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ReelQuoteAI Survey Tool

Presigned upload for the walkthrough video.

create_upload_url

Presigned upload for the walkthrough video. Requires stored contact email. Body: { content_type, consent, size }. Send the byte size: at or above 16 MB the response carries multipart (an upload_id, a part_size and a presigned PUT per part) instead of upload, and each part is retried on its own rather than restarting the whole video. Report each part's ETag to /upload-complete. Below the threshold, or if opening a multipart upload fails, the response is a single upload. Scope: jobs:write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoByte size of the file. Decides single vs multipart.
job_idYesThe job id (ULID)
consentYesMust be true: the customer agrees the video will be analysed and shared with the mover.
content_typeYesA video/* MIME type

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

With only minimal annotations (readOnlyHint=false, destructiveHint=false), the description carries the behavioral burden and exceeds it: it discloses the 16 MB branching behavior, the fallback when multipart creation fails, the exact response shape in each branch, the prerequisite contact-email requirement, and the post-upload ETag reporting step. Nothing contradicts the annotations.

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?

The description is dense but every sentence carries distinct information: purpose, prerequisite, body shape, threshold behavior, follow-up, fallback, scope. It is front-loaded with the core purpose and remains compact given the branching complexity it must explain. A slightly more structured layout (e.g., separating thresholds from follow-up) would earn a 5.

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

Completeness4/5

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 convey return values, and it does: it names `multipart` (with upload_id, part_size, presigned PUT per part) and `upload`, plus the fallback behavior. It covers prerequisites, scope, and follow-up. Minor gaps remain: the contents of the single `upload` response are unspecified, and the optionality of `size` in the schema vs its prominence in the description is unaddressed.

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 description coverage is 100%, so the baseline is 3. The description adds genuine meaning above the schema by explaining that size drives the single-vs-multipart decision at the 16 MB threshold, and it restates the body shape. It does not however clarify why size is optional in the schema while the body example lists it, so it stops short of 5.

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 identifies a specific resource and mechanism: 'Presigned upload for the walkthrough video.' This clearly states what the tool produces and for which asset, going well beyond a restatement of the name. It doesn't explicitly contrast itself with the sibling complete_upload or hand_off_video, so it stops short of full sibling differentiation.

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

Usage Guidelines3/5

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

The description gives a prerequisite ('Requires stored contact email'), an auth scope ('jobs:write'), and a clear threshold rule for when multipart vs single upload applies. It also points to the follow-up action ('Report each part's ETag to /upload-complete'). However, it never explicitly states when to use this tool versus an alternative or when not to use it; usage context is strong but exclusions/alternatives are only implied.

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

A3.5/5.0
Disambiguation5/5

Each tool targets a distinct action or resource: job lifecycle, upload steps, quote variants, key management, and webhook replay are clearly separated. Even the three pricing tools are differentiated by context (pre-job ballpark, direct quote, date-window pricing).

Naming Consistency4/5

Almost all tools follow a verb_noun snake_case pattern (create_job, list_jobs, set_contact, rotate_key). Minor deviations like ballpark_estimate (no verb) and get_cube_sheet_csv (format suffix) keep it from being perfectly consistent.

Tool Count2/5

32 tools is a large surface for a survey tool, crossing the 25+ threshold. Many key-management and webhook-delivery tools feel like a separate API admin surface rather than core survey workflow.

Completeness4/5

The core survey flow is well covered: create job, capture contact/access/date, upload video, edit inventory, approve, book, and report outcome. Minor gaps like no cancel/delete job or webhook subscription management are workarounds.

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