Skip to main content
Glama

Attach interview prep file

attach_interview_file

Attach prep material to a specific interview so the user sees it next to that round in the dashboard: the prep document you wrote, the job description, a deck, notes the company sent. Max 3 files per interview, 20000000 bytes (20 MB) each; pass the bytes as base64. Get interview ids from get_application. Example: attach_interview_file({application_id: "…", interview_id: "…", filename: "prep-round2.md", data_base64: "IyBQcmVw…"}).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mimeNoOptional; inferred from the filename extension when omitted
filenameYes
data_base64YesBase64-encoded file bytes
interview_idYes
application_idYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only declare readOnlyHint false and destructiveHint false; the description adds meaningful behavior beyond that: it reveals the practical limit (20 MB per file), the encoding requirement (base64), and the dashboard effect. This satisfies transparency without contradicting annotations.

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?

Three focused sentences: purpose+effect, constraints+input format, and source+example. Front-loaded with the core action and immediately actionable, with zero filler.

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?

Given there is no output schema and annotations are minimal, the description covers the crucial aspects: what to attach, limits, encoding, and how to obtain IDs. It omits the mime parameter detail but that is optional and documented in the schema. Overall, sufficient for an agent to invoke the tool correctly in most scenarios.

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?

Schema description coverage is only 40% (mime and data_base64 described), so the description must compensate. It adds context for interview_id and application_id via 'Get interview ids from get_application' and the example, but still leaves filename semantics implicit. The size and base64 constraints are helpful but not parameter-specific enough to fully compensate for the gap.

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?

Purpose is clearly stated: 'Attach prep material to a specific interview' with a specific outcome ('so the user sees it next to that round in the dashboard'). The verb+resource combination is precise and distinguishes it from the sibling attach_file by specifying interview-specific attachment.

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?

Provides explicit prerequisite: 'Get interview ids from get_application' and a concrete example showing required parameters. It also sets usage boundaries (max 3 files, size limit). Missing explicit comparison to alternatives like attach_file, but the interview-specific wording implies the correct choice.

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.

TDQS

A4.4/5.0
Disambiguation5/5

Every tool targets a distinct resource and action: application, note, analysis attachment, file attachment, interview file, application detail, due actions, planned schedule, application listing, interview logging, and application updates. Even the three 'attach' tools are clearly differentiated by purpose (analysis vs CV/cover letter vs interview prep). The only potential overlap between get_due and get_planned is explicitly resolved in the descriptions.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (add_application, get_application, list_applications, update_application, attach_analysis, log_interview, etc.). The verb prefix accurately reflects the action, and nouns are singular for single-item operations and plural for list operations, maintaining a predictable convention.

Tool Count5/5

With 11 tools, the server is well-scoped for a job application tracking domain. Each tool covers a necessary function without redundancy, and the count is neither sparse nor overwhelming.

Completeness4/5

The tool set covers the full lifecycle of an application: create, read, list, update, plus notes, attachments, analysis, and interview logging. Minor gaps exist—there is no explicit delete or archive tool (though status updates can archive), and interviews cannot be directly updated or removed after logging—but these are workable within the existing surface.

Resources