartile range, post count and cost-guide link. Edge-case behavior and the required user-facing disclaimer are both covered, so an agent can both call and report correctly.

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% and the single `job` param is already documented, so the baseline is 3. The description pushes slightly above it by showing the natural-language granularity callers use ("how much to mow a lawn", "what do movers charge"), which signals a short phrase rather than a category ID.

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 — returns the middle budget and the middle half of budgets people set for a posted job — with three concrete example queries. No sibling tool covers pricing, and the description makes that domain obvious without opening a schema.

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?

"Use this when someone asks what a home job or errand costs or what to pay for it" gives an explicit trigger, reinforced by three sample phrasings. It also states when the tool cannot answer (fewer than 5 posts) and what to do instead, which is the closest thing to an alternative-path rule here.

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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